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1
DONG, Le, Wen-Ling WU, Shuang WU, and Jian ZOU. "Another Look at the Integral Attack by the Higher-Order Differential Attack." Chinese Journal of Computers 35, no. 9 (2012): 1906. http://dx.doi.org/10.3724/sp.j.1016.2012.01906.
2
TSUNOO, Yukiyasu, Teruo SAITO, Hiroki NAKASHIMA, and Maki SHIGERI. "Higher Order Differential Attack on 6-Round MISTY1." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E92-A, no. 1 (2009): 3–10. http://dx.doi.org/10.1587/transfun.e92.a.3.
3
Sugio, Nobuyuki, Naoki Shibayama, and Yasutaka Igarashi. "Higher-order Differential Attack on Reduced-round SLIM." Journal of Information Processing 32 (2024): 352–57. http://dx.doi.org/10.2197/ipsjjip.32.352.
4
Yao, Jian Bo, and Tao Zhang. "Insert Random Time-Delay Defense High Order Side-Channel Attack." Advanced Engineering Forum 6-7 (September 2012): 169–74. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.169.
Анотація:
Side-channel attack is a non destructive physical attacks method. The current cryptographic algorithms are vulnerable to higher-order side-channel attack. To defense high order Side-channel attack, in this paper, a new countermeasure based on inserting random delay is proposed to secure AES against higher-order side-channel attack. By inserting a redundant instruction, it is expected to reduce the correlation between the leakage and the inside operations, and thus make the statistic analysis infeasible. The simulation shows the method is efficiency.
5
SUGIO, N., H. AONO, S. HONGO, and T. KANEKO. "A Study on Higher Order Differential Attack of KASUMI." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E90-A, no. 1 (January 1, 2007): 14–21. http://dx.doi.org/10.1093/ietfec/e90-a.1.14.
6
Cayrol, Claudette, and Marie-Christine Lagasquie-Schiex. "Logical Encoding of Argumentation Frameworks with Higher-order Attacks and Evidential Supports." International Journal on Artificial Intelligence Tools 29, no. 03n04 (June 2020): 2060003. http://dx.doi.org/10.1142/s0218213020600039.
Анотація:
We propose a logical encoding of argumentation frameworks with higher-order interactions (i.e. attacks/supports whose targets are arguments or other attacks/supports) with an evidential meaning for supports. Our purpose is to separate the logical expression of the meaning of an attack or an evidential support (simple or higher-order) from the logical expression of acceptability semantics. We consider semantics which specify the conditions under which the arguments (resp. the attacks/supports) are considered as accepted, directly on the extended framework, without translating the original framework into a Dung’s argumentation framework. We characterize the output of a given framework in logical terms (namely as particular models of a logical theory). Our proposal applies to the particular case of Dung’s frameworks, enabling to recover standard extensions.
7
Zhao, Pu, Pin-yu Chen, Siyue Wang, and Xue Lin. "Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6909–16. http://dx.doi.org/10.1609/aaai.v34i04.6173.
Анотація:
Despite the great achievements of the modern deep neural networks (DNNs), the vulnerability/robustness of state-of-the-art DNNs raises security concerns in many application domains requiring high reliability. Various adversarial attacks are proposed to sabotage the learning performance of DNN models. Among those, the black-box adversarial attack methods have received special attentions owing to their practicality and simplicity. Black-box attacks usually prefer less queries in order to maintain stealthy and low costs. However, most of the current black-box attack methods adopt the first-order gradient descent method, which may come with certain deficiencies such as relatively slow convergence and high sensitivity to hyper-parameter settings. In this paper, we propose a zeroth-order natural gradient descent (ZO-NGD) method to design the adversarial attacks, which incorporates the zeroth-order gradient estimation technique catering to the black-box attack scenario and the second-order natural gradient descent to achieve higher query efficiency. The empirical evaluations on image classification datasets demonstrate that ZO-NGD can obtain significantly lower model query complexities compared with state-of-the-art attack methods.
8
Chancellor, Dinah. "Higher-Order Thinking: A “Basic” Skill For Everyone." Arithmetic Teacher 38, no. 6 (February 1991): 48–50. http://dx.doi.org/10.5951/at.38.6.0048.
Анотація:
As I was walking down the hallway in one our our elementary schools the other day, one of the teachers rushed out of her room to catch me. “I love teaching this way!” she said with shining eyes. “The activities are exciting and challenging. The kids can't wait to do them. They are learning so much! I have really seen changes in how they attack problems. The only thing that bothers me is that I feel that all my students—not just the ones who have been identified as gifted— could benefit from these activities.
9
Kaedi, S., M. Doostari, and M. B. Ghaznavi-Ghoushchi. "NEMR: A Nonequidistant DPA Attack-Proof of Modular Reduction in a CRT Implementation of RSA." Journal of Circuits, Systems and Computers 27, no. 12 (June 22, 2018): 1850191. http://dx.doi.org/10.1142/s0218126618501918.
Анотація:
One of the most common algorithms in a digital signature is the RSA-CRT. Several side channel attacks have been presented on the RSA-CRT’s embedded design. Such attacks are divided into two categories: attack in the modular reduction step and attack in the recombination step. The former are plaintext attacks and based on the modular reduction on equidistant data attack, which is introduced in [B. den Boer, et al., “A DPA attack against the modular reduction within a CRT implementation of RSA,” in CHES 2002]. In these attacks, instead of using random plaintext, an equidistant series of input data is used. In a chosen and equidistant plaintext attack, the attacker needs a higher level of accessibility, and it is more difficult than a nonchosen plaintext attack. In this paper, we present a nonequidistant plaintext (but chosen plaintext) differential power analysis attack on the modular reduction in RSA-CRT, named NEMR (nonequidistant plaintext on modular reduction). We also present a new countermeasure on NEMR attack, which is resistant against equidistant and nonequidistant data attack on reduction step in RSA-CRT. In order to prove the idea, the NEMR attack is applied on the RSA-CRT 2048-bit implementation on SAKURA-G board, and the result is evaluated. Then, the presented countermeasure on NEMR attack is tested, and practical results demonstrate the validity of the proposed approach.
10
Narote, Prof Amit, Vamika Zutshi, Aditi Potdar, and Radhika Vichare. "D-Dos Attack Prediction Using Machine Learning Algorithms." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 2303–12. http://dx.doi.org/10.22214/ijraset.2022.41131.
Анотація:
Abstract: The risk of cyber-attack keeps on growing irrespective of development of new technologies for protection. One of the most frequent cyber-attacks is the DOS attack. A Denial-of-Service (DoS) attack is an attack which tries to shut down a machine or network, by flooding the target with unwanted traffic or triggers a crash by sending it some information, which makes it challenging for the users to access their network. A higher version of DoS attacks is the DDoS attacks that have recently become quite severe in security companies. Many organizations have begun facing these issues. Such attacks are very well coordinated that disrupts the normal functioning of the networking system from large firms to small scale business. Hence, detecting such attacks has become a tedious task. However, such a classification problem can be resolved using machine learning. Also, the same problem can be addressed using the concepts of cloud computing in order to detect and identify the computational effort carried out by the attacks. A DoS is generally considered to be an organized attack by hackers that is implemented from a single source of origin and targeted towards the victim’s end. In order to attack these systems such attackers impersonate themselves as legit users and gain access from the users by asking them their personal credential and details. As compared to this, a DDoS attack is limited to a single source of origin and takes place on distributed computers all together. Hence the primary aim of this thesis is to identify such attacks caused by hackers and detect them using machine learning algorithms. Keywords: Denial-of-Service (DoS), Distributed Denial-of-Service (DDoS), Machine Learning, Bots, Botnets, flooding attacks
11
Ramachandra, H. V., Pundalik Chavan, S. Supreeth, H. C. Ramaprasad, K. Chatrapathy, G. Balaraju, S. Rohith, and H. S. Mohan. "Secured Wireless Network Based on a Novel Dual Integrated Neural Network Architecture." Journal of Electrical and Computer Engineering 2023 (September 28, 2023): 1–11. http://dx.doi.org/10.1155/2023/9390660.
Анотація:
The development of the fifth generation (5G) and sixth generation (6G) wireless networks has gained wide spread importance in all aspects of life through the network due to their significantly higher speeds, extraordinarily low latency, and ubiquitous availability. Owing to the importance of their users, components, and services to our everyday lives, the network must secure all of these. With such a wide range of devices and service types being present in the 5G ecosystem, security issues are now much more prevalent. Security solutions, are not implemented, must already be envisioned in order to deal with a range of attacks on numerous services, cutting-edge technology, and more user information available over the network. This research proposes the dual integrated neural network (DINN) for secure data transmission in wireless networks. DINN comprises two neural networks based on sparse and dense dimensions. DINN is designed for any presence of deep learning-based attack in a physical security layer. DINN is evaluated considering the various machine learning attack such as basic_iterative_method attack, momentum_iterative_method attack, post_gradient_descent attack, and C&W attack; comparison is carried out on existing and DINN, considering attack success rate and MSE. Performance analysis suggests that DINN holds a higher level of security against the above attacks.
12
Wei, Zhipeng, Jingjing Chen, Micah Goldblum, Zuxuan Wu, Tom Goldstein, and Yu-Gang Jiang. "Towards Transferable Adversarial Attacks on Vision Transformers." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (June 28, 2022): 2668–76. http://dx.doi.org/10.1609/aaai.v36i3.20169.
Анотація:
Vision transformers (ViTs) have demonstrated impressive performance on a series of computer vision tasks, yet they still suffer from adversarial examples. In this paper, we posit that adversarial attacks on transformers should be specially tailored for their architecture, jointly considering both patches and self-attention, in order to achieve high transferability. More specifically, we introduce a dual attack framework, which contains a Pay No Attention (PNA) attack and a PatchOut attack, to improve the transferability of adversarial samples across different ViTs. We show that skipping the gradients of attention during backpropagation can generate adversarial examples with high transferability. In addition, adversarial perturbations generated by optimizing randomly sampled subsets of patches at each iteration achieve higher attack success rates than attacks using all patches. We evaluate the transferability of attacks on state-of-the-art ViTs, CNNs and robustly trained CNNs. The results of these experiments demonstrate that the proposed dual attack can greatly boost transferability between ViTs and from ViTs to CNNs. In addition, the proposed method can easily be combined with existing transfer methods to boost performance.
13
Thanh, Bui The, and Ngo Kien Trung. "Using the Model Reduction Techniques to Find the Low-Order Controller of the Aircraft's Angle of Attack Control System." Journal Européen des Systèmes Automatisés 55, no. 5 (November 30, 2022): 649–55. http://dx.doi.org/10.18280/jesa.550510.
Анотація:
The problem of controlling the angle of attack of the aircraft is one of the difficult and complex problems due to the problems of nonlinear kinematics, variable parameters and uncertainty model. The design of the angle of attack control according to the robustness control algorithm often leads to a higher order robustness controller. Using a higher-order controller has many disadvantages, so it is necessary to have solutions to reduce the order of the controller. This paper presents the idea of designing a low-order controller for the aircraft's angle of attack control system using the order reduction algorithm. In order to meet the requirements of performance and stability when parameters change, the optimal controller of the aircraft's angle of attack is usually of high order. The paper has used order reduction algorithms to reduce the order of high-order angle of attack controller, the results show that: 4th-order controller or 1st-order controller can be used instead of high order controller. Using a low-order controller to control the aircraft's angle of attack shows that the quality of the control system is comparable to that of a high-order controller.
14
Sălăgean, Ana, R. Winter, Matei Mandache-Sălăgean, and Raphael C. W. Phan. "Higher order differentiation over finite fields with applications to generalising the cube attack." Designs, Codes and Cryptography 84, no. 3 (September 21, 2016): 425–49. http://dx.doi.org/10.1007/s10623-016-0277-5.
15
Padmaja, K., and K. Padmaja. "Radial Basis Kernel Regressive Feature Extraction and Robert Ensembled Brown Boost Classifier for Attack Detection in Cloud Environment." Webology 18, no. 2 (December 23, 2021): 41–59. http://dx.doi.org/10.14704/web/v18i2/web18306.
Анотація:
Cloud computing shares the resource in information technology field. The existing technique is failed to provide better results for identifying unknown attacks with higher accuracy and lesser time consumption. In order to address these problems, Radial Basis Kernel Regressive Feature Extracted Brown Boost Classification (RBKRFEBBC) method is introduced for performing the attack detection in cloud computing. The main objective of RBKRFEBBC method is to improve the attack detection performance with higher accuracy and minimal time consumption. Dichotomous radial basis kernelized regressive function is used in RBKRFEBBC method to extract the relevant features through determining the correlation between the output and one or more input variables (i.e., features of patient transaction data). After extracting relevant features, GRNBBC algorithm is used in RBKRFEBBC method to improve the secured data communication performance through classifying the patient data transaction as attack presence or attack absence. By this way, attack detection is carried out in accurate manner. Experimental evaluation is carried out by NSL-KDD dataset using different metrics like attack detection accuracy, attack detection time and error rate. The evaluation result shows RBKRFEBBC method improves the accuracy and minimizes the time consumption as well as error rate than existing works.
16
Yang, Zhifei, Wenmin Li, Fei Gao, and Qiaoyan Wen. "FAPA: Transferable Adversarial Attacks Based on Foreground Attention." Security and Communication Networks 2022 (October 29, 2022): 1–8. http://dx.doi.org/10.1155/2022/4447307.
Анотація:
Deep learning models are vulnerable to attacks by adversarial examples. However, current studies are mainly limited to generating adversarial examples for specific models, and the migration of adversarial examples between different models is rarely studied. At the same time, in only studies, it is not considered that adding disturbance to the position of the image can improve the migration of adversarial examples better. As the main part of the picture, the model should give more weight to the foreground information in the recognition. Will adding more perturbations to the foreground information of the image result in a higher transfer attack rate? This paper focuses on the above problems, and proposes the FAPA algorithm, which first selects the foreground information of the image through the DINO framework, then uses the foreground information to generate M, and then uses PNA to generate the perturbation required for the whole picture. In order to show that our method attaches importance to the foreground information, we give a greater weight to the perturbation corresponding to the foreground information, and a smaller weight to the rest of the image. Finally, we optimize the generated perturbation through the gradient generated by the dual attack framework. In order to demonstrate the effectiveness of our method, we have conducted relevant comparative experiments. During the experiment, we used the three white-box ViTs models to attack the six black-box ViTs models and the three black-box CNNs models. In the transferable attack of ViTs models, the average attack success rate of our algorithm reaches 64.19%, which is much higher than 21.12% of the FGSM algorithm. In the transferable attack of CNN models, the average attack success rate of our algorithm reaches 48.07%, which is also higher than 18.65% of the FGSM algorithm. By integrating ViTs and CNNs models, the attack success rate of transfer of our algorithm reaches 56.13%, which is higher than 1.18% of the dual attack framework we refer to.
17
Le, Duc, Minh Dao, and Quyen Nguyen. "Comparison of machine learning algorithms for DDoS attack detection in SDN." Information and Control Systems, no. 3 (June 15, 2020): 59–70. http://dx.doi.org/10.31799/1684-8853-2020-3-59-70.
Анотація:
Introduction: Distributed denial-of-service (DDoS) has become a common attack type in cyber security. Apart from the conventional DDoS attacks, software-defined networks also face some other typical DDoS attacks, such as flow-table attack or controller attack. One of the most recent solutions to detect a DDoS attack is using machine learning algorithms to classify the traffic. Purpose: Analysis of applying machine learning algorithms in order to prevent DDoS attacks in software-defined network. Results: A comparison of six algorithms (random forest, decision tree, naive Bayes, support vector machine, multilayer perceptron, k-nearest neighbors) with accuracy and process time as the criteria has shown that a decision tree and naïve Bayes are the most suitable algorithms for DDoS attack detection. As compared to other algorithms, they have higher accuracy, faster processing time and lower resource consumption. The main features that identify malicious traffic compared to normal one are the number of bytes in a flow, time flow, Ethernet source address, and Ethernet destination address. A flow-table attack can be detected easier than a bandwidth attack, as all the six algorithms can predict this type with a high accuracy. Practical relevance: Important features which play a supporting role in correct data classification facilitate the development of a DDoS protection system with a smaller dataset, focusing only on the necessary data. The algorithms more suitable for machine learning can help us to detect DDoS attacks in software-defined networks more accurately.
18
Fargetti, Simone, Claudia Goldenstein-Schainberg, Andressa Silva Abreu, and Ricardo Fuller. "Refractory Gout Attack." Case Reports in Medicine 2012 (2012): 1–4. http://dx.doi.org/10.1155/2012/657694.
Анотація:
Refractory gout attack is an uncommon problem, since gout flares are usually self-limited. This clinical condition is characterized by serum uric acid higher than 6 mg/Dl or continuous manifestations of recurrent flares, chronic arthritis, and increased tophi. We report in this paper a 69-year-old man with a polyarticular and protracted gout attack, despite usual treatment and low urate sera levels. In order to manage this problem, we reviewed gout pathophysiology and developed a therapeutic solution based on benzbromarone pharmacokinetics. We also review herein new options for gout treatment that could be used in similar cases.
19
Liu, Fengchun, Sen Zhang, Weining Ma, and Jingguo Qu. "Research on Attack Detection of Cyber Physical Systems Based on Improved Support Vector Machine." Mathematics 10, no. 15 (August 1, 2022): 2713. http://dx.doi.org/10.3390/math10152713.
Анотація:
Cyber physical systems (CPS), in the event of a cyber attack, can have a serious impact on the operating physical equipment. In order to improve the attack detection capability of CPS, an support vector machine (SVM) attacks detection model based on particle swarm optimization (PSO) is proposed. First, the box plot anomaly detection method is used to detect the characteristic variables, and the characteristic variables with abnormal distribution are discretized. Secondly, the number of attack samples was increased by the SMOTE method to solve the problem of data imbalance, and the linear combination of characteristic variables was performed on the high-dimensional CPS network traffic data using principal component analysis (PCA). Then, the penalty coefficient and the hyperparameter of the kernel function in the SVM model are optimized by the PSO algorithm. Finally, Experiments on attack detection of CPS network traffic data show that the proposed model can detect different types of attack data and has higher detection accuracy compared with general detection models.
20
Yan, Ruoyu. "Combining Renyi Entropy and EWMA to Detect Common Attacks in Network." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 10 (November 23, 2016): 1650021. http://dx.doi.org/10.1142/s021800141650021x.
Анотація:
How to timely and precisely identify attack behaviors in network without dealing with a large number of traffic features and historical data, such as training data, is an important research work in the field of network security. In this paper, firstly, the differences between Renyi entropy and Shannon entropy are analyzed and compared. In order to capture network traffic changes exactly, Renyi entropy instead of Shannon entropy is proposed to measure selected traffic features. Then EWMA control chart theory is used to check Renyi entropy time series for detecting and screening anomalies. And three kinds of network attacks are also analyzed and characterized by behavior feature vector for attack identification. Finally a feature similarity-based method is used to identify attacks. The experimental results of real traffic traces show that the proposed method has good capability to detect and identify these attacks with less computation cost. To evaluate attack identification method conveniently, an approach is proposed to generate simulated attack traffics. Compared with Shannon entropy-based method, the experiments on simulation traffics show that Renyi entropy-based method has much higher overall accuracy, average precision and average true positive rate. Further comparison indicates the proposed method has more powerful performance to detect attacks than PCA-based method.
21
Baigang, Mi, and Yu Jingyi. "An Improved Nonlinear Aerodynamic Derivative Model of Aircraft at High Angles of Attack." International Journal of Aerospace Engineering 2021 (September 8, 2021): 1–12. http://dx.doi.org/10.1155/2021/5815167.
Анотація:
The classical aerodynamic derivative model is widely used in flight dynamics, but its application is extremely limited in cases with complicated nonlinear flows, especially at high angles of attack. A modified nonlinear aerodynamic derivative model for predicting unsteady aerodynamic forces and moments at a high angle of attack is developed in this study. We first extend the higher-order terms to describe the nonlinear characteristics and then introduce three more influence parameters, the initial angle of attack, the reduced frequency, and the oscillation amplitude, to correct the constant aerodynamic derivative terms that have higher-order polynomials for these values. The improved nonlinear aerodynamic derivative model was validated by using the NACA 0015 airfoil and the F-18 model. The results show that the improved model has a higher prediction ability at high angles of attack and has the ability to predict the aerodynamic characteristics of other unknown states based on known unsteady aerodynamic data, such as the initial angle of attack, reduced frequency, and oscillation amplitude.
22
OMORI, ITSUKI. "A problem of atrial attack-receiving ability evaluation by higher order right atrium electric potential." Japanese Journal of Electrocardiology 10, no. 6 (1990): 833–42. http://dx.doi.org/10.5105/jse.10.833.
23
Sárkány, Zoltán, Kinga Sárkány, and A. Horváth. "Investigating the Possibility to Individualize Asthma Attack Therapy Based on Attack Severity and Patient Characteristics." Acta Medica Marisiensis 62, no. 1 (March 1, 2016): 73–77. http://dx.doi.org/10.1515/amma-2015-0120.
Анотація:
AbstractIntroduction: The objective of this study was to investigate with the help of a computerized simulation model whether the treatment of an acute asthma attack can be individualized based on the severity of the attack and the characteristics of the patient. Material and Method: A stochastic lung model was used to simulate the deposition of 1 nm - 10 μm particles during a mild and a moderate asthma attack. Breathing parameters were varied to maximize deposition, and simulation results were compared with those obtained in the case of a severe asthma attack. In order to investigate the effect of height on the deposition of inhaled particles, another series of simulations was carried out with identical breathing parameters, comparing patient heights of 155 cm, 175 cm and 195 cm. Results: The optimization process yielded an increase in the maximum deposition values of around 6-7% for each type of investigated asthma attack, and the difference between attacks of different degree of severity was around 5% for both the initial and the optimized values, a higher degree of obstruction increasing the amount of deposited particles. Conclusions: Our results suggest that the individualization of asthma attack treatment cannot be based on particles of different size, as the highest deposited fraction in all three types of attacks can be obtained using 0.01 μm particles. The use of a specific set of breathing parameters yields a difference between a mild and a moderate, as well as a moderate and a severe asthma attack of around 5%.
24
Singh, Anurag, and Dr Subhadra Shaw. "Using Machine Learning Algorithms to Alleviate the Shilling Attack in a Recommendation System." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 1879–83. http://dx.doi.org/10.22214/ijraset.2023.51951.
Анотація:
Abstract: Every e-commerce site must have a referral system. Shilling attacks, One of the biggest issues with recommendation systems is those that involve the creation of fake profiles in the system and biased ratings of things. They reduce the accuracy and improve the performance of the recommender system when making suggestions to users. The goal of attackers is to change the order of materials or objects that match their interests. Shilling attacks threaten the reliability of RS. Therefore, to maintain their validity and fairness, recommender systems must be able to detect shilling attacks. So far, suitable algorithms and methods have been presented for the detection of shilling attacks. Some of these approaches, though, either use low-order interactions or higher-order interactions, or they examine the rating matrix from a single point of view. This study aimed to propose a mechanism using users' rating matrix, rating time, and social network analysis output of users' profiles by Gaussian-Rough neural network to simultaneously use low-order and high-order interactions to detect shilling attacks. Finally, several experiments were conducted with three models: CNN, DNN, and RNN compared with the Proposed Model. The results indicated that the proposed method is more effective than the comparison methods regarding attack detection and overall detection, which proves the effectiveness of the proposed model.
25
Thaper, Rohit, and Amandeep Verma. "Enhanced-Adaptive Pattern Attack Recognition Technique (E-APART) Against EDoS Attacks in Cloud Computing." Journal of Cases on Information Technology 17, no. 3 (July 2015): 41–55. http://dx.doi.org/10.4018/jcit.2015070105.
Анотація:
Cloud Computing is most widely used in current technology. It provides a higher availability of resources to greater number of end users. In the cloud era, security has develop a reformed source of worries. Distributed Denial of Service (DDoS) and Economical Denial of Sustainability (EDoS) are attacks that can affect the ‘pay-per-use' model. This model automatically scales the resources according to the demand of consumers. The functionality of this model is to mitigate the EDoS attack by some tactical attacker/s, group of attackers or zombie machine network (BOTNET) to minimize the availability of the target resources, which directly or indirectly reduces the profits and increase the cost for the cloud operators. This paper presents a model called Enhanced-APART which is step further of the authors' previous model (APART) that can be used to mitigate the EDoS attack from the cloud platform and shows the nature of the attack. Enhanced-APART model offers pre-shared security mechanism to ensure the access of legitimate users on the cloud services. It also performs pattern analysis in order to detect the EDoS caused by BOTNET mechanism and includes time-based and key-sharing post-setup authentication scheme to prevent the replication or replay attacks and thus results in mitigation of EDoS attack.
26
Ueno, Rei, Naofumi Homma, Akiko Inoue, and Kazuhiko Minematsu. "Fallen Sanctuary: A Higher-Order and Leakage-Resilient Rekeying Scheme." IACR Transactions on Cryptographic Hardware and Embedded Systems 2024, no. 1 (December 4, 2023): 264–308. http://dx.doi.org/10.46586/tches.v2024.i1.264-308.
Анотація:
This paper presents a provably secure, higher-order, and leakage-resilient (LR) rekeying scheme named LR Rekeying with Random oracle Repetition (LR4), along with a quantitative security evaluation methodology. Many existing LR primitives are based on a concept of leveled implementation, which still essentially require a leak-free sanctuary (i.e., differential power analysis (DPA)-resistant component(s)) for some parts. In addition, although several LR pseudorandom functions (PRFs) based on only bounded DPA-resistant components have been developed, their validity and effectiveness for rekeying usage still need to be determined. In contrast, LR4 is formally proven under a leakage model that captures the practical goal of side-channel attack (SCA) protection (e.g., masking with a practical order) and assumes no unbounded DPA-resistant sanctuary. This proof suggests that LR4 resists exponential invocations (up to the birthday bound of key size) without using any unbounded leak-free component, which is the first of its kind. Moreover, we present a quantitative SCA success rate evaluation methodology for LR4 that combines the bounded leakage models for LR cryptography and a state-of-the-art information-theoretical SCA evaluation method. We validate its soundness and effectiveness as a DPA countermeasure through a numerical evaluation; that is, the number of secure calls of a symmetric primitive increases exponentially by increasing a security parameter under practical conditions.
27
Dong, Gaogao, Nan Wang, Fan Wang, Ting Qing, Yangyang Liu, and André L. M. Vilela. "Network resilience of non-hub nodes failure under memory and non-memory based attacks with limited information." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 6 (June 2022): 063110. http://dx.doi.org/10.1063/5.0092284.
Анотація:
Previous studies on network robustness mainly concentrated on hub node failures with fully known network structure information. However, hub nodes are often well protected and not accessible to damage or malfunction in a real-world networked system. In addition, one can only gain insight into limited network connectivity knowledge due to large-scale properties and dynamic changes of the network itself. In particular, two different aggression patterns are present in a network attack: memory based attack, in which failed nodes are not attacked again, or non-memory based attack; that is, nodes can be repeatedly attacked. Inspired by these motivations, we propose an attack pattern with and without memory based on randomly choosing [Formula: see text] non-hub nodes with known connectivity information. We use a network system with the Poisson and power-law degree distribution to study the network robustness after applying two failure strategies of non-hub nodes. Additionally, the critical threshold [Formula: see text] and the size of the giant component [Formula: see text] are determined for a network configuration model with an arbitrary degree distribution. The results indicate that the system undergoes a continuous second-order phase transition subject to the above attack strategies. We find that [Formula: see text] gradually tends to be stable after increasing rapidly with [Formula: see text]. Moreover, the failure of non-hub nodes with a higher degree is more destructive to the network system and makes it more vulnerable. Furthermore, from comparing the attack strategies with and without memory, the results highlight that the system shows better robustness under a non-memory based attack relative to memory based attacks for [Formula: see text]. Attacks with memory can block the system’s connectivity more efficiently, which has potential applications in real-world systems. Our model sheds light on network resilience under memory and non-memory based attacks with limited information attacks and provides valuable insights into designing robust real-world systems.
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Lu, Jiqiang, Yongzhuang Wei, Jongsung Kim, and Enes Pasalic. "The higher-order meet-in-the-middle attack and its application to the Camellia block cipher." Theoretical Computer Science 527 (March 2014): 102–22. http://dx.doi.org/10.1016/j.tcs.2014.01.031.
29
Al-Shabi, Mohammed. "Performance Ameliorations of AODV by Black Hole Attack Detection Utilizing IDSAODV as Well as Reverse AODV." International Journal of Communication Networks and Information Security (IJCNIS) 14, no. 2 (August 31, 2022): 99–110. http://dx.doi.org/10.17762/ijcnis.v14i2.5483.
Анотація:
The so-called Black Hole Attack is among the most perilous and widespread security attacks in MANET nets, researchers have been tasked with developing strategies to detect it. Two of these methods are the Intrusion Detection System AODV (IDSAODV) as well as the Extended AODV. The present paper attempts to investigate the impact of a Black Hole Attack on the functionality of the network in the existence of single or more attackers. It also evaluates the Extended AODV and IDSAODV in a net in order to see how effectively they could detect and mitigate the attack. For the aim of evaluating its performance, the researchers utilized Throughput, Normalized Routing Load (NRL), and Packet Delivery Ratio (PDR). The comprehensive simulation results show that the IDSAODV application decreased the effect of the attacks. However, it raised the rate of packet delivery to sixty eight percent at the identical time. Reverse AODV, on the other hand, provided superior outcomes, with a PDR of 100%, but also resulted in an exceedingly higher NRL than the IDSAODV. Likewise, the simulation findings demonstrated that the attacking node's position tormented the IDSAODV's functionality.
30
Yildirim, D., R. C. Kardaş, B. Ozkiziltas, I. Vasi, M. A. Ozturk, S. Haznedaroglu, B. Goker, and A. Tufan. "AB1272 FACTORS AFFECTING PATIENT-ACCEPTABLE SYMPTOM STATES IN FAMILIAL MEDITERRANEAN FEVER." Annals of the Rheumatic Diseases 81, Suppl 1 (May 23, 2022): 1744.1–1744. http://dx.doi.org/10.1136/annrheumdis-2022-eular.386.
Анотація:
BackgroundFamilial Mediterranean fever (FMF) is an autoinflammatory disease characterized by recurrent attacks of fever, serositis, and musculoskeletal symptoms (1, 2). Arthritis is the most common musculoskeletal symptom of attacks and also included in diagnostic criteria of FMF (3). If it is specifically queried, myalgia may be detected in up to 20-25% of the patients with FMF.(4,5).ObjectivesIn our study, we aim to assess the localization of attack-related myalgia and associated parameters in patients with FMF.MethodsA total of 349 consecutive patients followed by FMF in our clinic were enrolled in the study and asked for attack-induced myalgia and if present, localization of muscle groups on the mannequin body parts diagram.Attack frequency, duration, and disease activity were evaluated with the AutoInflammatory Diseases Activity Index (AIDAI) scoring system (6). Patients were also asked for work/study day loss during attacks and patient acceptable symptom state (PASS) status (7).Results126 patients showed attack myalgia (36%); attack duration, frequency, severity were significantly higher in patients with attack-myalgia (p<0,005). Most common muscle groups were calves, lower back, and latissimus dorsi muscles in order. Myalgia was most commonly accompanied by arthritis (p<0,002). Patients with myalgia have a higher frequency of colchicine resistance and work/study day loss due to attacks.ConclusionOur results conclude that myalgia is an important domain of attacks and causes absenteeism and uncontrolled disease activity. Treatment of myalgia attacks may provide controlled disease activity, and prevent absenteeism from work/school.References[1]El-Shanti H, Majeed HA, El-Khateeb M. Familial mediterranean fever in Arabs.Lancet. 2006;367(9515):1016–24.[2]Majeed HA, Al-Qudah AK, Qubain H, Shahin HM. The clinical patterns of myalgia in children with familial Mediterranean fever. Semin Arthritis Rheum. 2000;30(2):138–43.[3]Gattorno M, Hofer M, Federici S, Vanoni F et al. Eurofever Registry and the Paediatric Rheumatology International Trials Organisation (PRINTO). Classification criteria for autoinflammatory recurrent fevers. Ann Rheum Dis. 2019 Aug;78(8):1025-1032. doi: 10.1136/annrheumdis-2019-215048.[4]Zemer D. Muscle pains in familial Mediterranean fever. Harefuah 1984; 106: 232-233.[5]Majeed HA. Differential diagnosis of fever of unknown origin in children. Curr Opin Rheumatol 2000; 12: 439-444.[6]Piram M, Frenkel J, Gattorno M et al. EUROFEVER and EUROTRAPS networks. A preliminary score for the assessment of disease activity in hereditary recurrent fevers: results from the AIDAI (Auto-Inflammatory Diseases Activity Index) Consensus Conference. Ann Rheum Dis. 2011 Feb;70(2):309-14. doi: 10.1136/ard.2010.132613.[7]Salaffi F, Carotti M, Gutierrez M, Di Carlo M, De Angelis R. (2015) Patient Acceptable Symptom State in Self-Report Questionnaires and Composite Clinical Disease Index for Assessing Rheumatoid Arthritis Activity: Identification of Cut-Off Points for Routine Care. Biomed Res Int. 2015:930756. doi: 10.1155/2015/930756.Table 1.Comparison of clinical and laboratory parameters between patients with /without myalgia attacksPatients with myalgia attackPatients without myalgia attackp valueAge (years)36,33 ±10, 6837,9±11, 48>0,05Sex (female/male)78/43138/87>0,05Follow-up time (years)16,117,6>0,05Dominant attack(number)Peritonitis4255>0,05Arthritis11390,012Pleuritis1310>0,05Only fever47>0,05AIDAI score (mean, 0-175)127,4080,68<0,05VAS score for pain (median score, during attack. 0-10)85<0,05Colchicine resistance (number ofpatients)69250,003Colchicine-resistant29840,002Colchicine-sensitivePASS status (number)Need additional treatment4160,016Satisfied from treatment34740,010Work/study day loss (number)4860,003AcknowledgementsAll study population signed informed consent for both participation and publication. Local Ethical Committee of the university approved the study.Disclosure of InterestsNone declared
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JIN, Xiaying, Yang LI, and Quan PAN. "DE-JSMA: a sparse adversarial attack algorithm for SAR-ATR models." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 41, no. 6 (December 2023): 1170–78. http://dx.doi.org/10.1051/jnwpu/20234161170.
Анотація:
The vulnerability of DNN makes the SAR-ATR system that uses an intelligent algorithm for recognition also somewhat vulnerable. In order to verify the vulnerability, this paper proposes DE-JSMA, a novel sparse adversarial attack algorithm based on a salient map's adversarial attack algorithm and differential evolution algorithm, with the synthetic aperture radar (SAR) image feature sparsity considered. After accurately screening out the salient features that have a great impact on the model inference results, the DE-JSMA algorithm optimizes the appropriate feature values for the salient features. In order to verify its effectiveness more comprehensively, a new metric that combines the attack success rate with the average confidence interval of adversarial examples is proposed. The experimental results show that DE-JSMA extends JSMA, which can be used only for targeted attack scenario, to untargeted attack scenario without increasing too much time consumption but ensuring a high attack success rate, thus achieving sparse adversarial attack with higher reliability and better sparsity in both attack scenarios. The pixel perturbations of only 0.31% and 0.85% can achieve the untargeted and targeted attack success rates up to 100% and 78.79% respectively.
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Lombardero, M. J., M. P. Ayres, F. E. Krivak-Tetley, and K. N. E. Fitza. "Population biology of the European woodwasp,Sirex noctilio, in Galicia, Spain." Bulletin of Entomological Research 106, no. 5 (February 24, 2016): 569–80. http://dx.doi.org/10.1017/s0007485316000043.
Анотація:
AbstractSirex noctilioFabricius (Hymenoptera, Siricidae) is rare and rarely studied where it is native in Eurasia, but is a widespread pest of pines in the Southern Hemisphere. Here we report on the abundance, basic biology, host use patterns and natural enemies of nativeS. noctilioin Galicia, Spain. Most trees attacked byS. noctiliofailed to produce any adult progeny: >90% of emergences came from <20% of the attacked trees. The highest reproduction was inPinus pinaster, followed byPinus sylvestrisandPinus radiata.The proportions ofS. noctiliorequiring 1, 2 or 3 years for development were 0.72: 0.24: 0.04. Delayed development could be an adaptation to avoid parasitic nematodes, which sterilized 41.5% adults with one year generation time but only 19% of adults with 2 years generation time. Hymenoptera parasitoids accounted for 20% mortality. Sex ratios were male biased at 1: 2.9. Body size and fecundity were highly variable and lower than previously reported from the Southern Hemisphere. On attacked trees, there were 5–20 attacks per standard log (18 dm2), with usually 1–3 drills per attack. Attack densities and drills per attack were higher in trees that subsequently died. The production ofS. noctilioper log was positively related to total attacks, and negatively related to: (1) attack density, (2) incidence of blue stain fromOphiostomafungi and (3) frequency of lesions in plant tissue around points of attack. A preliminary life table for S.noctilioin Galicia estimated effects on potential population growth rate from (in decreasing order of importance) host suitability, unequal sex ratio, parasitic nematodes and Hymenoptera parasitoids.
33
Liu, Hongjuan, Zhiliang Zhu, Hai Yu, and Qian Zhu. "Modified Projective Synchronization between Different Fractional-Order Systems Based on Open-Plus-Closed-Loop Control and Its Application in Image Encryption." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/567898.
Анотація:
A new general and systematic coupling scheme is developed to achieve the modified projective synchronization (MPS) of different fractional-order systems under parameter mismatch via the Open-Plus-Closed-Loop (OPCL) control. Based on the stability theorem of linear fractional-order systems, some sufficient conditions for MPS are proposed. Two groups of numerical simulations on the incommensurate fraction-order system and commensurate fraction-order system are presented to justify the theoretical analysis. Due to the unpredictability of the scale factors and the use of fractional-order systems, the chaotic data from the MPS is selected to encrypt a plain image to obtain higher security. Simulation results show that our method is efficient with a large key space, high sensitivity to encryption keys, resistance to attack of differential attacks, and statistical analysis.
34
Peng, Hao, Cheng Qian, Dandan Zhao, Ming Zhong, Jianmin Han, and Wei Wang. "Targeting attack hypergraph networks." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 7 (July 2022): 073121. http://dx.doi.org/10.1063/5.0090626.
Анотація:
In modern systems, from brain neural networks to social group networks, pairwise interactions are not sufficient to express higher-order relationships. The smallest unit of their internal function is not composed of a single functional node but results from multiple functional nodes acting together. Therefore, researchers adopt the hypergraph to describe complex systems. The targeted attack on random hypergraph networks is still a problem worthy of study. This work puts forward a theoretical framework to analyze the robustness of random hypergraph networks under the background of a targeted attack on nodes with high or low hyperdegrees. We discovered the process of cascading failures and the giant connected cluster (GCC) of the hypergraph network under targeted attack by associating the simple mapping of the factor graph with the hypergraph and using percolation theory and generating function. On random hypergraph networks, we do Monte-Carlo simulations and find that the theoretical findings match the simulation results. Similarly, targeted attacks are more effective than random failures in disintegrating random hypergraph networks. The threshold of the hypergraph network grows as the probability of high hyperdegree nodes being deleted increases, indicating that the network’s resilience becomes more fragile. When considering real-world scenarios, our conclusions are validated by real-world hypergraph networks. These findings will help us understand the impact of the hypergraph’s underlying structure on network resilience.
35
Yildirim, D., E. Tahta, R. C. Kardaş, B. Özkiziltaş, I. Vasi, H. Küçük, M. A. Ozturk, and A. Tufan. "POS1364 ATTACKS OF MYALGIA IN PATIENTS WITH FAMILIAL MEDITERRANEAN FEVER: OTHER THAN CALF PAIN." Annals of the Rheumatic Diseases 81, Suppl 1 (May 23, 2022): 1021.1–1021. http://dx.doi.org/10.1136/annrheumdis-2022-eular.4246.
Анотація:
BackgroundFamilial Mediterranean fever (FMF) is an autoinflammatory disease characterized by recurrent attacks of fever, serositis, and musculoskeletal symptoms [1, 2]. Arthritis is the most common musculoskeletal symptom of attacks and also included in diagnostic criteria of FMF [3]. If it is specifically queried, myalgia may be detected in up to 20-25% of the patients with FMF. [4, 5].ObjectivesIn our study, we aim to assess the localization of attack-related myalgia and associated parameters in patients with FMF.MethodsA total of 349 consecutive patients followed by FMF in our clinic were enrolled in the study and asked for attack-induced myalgia and if present, localization of muscle groups on the mannequin body parts diagram.Attack frequency, duration, and disease activity were evaluated with the AutoInflammatory Diseases Activity Index (AIDAI) scoring system [6]. Patients were also asked for work/study day loss during attacks and patient acceptable symptom state (PASS) status [7].Results126 patients showed attack myalgia (36%); attack duration, frequency, severity were significantly higher in patients with attack-myalgia (p<0,005). Most common muscle groups were calves, lower back, and latissimus dorsi muscles in order. Myalgia was most commonly accompanied by arthritis (p<0,002). Patients with myalgia have a higher frequency of colchicine resistance and work/study day loss due to attacks.ConclusionOur results conclude that myalgia is an important domain of attacks and causes absenteeism and uncontrolled disease activity.References[1]El-Shanti H, Majeed HA, El-Khateeb M. Familial mediterranean fever in Arabs.Lancet. 2006;367(9515):1016–24.[2]Majeed HA, Al-Qudah AK, Qubain H, Shahin HM. The clinical patterns of myalgia in children with familial Mediterranean fever. Semin Arthritis Rheum. 2000;30(2):138–43.[3]Gattorno M, Hofer M, Federici S, Vanoni F et al. Eurofever Registry and the Paediatric Rheumatology International Trials Organisation (PRINTO). Classification criteria for autoinflammatory recurrent fevers. Ann Rheum Dis. 2019 Aug;78(8):1025-1032. doi: 10.1136/annrheumdis-2019-215048.[4]Zemer D. Muscle pains in familial Mediterranean fever. Harefuah 1984; 106: 232-233.[5]Majeed HA. Differential diagnosis of fever of unknown origin in children. Curr Opin Rheumatol 2000; 12: 439-444.[6]Piram M, Frenkel J, Gattorno M et al. EUROFEVER and EUROTRAPS networks. A preliminary score for the assessment of disease activity in hereditary recurrent fevers: results from the AIDAI (Auto-Inflammatory Diseases Activity Index) Consensus Conference. Ann Rheum Dis. 2011 Feb;70(2):309-14. doi: 10.1136/ard.2010.132613.[7]Salaffi F, Carotti M, Gutierrez M, Di Carlo M, De Angelis R. (2015) Patient Acceptable Symptom State in Self-Report Questionnaires and Composite Clinical Disease Index for Assessing Rheumatoid Arthritis Activity: Identification of Cut-Off Points for Routine Care. Biomed Res Int. 2015:930756. doi: 10.1155/2015/930756.Table 1.Comparison of clinical and laboratory parameters between patients with /without myalgia attacksPatients with myalgia attackPatients without myalgia attackp valueAge (years)36,33 ±10, 6837,9±11, 48>0,05Sex (female/male)78/43138/87>0,05Follow-up time (years)16,117,6>0,05Dominant attack(number)Peritonitis4255>0,05Arthritis11390,012Pleuritis1310>0,05Only fever47>0,05AIDAI score (mean, 0-175)127,4080,68<0,05VAS score for pain (median score, during attack. 0-10)85<0,05Colchicine resistance (number of patients)69250,003Colchicine-resistantColchicine-sensitive29840,002PASS status (number)4160,016Need additional treatment Satisfied from treatment34740,010Work/study day loss (number)4860,003AcknowledgementsNo financial funding is received for this report. Informed consents for participating and publishing were obtained from all participantsDisclosure of InterestsNone declared
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Li, Huizhong, Yongbin Zhou, Jingdian Ming, Guang Yang, and Chengbin Jin. "The Notion of Transparency Order, Revisited." Computer Journal 63, no. 12 (July 3, 2020): 1915–38. http://dx.doi.org/10.1093/comjnl/bxaa069.
Анотація:
Abstract We revisit the definition of transparency order (TO) and that of modified transparency order (MTO) as well, which were proposed to measure the resistance of substitution boxes (S-boxes) against differential power analysis (DPA). We spot a definitional flaw in original TO, which is proved to significantly affect the soundness of TO. Regretfully, MTO overlooks this flaw, yet it happens to incur no bad effects on the correctness of MTO, even though the start point of this formulation is highly questionable. It is also this neglect that made MTO consider a variant of multi-bit DPA attack, which was mistakenly thought to appropriately serve as an alternative powerful attack. This implies the soundness of MTO is also more or less arguable. Therefore, we fix this definitional flaw and provide a revised definition named reVisited TO (VTO). For demonstrating validity and soundness of VTO, we present simulated and practical DPA attacks on implementations of $4\times 4$ and $8\times 8$ S-boxes. In addition, we also illustrate the soundness of VTO in masked S-boxes. Furthermore, as a concrete application of VTO, we present the distribution of VTO values of optimal affine equivalence classes of $4\times 4$ S-boxes and give some recommended guidelines on how to select $4\times 4$ S-boxes with higher DPA resistance at the identical level of implementation cost.
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Li, Jiang, Xiaohui Liu, and Chunjin Wei. "Stationary distribution of a stage-structure predator–prey model with prey’s counter-attack and higher-order perturbations." Applied Mathematics Letters 129 (July 2022): 107921. http://dx.doi.org/10.1016/j.aml.2022.107921.
38
Branciard, C., N. Gisin, N. Lutkenhaus, and V. Scarani. "Zero-error attacks and detection statistics in the coherent one-way protocol for quantum cryptography." Quantum Information and Computation 7, no. 7 (September 2007): 639–64. http://dx.doi.org/10.26421/qic7.7-6.
Анотація:
This is a study of the security of the Coherent One-Way (COW) protocol for quantum cryptography, proposed recently as a simple and fast experimental scheme. In the zero-error regime, the eavesdropper Eve can only take advantage of the losses in the transmission. We consider new attacks, based on unambiguous state discrimination, which perform better than the basic beam-splitting attack, but which can be detected by a careful analysis of the detection statistics. These results stress the importance of testing several statistical parameters in order to achieve higher rates of secret bits.
39
Deng, Ya Juan, and Shao Rong Hu. "Topology Characteristic of Hub-and-Spoke Transportation Network." Applied Mechanics and Materials 361-363 (August 2013): 2030–35. http://dx.doi.org/10.4028/www.scientific.net/amm.361-363.2030.
Анотація:
As the hub-and-spoke network can achieve the balance of efficiency and cost, currently it is widely used in aviation, public and logistics transportation. The article chooses connectivity, node degree, entropy, and concentration indicator to analyze topology characteristic of hub-and-spoke transportation network; as well as structure reliability indicator considering sub-network numbers, shortest path and network dimension to research the reliability of hub-and-spoke network. The conclusion includes: hub-and-spoke network has higher connectivity, larger difference of node importance, higher order and less convenient; the ability to deal with random attacks is strong while the capability to resist deliberate attack is poor. The conclusion can improve planning and evaluation method of hub-and-spoke transportation network.
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Abreu Maranhão, João Paulo, João Paulo Carvalho Lustosa da Costa, Edison Pignaton de Freitas, Elnaz Javidi, and Rafael Timóteo de Sousa Júnior. "Error-Robust Distributed Denial of Service Attack Detection Based on an Average Common Feature Extraction Technique." Sensors 20, no. 20 (October 16, 2020): 5845. http://dx.doi.org/10.3390/s20205845.
Анотація:
In recent years, advanced threats against Cyber–Physical Systems (CPSs), such as Distributed Denial of Service (DDoS) attacks, are increasing. Furthermore, traditional machine learning-based intrusion detection systems (IDSs) often fail to efficiently detect such attacks when corrupted datasets are used for IDS training. To face these challenges, this paper proposes a novel error-robust multidimensional technique for DDoS attack detection. By applying the well-known Higher Order Singular Value Decomposition (HOSVD), initially, the average value of the common features among instances is filtered out from the dataset. Next, the filtered data are forwarded to machine learning classification algorithms in which traffic information is classified as a legitimate or a DDoS attack. In terms of results, the proposed scheme outperforms traditional low-rank approximation techniques, presenting an accuracy of 98.94%, detection rate of 97.70% and false alarm rate of 4.35% for a dataset corruption level of 30% with a random forest algorithm applied for classification. In addition, for error-free conditions, it is found that the proposed approach outperforms other related works, showing accuracy, detection rate and false alarm rate of 99.87%, 99.86% and 0.16%, respectively, for the gradient boosting classifier.
41
Zhang, Chenhui, Le Wang, Dunqiu Fan, Junyi Zhu, Tang Zhou, Liyi Zeng, and Zhaohua Li. "VTT-LLM: Advancing Vulnerability-to-Tactic-and-Technique Mapping through Fine-Tuning of Large Language Model." Mathematics 12, no. 9 (April 24, 2024): 1286. http://dx.doi.org/10.3390/math12091286.
Анотація:
Vulnerabilities are often accompanied by cyberattacks. CVE is the largest repository of open vulnerabilities, which keeps expanding. ATT&CK models known multi-step attacks both tactically and technically and remains up to date. It is valuable to correlate the vulnerability in CVE with the corresponding tactic and technique of ATT&CK which exploit the vulnerability, for active defense. Mappings manually is not only time-consuming but also difficult to keep up-to-date. Existing language-based automated mapping methods do not utilize the information associated with attack behaviors outside of CVE and ATT&CK and are therefore ineffective. In this paper, we propose a novel framework named VTT-LLM for mapping Vulnerabilities to Tactics and Techniques based on Large Language Models, which consists of a generation model and a mapping model. In order to generate fine-tuning instructions for LLM, we create a template to extract knowledge of CWE (a standardized list of common weaknesses) and CAPEC (a standardized list of common attack patterns). We train the generation model of VTT-LLM by fine-tuning the LLM according to the above instructions. The generation model correlates vulnerability and attack through their descriptions. The mapping model transforms the descriptions of ATT&CK tactics and techniques into vectors through text embedding and further associates them with attacks through semantic matching. By leveraging the knowledge of CWE and CAPEC, VTT-LLM can eventually automate the process of linking vulnerabilities in CVE to the attack techniques and tactics of ATT&CK. Experiments on the latest public dataset, ChatGPT-VDMEval, show the effectiveness of VTT-LLM with an accuracy of 85.18%, which is 13.69% and 54.42% higher than the existing CVET and ChatGPT-based methods, respectively. In addition, compared to fine-tuning without outside knowledge, the accuracy of VTT-LLM with chain fine-tuning is 9.24% higher on average across different LLMs.
42
Luo, Yuling, Dezheng Zhang, and Junxiu Liu. "A Chaotic Block Cryptographic System Resistant to Power Analysis Attack." International Journal of Bifurcation and Chaos 29, no. 08 (July 2019): 1950106. http://dx.doi.org/10.1142/s0218127419501062.
Анотація:
The securities of chaotic cryptographic systems are widely evaluated by conventional tests such as the character frequency test, entropy test and avalanche test. However, when the chaotic cryptosystem is in operation, side channel information such as power consumption, and electromagnetic radiation is leaked. The side channel information can be used to attack the cryptosystem, e.g. the side channel attack (SCA), which is a threat for the security of chaotic cryptographic systems. This paper proposes a chaotic block cryptographic algorithm that can resist the SCA, with the aim of enhancing the security of chaotic cryptosystems. Masking and hiding mechanisms are used in this work. By using the former, the intermediate data correlated with the plaintexts/keys are masked by random numbers, thus no direct correlation exists between the power consumption and the plaintexts/keys and the first order SCA can be counteracted. By using the latter, additional noise is added to the side channel information by randomizing the operation sequence of the algorithm. Combining these two methods, the higher order SCA can be counteracted. To evaluate the security of the proposed system, the correlation power analysis attacks are carried out based on the target device of an Atmel XMEGA microcontroller. For the proposed system, the correlation coefficient calculated from the correct key is not larger than the incorrect keys. However, for the unprotected cipher system, the correlation coefficient calculated from the correct key is 0.8 and the coefficients calculated from the incorrect keys are less than 0.5, i.e. the system can be attacked. Experimental results demonstrate that the proposed cryptosystems can counteract the correlation power analysis attacks and maintain the security performance for the chaotic cryptographic systems.
43
Carvallo, P., E. Carvallo, R. Rivas, L. Carvallo, and M. Del Sol. "Middle Cerebral Artery Occlusion in Acute Ischaemic Cerebrovascular Attack." International Journal of Medical and Surgical Sciences 3, no. 1 (October 26, 2018): 747–51. http://dx.doi.org/10.32457/ijmss.2016.003.
Анотація:
Ischaemic stroke (CVA) is one of the leading causes of morbidity and mortality at a global and national level. We studied 35 patients, determined the arteries that presented a higher frequency of occlusion in acute ischemic stroke and identified the middle cerebral artery and the poste- rior cerebral artery. We consider it necessary that specialists can locate anatomically strokes in order to apply neuroprotective therapies to improve treatment options and preventing secondary obstructions.
44
Yin, Ziwei, Kun Li, and Hongjun Bi. "Trusted Multi-Domain DDoS Detection Based on Federated Learning." Sensors 22, no. 20 (October 12, 2022): 7753. http://dx.doi.org/10.3390/s22207753.
Анотація:
Aiming at the problems of single detection target of existing distributed denial of service (DDoS) attacks, incomplete detection datasets and privacy caused by shared datasets, we propose a trusted multi-domain DDoS detection method based on federated learning. Firstly, we divide the types of DDoS attacks into different sub-attacks, design the federated learning dataset for DDoS detection in each domain, and use them to realize a more comprehensive detection method of DDoS attacks on the premise of protecting the data privacy of each domain. Secondly, in order to improve the robustness of federated learning and alleviate poisoning attack, we propose a reputation evaluation method based on blockchain, which estimates interaction reputation, data reputation and resource reputation of each participant comprehensively, so as to obtain the trusted federated learning participants and identify the malicious participants. In addition, we also propose a combination scheme of multi-domain detection and distributed knowledge base and design a feature graph of malicious behavior based on a knowledge graph to realize the memory of multi-domain feature knowledge. The experimental results show that the accuracy of most categories of the multi-domain DDoS detection method can reach more than 95% with the protection of datasets, and the reputation evaluation method proposed in this paper has a higher ability to identify malicious participants against the data poisoning attack when the threshold is set to 0.6.
45
Sagu, Amit, Nasib Singh Gill, Preeti Gulia, Jyotir Moy Chatterjee, and Ishaani Priyadarshini. "A Hybrid Deep Learning Model with Self-Improved Optimization Algorithm for Detection of Security Attacks in IoT Environment." Future Internet 14, no. 10 (October 19, 2022): 301. http://dx.doi.org/10.3390/fi14100301.
Анотація:
With the growth of the Internet of Things (IoT), security attacks are also rising gradually. Numerous centralized mechanisms have been introduced in the recent past for the detection of attacks in IoT, in which an attack recognition scheme is employed at the network’s vital point, which gathers data from the network and categorizes it as “Attack” or “Normal”. Nevertheless, these schemes were unsuccessful in achieving noteworthy results due to the diverse necessities of IoT devices such as distribution, scalability, lower latency, and resource limits. The present paper proposes a hybrid model for the detection of attacks in an IoT environment that involves three stages. Initially, the higher-order statistical features (kurtosis, variance, moments), mutual information (MI), symmetric uncertainty, information gain ratio (IGR), and relief-based features are extracted. Then, detection takes place using Gated Recurrent Unit (GRU) and Bidirectional Long Short-Term Memory (Bi-LSTM) to recognize the existence of network attacks. For improving the classification accuracy, the weights of Bi-LSTM are optimally tuned via a self-upgraded Cat and Mouse Optimizer (SU-CMO). The improvement of the employed scheme is established concerning a variety of metrics using two distinct datasets which comprise classification accuracy, and index, f-measure and MCC. In terms of all performance measures, the proposed model outperforms both traditional and state-of-the-art techniques.
46
Hadi, Yusuf Sudo, Dede Hermawan, Imam Busyra Abdillah, Mahdi Mubarok, Wa Ode Muliastuty Arsyad, and Rohmah Pari. "Polystyrene-Impregnated Glulam Resistance to Subterranean Termite Attacks in a Laboratory Test." Polymers 14, no. 19 (September 24, 2022): 4003. http://dx.doi.org/10.3390/polym14194003.
Анотація:
This study aimed to enhance tropical fast-growing tree species’ resistance to subterranean termite (Coptotermes curvignathus) attacks through the manufacturing of polystyrene glued-laminated timber (glulam). Three young tropical wood species, namely manii (Maesopsis eminii), mangium (Acacia mangium), and rubber-wood (Hevea brasiliensis), were cut into laminae. After drying, the laminae were impregnated with styrene monomer, then polymerized using potassium peroxydisulfate as a catalyst and heat. The polystyrene-impregnated laminae were constructed using isocyanate glue and a cold press for three-layered glulam. Untreated or control glulam and solid wood specimens were also prepared. The specimens of each wood species and wood products (solid wood, control glulam, and polystyrene glulam) were exposed to the termite in a laboratory test according to Indonesian standards. The results showed that mangium wood had better resistance to the termite attack than manii and rubber-wood, with both of those woods performing the same. Among the wood products, the glulams were equal and had higher resistance to the termite attack than solid wood. To enhance the termite resistance of polystyrene glulam, we suggest that the polymer loading of polystyrene on each lamina should be increased. In our evaluation of the products’ order of priority, polystyrene glulam emerged as performing best towards subterranean termites attack.
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Khare, Surbhi, and Abhishek Badholia. "BLA2C2: Design of a Novel Blockchain-based Light-Weight Authentication & Access Control Layer for Cloud Deployments." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 3 (April 5, 2023): 283–94. http://dx.doi.org/10.17762/ijritcc.v11i3.6359.
Анотація:
Cloud deployments are consistently under attack, from both internal and external adversaries. These attacks include, but are not limited to brute force, masquerading, improper access, session hijacking, cross site scripting (XSS), etc. To mitigate these attacks, a wide variety of authentication & access control models are proposed by researchers, and each of them vary in terms of their internal implementation characteristics. It was observed that these models are either highly complex, or lack in terms of security under multiple attacks, which limits their applicability for real-time deployments. Moreover, some of these models are not flexible and cannot be deployed under dynamic cloud scenarios (like constant reconfigurations of Virtual Machines, dynamic authentication use-cases, etc.). To overcome these issues, this text proposes design of a novel blockchain-based Light-weight authentication & access control layer that can be used for dynamic cloud deployments. The proposed model initially applies a header-level light-weight sanitization layer that removes Cross Site Scripting, SQL Injection, and other data-level attacks. This is followed by a light-weight authentication layer, that assists in improving login-level security for external attacks. The authentication layer uses IP matching with reverse geolocation mapping in order to estimate outlier login attempts. This layer is cascaded with an efficient blockchain-based access control model, which assists in mitigating session hijacking, masquerading, sybil and other control-level attacks. The blockchain model is developed via integration of Grey Wolf Optimization (GWO) to reduce unnecessary complexities, and provides faster response when compared with existing blockchain-based security deployments. Efficiency of the model was estimated in terms of accuracy of detection for different attack types, delay needed for detection of these attacks, and computational complexity during attack mitigation operations. This performance was compared with existing models, and it was observed that the proposed model showcases 8.3% higher accuracy, with 10.5% lower delay, and 5.9% lower complexity w.r.t. standard blockchain-based & other security models. Due to these enhancements, the proposed model was capable of deployment for a wide variety of large-scale scenarios.
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Mialhe, PJ. "Preferential prey selection by Desmodus rotundus (E. Geoffroy, 1810, Chiroptera, Phyllostomidae) feeding on domestic herbivores in the municipality of São Pedro - SP." Brazilian Journal of Biology 74, no. 3 (August 2014): 579–84. http://dx.doi.org/10.1590/bjb.2014.0086.
Анотація:
In order to verify possible preferential prey selection by Desmodus rotundus feeding on domestic herbivores in the Municipality of São Pedro (São Paulo, Brazil), vampire bat attacks were surveyed at rural properties where domestic herbivores were being raised and attack frequencies of D. rotundus on the total herd and on different species were calculated. The analysis found that the most frequently attacked herbivores were cattle and horses. The chi-square test (χ2), with a significance level of 5% corroborated the comparative analysis of attack frequency in properties that had these two species. Of the two, horses were attacked more frequently, which could be a sign that D. rotundus exhibits preferential prey selection when attacking domestic herbivores. This evidence is also supported by the Optimal Foraging Theory, in which the net rate of energy consumed is higher for horses than it is for cattle. Additionally, we propose that the thinner integument of horses (relative to that of cattle) may facilitate bites by D. rotundus and thus contribute to the observed prey preference.
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Domingo, Luis R., Mar Ríos-Gutiérrez, and Patricia Pérez. "Unveiling the Chemistry of Higher-Order Cycloaddition Reactions within the Molecular Electron Density Theory." Chemistry 4, no. 3 (July 26, 2022): 735–52. http://dx.doi.org/10.3390/chemistry4030052.
Анотація:
The higher-order cycloaddition (HOCA) reaction of tropone with cyclopentadiene (Cp) has been studied within the Molecular Electron Density Theory. The Electron Localization Function (ELF) analysis of the electronic structure of tropone and Cp characterizes the structural behaviors of the two conjugated unsaturated systems, while the conceptual DFT reactivity indices classify tropone as a strong electrophile and Cp as a strong nucleophile participating in polar cycloaddition reactions of reverse electron density flux. Eight competitive reaction paths have been characterized for this cycloaddition reaction. The most favorable one allowing the formation of the formal out [6 + 4] cycloadduct has an activation enthalpy of 16.2 kcal·mol−1, and the reaction is exothermic by −21.4 kcal·mol−1. This HOCA reaction, which takes place through a non-concerted two-stage one-step mechanism, presents high stereo-, pseudocyclic- and regioselectivities, explaining the exclusive formation of the experimental [6 + 4] cycloadduct. While the most favorable nucleophilic attack of Cp on most electrophilic C2 positions of tropone accounts for regioselectivities, the favorable electrostatic interactions present between the Cp framework and the negatively charged O8 oxygen of tropone account for the stereo- and pseudocyclic selectivities. Despite the symmetry of the two reagents, this HOCA reaction takes place via a highly asynchronous transition state structure as a consequence of the most favorable two-center interactions taking place between the electrophilic C2 center of tropone and the nucleophilic C9 center of Cp.
50
Salem, Ahmed, Xuening Liao, Yulong Shen, and Xiaohong Jiang. "Provoking the Adversary by Detecting Eavesdropping and Jamming Attacks: A Game-Theoretical Framework." Wireless Communications and Mobile Computing 2018 (August 28, 2018): 1–14. http://dx.doi.org/10.1155/2018/1029175.
Анотація:
This paper investigates the secrecy and reliability of a communication where the user is assisting an Intrusion Detection System (IDS) in detecting the adversary’s attack. The adversary is assumed to be sophisticated such that it can conduct eavesdropping and jamming attacks. The IDS is equipped with the capability of detecting both of those attacks. Two scenarios were considered; the first scenario is that the user is trying to detect the adversary by assisting the IDS, and the second scenario is that the user is equipped with a silent time slot in its communication protocol besides assisting the IDS, in order to provoke the adversary into jamming the channel, thus detecting it with a higher probability. Interestingly, adding the capability of detecting eavesdropping attacks pushed the adversary into conducting jamming attacks much more, thus aiding in detecting the adversary earlier. All of that was modeled by means of stochastic game theory, in order to analyze and study the behavior and the interactions between the user and the adversary. Results show a major improvement in the first scenario by 188% and an improvement by 294% in the second scenario in the game value when the probability of detecting eavesdropping attacks was 0.3, which represents the payoff that the user gains in terms of secrecy and reliability.