Journal articles on the topic 'Attack on the network'
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1
Ahmed, Abdulghani Ali. "Investigation Approach for Network Attack Intention Recognition." International Journal of Digital Crime and Forensics 9, no. 1 (January 2017): 17–38. http://dx.doi.org/10.4018/ijdcf.2017010102.
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Sensitive information has critical risks when transmitted through computer networks. Existing protection systems still have limitations with treating network information with sufficient confidentiality, integrity, and availability. The rapid development of network technologies helps increase network attacks and hides their malicious intentions. Attack intention is the ultimate attack goal that the attacker attempts to achieve by executing various intrusion methods or techniques. Recognizing attack intentions helps security administrator develop effective protection systems that can detect network attacks that have similar intentions. This paper analyses attack types and classifies them according to their malicious intent. An investigation approach based on similarity metric is proposed to recognize attacker plans and predict their intentions. The obtained results demonstrate that the proposed approach is capable of investigating similarity of attack signatures and recognizing the intentions of Network attack.
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Singhal, Prateek, Puneet Sharma, and Deepak Arora. "An approach towards preventing iot based sybil attack based on contiki framework through cooja simulator." International Journal of Engineering & Technology 7, no. 2.8 (March 19, 2018): 261. http://dx.doi.org/10.14419/ijet.v7i2.8.10421.
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In this paper we propagate the Sybil attack in WSN (Wireless sensor network), by the researchers many attacks have been recognized in WSN till now and there are many attacks which can attack over through internet, Internet of thing means all devices is interconnected to each other M2M over internet and can be attacked by any of the attacker on any devices. Sybil attack is the detrimental attack against sensor network where several counterfeit identities and legitimate identities are used to get prohibited pass in a network. This is major attack which results an information loss and misinterpretation in the network, and it also minimizes the routing disturbance, trustworthiness and dropping sensitivity packets into a network. In this instance node can trust the imaginary node and sharing of information starts, owed to this security of node is get affected and information is lost. In this paper, a survey of CONTIKI OS-2.7, stimulation tool COOJA and the Sybil attack and proposed the defense mechanisms and CAM (Compare and Match) approach to verify the Sybil attack position and prevent it. This Sybil attack can be stimulated on the stimulation tool COOJA which helps to identify the attacker position node, whereas these attacks outcome in uni-casting as well as multicasting and in this paper specifically given the secure security for Wireless sensor network.
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Glăvan, Dragoș. "Sniffing attacks on computer networks." Scientific Bulletin of Naval Academy XXIII, no. 1 (July 15, 2020): 202–7. http://dx.doi.org/10.21279/1454-864x-20-i1-027.
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The sniffing attack or sniffer attack, in the context of network security, corresponds to data theft or interception by capturing network traffic using a sniffer (an application that aims to capture network packets). When data is transmitted over networks, if data packets are not encrypted, data in the network packet can be read using a sniffer. Using a sniffer application, an attacker can analyze the network and obtain information so that it can eventually crash or corrupt the network or read the communications that occur in the network. Sniffing attacks can be compared to touching wires and getting to know the conversation, and for this reason it is also called "wiretapping" applied to computer networks. In this paper, a sniffing attack is shared which can significantly damage the computer networks as well as methods of combating such attacks. Sniffing is usually performed to analyze network usage, troubleshoot network problems, monitor session for development and testing purposes.
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Winda Andrini Wulandari. "THE ANALYSIS NETWORK FORENSICS USING HONEYPOT ON PUBLIC CLOUD COMPUTING SERVICE NETWORK." Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) 3, no. 1 (April 20, 2018): 18–25. http://dx.doi.org/10.20527/jtiulm.v3i1.24.
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This research presents visualization in dashboard using AWN campus honeypot log data connected to IHP (Kemkominfo) Jakarta on public cloud computing service network to categorize time stamp in data. Package attack data is divided into three categories namely morning, noon, and night based on Time Western Indonesia (WIB). DDoS attacks attacked several ports 21, 80, 135, and 445. K -means clustering method is implemented in this research to get categorization result of time of effective attack to know DDoS attack attack and cyber profilling which is expected to help monitoring process of anticipation of vulnerability cloud network of ddos / cyber crime attacks. The results of this study indicate that the method used to obtain results in accordance with the objectives.
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Kamaleshwar, T., R. Lakshminarayanan, Yuvaraja Teekaraman, Ramya Kuppusamy, and Arun Radhakrishnan. "Self-Adaptive Framework for Rectification and Detection of Black Hole and Wormhole Attacks in 6LoWPAN." Wireless Communications and Mobile Computing 2021 (December 26, 2021): 1–8. http://dx.doi.org/10.1155/2021/5143124.
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Internet network communication protocol version 6 low-power wireless personal area networks (6LoWPAN) is supposed to assist the gadgets with low-power wireless sensor network (WSN) and it furnishes the top model layer of the data transmission system. The 6LoWPAN is prone to the diversified attacks such as wormhole and black hole attacks, which might be very difficult to become aware of and defend. In a wormhole attack, the attacker listens to the facts over the networks, and in a black hole attack, the intruder reprograms the nodes to dam the data transmission. As an end result, any data datagram that enters the attacked region will end result in transmission failure with low flow network rate and excessive one-way delay. To come across and heal the attack, a self-adaptive framework is brought into the networks and the procedure of data transmission is enriched. In this work, the affected region is measured and rectified with the aid of using the proposed self-adaptive framework for Ad Hoc On-Demand Distance Vector (AODV) routing protocol network communication protocol. The overall performance of the network healing technique is investigated with the aid of using simulation and its miles diagnosed that the proposed framework suggests promising overall performance with the aid of using accomplishing excessive flow network rate and minimum delay.
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Park, Sanglee, and Jungmin So. "On the Effectiveness of Adversarial Training in Defending against Adversarial Example Attacks for Image Classification." Applied Sciences 10, no. 22 (November 14, 2020): 8079. http://dx.doi.org/10.3390/app10228079.
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State-of-the-art neural network models are actively used in various fields, but it is well-known that they are vulnerable to adversarial example attacks. Throughout the efforts to make the models robust against adversarial example attacks, it has been found to be a very difficult task. While many defense approaches were shown to be not effective, adversarial training remains as one of the promising methods. In adversarial training, the training data are augmented by “adversarial” samples generated using an attack algorithm. If the attacker uses a similar attack algorithm to generate adversarial examples, the adversarially trained network can be quite robust to the attack. However, there are numerous ways of creating adversarial examples, and the defender does not know what algorithm the attacker may use. A natural question is: Can we use adversarial training to train a model robust to multiple types of attack? Previous work have shown that, when a network is trained with adversarial examples generated from multiple attack methods, the network is still vulnerable to white-box attacks where the attacker has complete access to the model parameters. In this paper, we study this question in the context of black-box attacks, which can be a more realistic assumption for practical applications. Experiments with the MNIST dataset show that adversarially training a network with an attack method helps defending against that particular attack method, but has limited effect for other attack methods. In addition, even if the defender trains a network with multiple types of adversarial examples and the attacker attacks with one of the methods, the network could lose accuracy to the attack if the attacker uses a different data augmentation strategy on the target network. These results show that it is very difficult to make a robust network using adversarial training, even for black-box settings where the attacker has restricted information on the target network.
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Qin, Yuan. "Computer Network Attack Modeling and Network Attack Graph Study." Advanced Materials Research 1079-1080 (December 2014): 816–19. http://dx.doi.org/10.4028/www.scientific.net/amr.1079-1080.816.
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With the development of computer network and rapid popularity of Internet, network information security has become the focus of safeguarding national security and social stability. In the network security event, the hacker often can’t successfully intrude into the network by means of a single host / services hacker. With the help of various kinds of "vulnerability" generated bydifferent relationship existing in multiple point multiple host, the hacker can achieve the purpose of network intrusion. Therefore one important aspect of network security is after obtaining the vulnerability of the network information, considering a combination of multiple exploits and analyzing the attack path of network penetration attacks that the attacker may take.
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Gandhi, Kaushal, Rajneesh Narula, Sumeer Khullar, and Anish Arora. "Security Issues of Routing Protocols in MANETs." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 2 (October 30, 2012): 339–42. http://dx.doi.org/10.24297/ijct.v3i2c.2894.
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There are a number of routing protocols developed by researchers. Due to the nature of ad hoc networks, secure routing is an important area of research in developing secure routing protocols. Although researchers have proposed several secure routing protocols, their resistance towards various types of security attacks and efficiency are primary points of concern in implementing these protocols. This paper presents some of the available secure routing protocols and most common attack patterns against ad hoc networks. Routing protocols are subjected to case studies against the most commonly identified attack patterns such as: denial-of-service attack, tunneling, spoofing, black hole attack and wormhole attack etc. In MANET, the nodes also function as routers that discover and maintain routes to other nodes in the network. Establishing an optimal and efficient route between the communicating parties is the primary concern of the routing protocols of MANET. Any attack in routing phase may disrupt the overall communication and the entire network can be paralyzed. Thus, security in network layer plays an important role in the security of the whole network. A number of attacks in network layer have been identified and studied in security research. An attacker can absorb network traffic, inject themselves into the path between the source and destination and thus control the network traffic flow.
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Sehrawat, Harkesh, Yudhvir Singh, and Vikas Siwach. "Analysis of AODV protocol under sinkhole attack in wireless sensor network." International Journal of Engineering & Technology 7, no. 2.4 (March 10, 2018): 153. http://dx.doi.org/10.14419/ijet.v7i2.4.13028.
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A Wireless Sensor Network (WSNs) is a collection of number of sensor nodes which are left open in an unsecured environment. Sensor nodes work and communicate together to attain the desired goals. They are placed at the locations where monitoring is otherwise impossible. Wireless Sensor Networks are resource constrained which may be computational power, memory capacity, battery power etc. As Wireless Sensor Networks are implemented in the unattended environment, they are prone to discrete type of security attacks. Because of their limitations these networks are easily targeted by intruders. Sinkhole attack is one of the security attacks which try to disturb the ongoing communication in wireless sensor network. In sinkhole attack, the intruder or the malicious node try to attract the network traffic towards itself, that sensor nodes will pass data packets through this compromised node thereby manipulating messages which sensor nodes are transferring to the base station. In this paper we analyze the impact of Sinkhole attack on AODV protocol under various conditions. We analyzed the impact of Sinkhole attack on AODV protocol with varying number of attacker nodes.
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Moskal, Stephen, Shanchieh Jay Yang, and Michael E. Kuhl. "Cyber threat assessment via attack scenario simulation using an integrated adversary and network modeling approach." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 15, no. 1 (August 15, 2017): 13–29. http://dx.doi.org/10.1177/1548512917725408.
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Existing research on cyber threat assessment focuses on analyzing the network vulnerabilities and producing possible attack graphs. Cyber attacks in real-world enterprise networks, however, vary significantly due to not only network and system configurations, but also the attacker’s strategies. This work proposes a cyber-based attacker behavior model (ABM) in conjunction with the Cyber Attack Scenario and Network Defense Simulator to model the interaction between the network and the attackers. The ABM leverages a knowledge-based design and factors in the capability, opportunity, intent, preference, and Cyber Attack Kill Chain integration to model various types of attackers. By varying the types of attackers and the network configurations, and simulating their interactions, we present a method to measure the overall network security against cyber attackers under different scenarios. Simulation results based on four attacker types on two network configurations are shown to demonstrate how different attacker behaviors may lead to different ways to penetrate a network, and how a single misconfiguration may impact network security.
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Podobnik, B., D. Horvatic, T. Lipic, M. Perc, J. M. Buldú, and H. E. Stanley. "The cost of attack in competing networks." Journal of The Royal Society Interface 12, no. 112 (November 2015): 20150770. http://dx.doi.org/10.1098/rsif.2015.0770.
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Real-world attacks can be interpreted as the result of competitive interactions between networks, ranging from predator–prey networks to networks of countries under economic sanctions. Although the purpose of an attack is to damage a target network, it also curtails the ability of the attacker, which must choose the duration and magnitude of an attack to avoid negative impacts on its own functioning. Nevertheless, despite the large number of studies on interconnected networks, the consequences of initiating an attack have never been studied. Here, we address this issue by introducing a model of network competition where a resilient network is willing to partially weaken its own resilience in order to more severely damage a less resilient competitor. The attacking network can take over the competitor's nodes after their long inactivity. However, owing to a feedback mechanism the takeovers weaken the resilience of the attacking network. We define a conservation law that relates the feedback mechanism to the resilience dynamics for two competing networks. Within this formalism, we determine the cost and optimal duration of an attack, allowing a network to evaluate the risk of initiating hostilities.
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Patel, Anshuman, and Devesh Jinwala. "A Trust-Integrated RPL Protocol to Detect Blackhole Attack in Internet of Things." International Journal of Information Security and Privacy 15, no. 4 (October 2021): 1–17. http://dx.doi.org/10.4018/ijisp.2021100101.
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Internet of things (IoT) offers communication between user-to-machine and machine-to-machine. Due to their inherent characteristics of open medium, very dynamic topology, lack of infrastructure and lack of centralized management authority, IoT present serious vulnerabilities to security attacks. The routing protocol for low-power and lossy networks (RPL) does not have an inherent mechanism to detect routing attacks. Popular among these IoT attacks is blackhole attack. An attacker can exploit the routing system of RPL to launch blackhole attack against an IoT network. To secure IoT networks from blackhole attack, trust-integrated RPL protocol (TRPL) is proposed and implemented. The trust system is embedded in the RPL protocol to detect and isolate a blackhole attack while optimizing network performance. The trust is calculated from successful interaction between two nodes. The calculated trust value is considered in parent selection. TRPL demonstrates its superior performance over the standard RPL protocol and existing techniques in the detection and isolation of blackhole attacks.
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BALABAN, Ioana. "Denial-of-Service Attack." International Journal of Information Security and Cybercrime 10, no. 1 (June 29, 2021): 59–64. http://dx.doi.org/10.19107/ijisc.2021.01.06.
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A denial-of-service (DoS) is any type of attack where the attackers (hackers) attempt to prevent legitimate users from accessing the service. In a DoS attack, the attacker usually sends excessive messages asking the network or server to authenticate requests that have invalid return addresses. The network or server will not be able to find the return address of the attacker when sending the authentication approval, causing the server to wait before closing the connection. When the server closes the connection, the attacker sends more authentication messages with invalid return addresses. Hence, the process of authentication and server wait will begin again, keeping the network or server busy. This paper presents how DoS attacks are performed, the techniques used, the attack tools, the prevention of an attack and the some of the famous DoS attacks.
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Yan, Yao, and Rui Xu. "DDoS Attacks for Ad Hoc Network Based on Attack Cluster." Advanced Materials Research 546-547 (July 2012): 1371–76. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.1371.
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Show the definition of Ad Hoc network attack cluster, and propose a new method of DDoS attacks for Ad Hoc Networks, which can accurately attack the target node, demonstrate no redundant aggressive behavior compared with the traditional attack and reduce the detection rate of aggressive behavior. Use NS2 simulation platform to build Ad Hoc network simulation scenarios with dynamic topology, and simulate DDoS attacks in this environment; The simulation results show that the new DDoS attack method can effectively reduce the communication ability of the Ad Hoc network, and increasing the attack node density will strengthen the attack effect.
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Chandran, Rahul, and Wei Q. Yan. "Attack Graph Analysis for Network Anti-Forensics." International Journal of Digital Crime and Forensics 6, no. 1 (January 2014): 28–50. http://dx.doi.org/10.4018/ijdcf.2014010103.
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The development of technology in computer networks has boosted the percentage of cyber-attacks today. Hackers are now able to penetrate even the strongest IDS and firewalls. With the help of anti-forensic techniques, attackers defend themselves, from being tracked by destroying and distorting evidences. To detect and prevent network attacks, the main modus of operandi in network forensics is the successful implementation and analysis of attack graph from gathered evidences. This paper conveys the main concepts of attack graphs, requirements for modeling and implementation of graphs. It also contributes the aspect of incorporation of anti-forensic techniques in attack graph which will help in analysis of the diverse possibilities of attack path deviations and thus aids in recommendation of various defense strategies for better security. To the best of our knowledge, this is the first time network anti-forensics has been fully discussed and the attack graphs are employed to analyze the network attacks. The experimental analysis of anti-forensic techniques using attack graphs were conducted in the proposed test-bed which helped to evaluate the model proposed and suggests preventive measures for the improvement of security of the networks.
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Dhaked, Urvashi, Dr Ashok Kumar, and Dr Brajesh Kumar Singh. "Detection and Isolation Technique for Sinkhole Attack in WSN." Journal of University of Shanghai for Science and Technology 23, no. 10 (October 9, 2021): 381–90. http://dx.doi.org/10.51201/jusst/21/10718.
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The WSN is a self-configuring network in which no centralized control is available. The sensing devices are considered as the nodes. These nodes have small size and low-cost. Primarily, the deployment of these networks is done in the military areas in order to monitor the activities of conflicting sides. These networks can monitor all the movement of energy. Malicious nodes can also join the network and trigger different types of active & passive attacks. The major kind of active attack is sinkhole intrusion. Such an attack allows the attacker node to spoof the identity of sink and act like sink itself. The sensor nodes focus on the transmission of information to the attacker node instead of BS. This research study suggests an algorithm to explore and segregate the attacker nodes from the network. This algorithm is designed on the basis of the identify confirmation. The NS2 (Network Simulator 2) is utilized to deploy the suggested algorithm and diverse metrics are utilized for analyzing the results.
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Shan, Chun, Benfu Jiang, Jingfeng Xue, Fang Guan, and Na Xiao. "An Approach for Internal Network Security Metric Based on Attack Probability." Security and Communication Networks 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/3652170.
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A network security metric may provide quantifiable evidence to assist security practitioners in securing computer networks. However, research on security metrics based on attack graph is not applicable to the characteristics of internal attack; therefore we propose an internal network security metric method based on attack probability. Our approach has the following benefits: it provides the method of attack graph simplification with monitoring event node which could solve the attack graph exponential growth with the network size, while undermining the disguise of internal attacks and improving the efficiency of the entire method; the method of attack probability calculation based on simplified attack graph can simplify the complexity of internal attacks and improve the accuracy of the approach.
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Mitchel, Christopher, Baraq Ghaleb, Safwan M. Ghaleb, Zakwan Jaroucheh, and Bander Ali Saleh Al-rimy. "The Impact of Mobile DIS and Rank-Decreased Attacks in Internet of Things Networks." International Journal of Engineering and Advanced Technology 10, no. 2 (December 30, 2020): 66–72. http://dx.doi.org/10.35940/ijeat.b1962.1210220.
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With a predicted 50 billion devices by the end of 2020, the Internet of things has grown exponentially in the last few years. This growth has seen an increasing demand for mobility support in low power and lossy sensor networks, a type of network characterized by several limitations in terms of their resources including CPU, memory and batter, causing manufactures to push products out to the market faster, without the necessary security features. IoT networks rely on the Routing Protocol for Low Power and Lossy Network (RPL) for communication, designed by the Internet Engineering Task Force (IETF). This protocol has been proven to be efficient in relation to the handling of routing in such constrained networks, However, research studies revealed that RPL was inherently designed for static networks, indicating poor handling of mobile or dynamic topologies which is worsen when introducing mobile attacker. In this paper, two IoT routing attacks are evaluated under a mobile attacker with the aim of providing a critical evaluation of the impact the attacks have on the network in comparison to the case with static attacker. The first attack is the Rank attack in which the attacker announces false routing information to its neighbour attracting them to forward their data via the attacker. The second attack is the DIS attack in which the attacker floods the network with DIS messages triggering them to reset their transmission timers and sending messages more frequently. The comparison were conducted in terms of average power consumption and also the packet delivery ratio (PDR). Based on the results collected from the simulations, it was established that when an attacking node is mobile, there’s an average increase of 36.6 in power consumption and a decrease of 14 for packet delivery ratios when compared to a static attacking node.
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Sowah, Robert A., Kwadwo B. Ofori-Amanfo, Godfrey A. Mills, and Koudjo M. Koumadi. "Detection and Prevention of Man-in-the-Middle Spoofing Attacks in MANETs Using Predictive Techniques in Artificial Neural Networks (ANN)." Journal of Computer Networks and Communications 2019 (January 20, 2019): 1–14. http://dx.doi.org/10.1155/2019/4683982.
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A Mobile Ad-Hoc Network (MANET) is a convenient wireless infrastructure which presents many advantages in network settings. With Mobile Ad-Hoc Network, there are many challenges. These networks are more susceptible to attacks such as black hole and man-in-the-middle (MITM) than their corresponding wired networks. This is due to the decentralized nature of their overall architecture. In this paper, ANN classification methods in intrusion detection for MANETs were developed and used with NS2 simulation platform for attack detection, identification, blacklisting, and node reconfiguration for control of nodes attacked. The ANN classification algorithm for intrusion detection was evaluated using several metrics. The performance of the ANN as a predictive technique for attack detection, isolation, and reconfiguration was measured on a dataset with network-varied traffic conditions and mobility patterns for multiple attacks. With a final detection rate of 88.235%, this work not only offered a productive and less expensive way to perform MITM attacks on simulation platforms but also identified time as a crucial factor in determining such attacks as well as isolating nodes and reconfiguring the network under attack. This work is intended to be an opening for future malicious software time signature creation, identification, isolation, and reconfiguration to supplement existing Intrusion Detection Systems (IDSs).
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Xia, Kui Liang. "Modeling and Simulation of Low Rate of Denial of Service Attacks." Applied Mechanics and Materials 484-485 (January 2014): 1063–66. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.1063.
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The low-rate denial of service attack is more applicable to the network in recent years as a means of attack, which is different from the traditional field type DoS attacks at the network end system or network using adaptive mechanisms exist loopholes flow through the low-rate periodic attacks on the implementation of high-efficiency attacked by an intruder and not be found, resulting in loss of user data or a computer deadlock. LDos attack since there has been extensive attention of researchers, the attack signature analysis and detection methods to prevent network security have become an important research topic. Some have been proposed for the current attacks were classified LDoS describe and model, and then in NS-2 platform for experimental verification, and then LDoS attack detection to prevent difficulties are discussed and summarized for the future such attacks detection method research work to provide a reference.
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Divekar, Anuja Sanjay, Deepali Borade, and Vivek Bugad. "A Simple and Efficient Mechanism to Detect and Avoid Wormhole Attacks in IP network through LOLS." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 14, no. 3 (January 8, 2015): 5543–49. http://dx.doi.org/10.24297/ijct.v14i3.1998.
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It has been observed that IP networks are vulnerable to many kinds of attacks. Among the various attacks possible in IP networks wormhole attack is one which is treated as a very severe attack. In LOLS, multiple failures are handled but network attack is not detected. LOLS cannot handle any kind of attack and this is the reason why we are working on wormhole attack and its detection by using AOMDV algorithm. In this attack a harmful node records packets at one end in the network and tunnels them to another harmful node which is present in the other end of the network. In this paper, we have proposed an algorithm which detects and avoids the wormhole attack while data transfer . In this paper one mechanism is used, which is based on the total round trip time (RTT) of current route and the average round trip times This mechanism works for both mobile ad hoc networks and wireless ad hoc networks.
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Najafabadi, Maryam M., Taghi M. Khoshgoftaar, and Amri Napolitano. "Detecting Network Attacks Based on Behavioral Commonalities." International Journal of Reliability, Quality and Safety Engineering 23, no. 01 (February 2016): 1650005. http://dx.doi.org/10.1142/s0218539316500054.
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Due to the great increase in the amount of attacks that occur in computer networks, there is an increasing dependence on network intrusion detection systems which monitor and analyze the network data to detect attacks. In recent years, machine learning methods have been used to build predictive models for network intrusion detection. These methods are able to automatically extract patterns from the network data to build detection models. Defining proper features, which help models to better discriminate between normal and attack data, is a critical task. While network attacks vary widely, they share some commonalities. Many attacks, by their nature, are repetitive and exhibit behaviors different from normal traffic. Among these commonalities are self-similarity between attack packets, periodicity and repetition characteristics seen in the attack traffic. In this paper, we study the common behaviors between two different attack types, called RUDY and DNS Amplification attacks, in order to propose new features for building predictive models by using machine learning algorithms. We collected Netflow traffic from an operational ISP network. We introduce a concept called “session” derived from Netflow which incorporates both sides of a network communication to define a network instance. Features are extracted for each session. To demonstrate how the newly defined features work for the task of intrusion detection, we use these features to build intrusion detection models for the detection of RUDY attack, DNS Amplification attack and the combination of these two attacks. To build predictive models we apply four machine learning classification algorithms: two versions of a decision tree algorithm, Naïve Bayes and 5-Nearest Neighbor (5-NN) algorithm. Our results show that the proposed features based on the attack commonalities provide very good prediction results for the detection of two studied attacks on real network traffic.
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Munir, Misbachul, Ipung Ardiansyah, Joko Dwi Santoso, Ali Mustopa, and Sri Mulyatun. "DETECTION AND MITIGATION OF DISTRIBUTED DENIAL OF SERVICE ATTACKS ON NETWORK ARCHITECTURE SOFTWARE DEFINED NETWORKING USING THE NAIVE BAYES ALGORITHM." Journal of Information System Management (JOISM) 3, no. 2 (January 16, 2022): 51–55. http://dx.doi.org/10.24076/joism.2022v3i2.656.
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DDoS attacks are a form of attack carried out by sending packets continuously to machines and even computer networks. This attack will result in a machine or network resources that cannot be accessed or used by users. DDoS attacks usually originate from several machines operated by users or by bots, whereas Dos attacks are carried out by one person or one system. In this study, the term to be used is the term DDoS to represent a DoS or DDoS attack. In the network world, Software Defined Network (SDN) is a promising paradigm. SDN separates the control plane from forwarding plane to improve network programmability and network management. As part of the network, SDN is not spared from DDoS attacks. In this study, we use the naïve Bayes algorithm as a method to detect DDoS attacks on the Software Defined Network network architecture
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Sun, Yan, and Xue Guang Zhou. "Research on Attack Model for Cognitive Network Based on Scientific Analysis of Network Material System." Applied Mechanics and Materials 63-64 (June 2011): 911–14. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.911.
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Cognitive attacks, which influence the user’s perceptions and behavior, are more serious than physical or even syntactic attacks. We construct an attack model for cognitive Network based on scientific analysis of Network material system to visualize cognitive attack. The cognitive attack model consists of two parts: attackers and netizens. We formalize each element of the model. The cognitive attack example analysis illustrates the rationality of the model.
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Thakur, Mandeep, and Amninder Kaur Gill. "Detection and Isolation Technique for Blackhole Attack in Wireless Sensor Network." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 8 (August 30, 2017): 25. http://dx.doi.org/10.23956/ijarcsse.v7i8.12.
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A wireless sensor network comprises of countless spread over a particular territory where we need to take care of at the progressions going ahead there. A sensor hub, for the most part, comprises of sensors, actuators, memory, a processor and they do have correspondence capacity. These sorts of networks are much powerless against security attacks. Many kinds of active and passive attacks are conceivable in the sensor network. Among all the conceivable active attacks, sinkhole attack is the most widely recognized and destructive attack. This attack debases network execution and prompts denial of service attack. The attack is triggered by the malicious hub which is available in the network. In this work, a novel strategy has been proposed to recognize and disengage malicious nodes from the network which are in charge of triggering the attack. The novel procedure is based on blacklist technique and clustering technique. The exploratory results will demonstrate that proposed strategy detects and separate the malicious nodes from the network proficiently. It will enhance network effectiveness as far as bundle misfortune, defer and expand throughput of the network. NS2 simulator instrument will be utilized as a part of it.
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Houmer, Meriem, and Moulay Lahcen Hasnaoui. "A risk and security assessment of VANET availability using attack tree concept." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 6 (December 1, 2020): 6039. http://dx.doi.org/10.11591/ijece.v10i6.pp6039-6044.
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The challenging nature of insecure wireless channels and the open-access environment make the protection of vehicular ad hoc network (VANET) a particularly critical issue. Researchers and interested authorities have therefore paid more attention to this issue. Therefore, robust approaches to protect this network's security and privacy against adversaries and attacks need to be improved, trying to achieve an adequate level, to secure the confidential information of drivers and passengers. Accordingly, to improve the security of VANET, it is necessary to carry out a risk assessment, in order to evaluate the risk that faces this network. This paper focuses on the security threats in vehicular network especially on the availability of this network. We propose a novel risk assessment approach to evaluate the risk of the attack that the attacker can lead against the availability of VANET. We adopt a tree structure called attack tree to model the attacker's potential attack strategies. Based on this attack tree model, we can estimate the degree that a certain threat can lead to the VANET and identify possible attack sequences that an attacker may launch against the availability of this network. Then we utilize the multi-attribute utility theory to calculate the system’s total risk value also the probabilities of each attack sequence. The analysis results can provide support for decision-makers to make corresponding protection measures against the attack on the availability of this network.
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Apiecionek, Łukasz, and Matusz Biedziak. "Fuzzy Adaptive Data Packets Control Algorithm for IoT System Protection." JUCS - Journal of Universal Computer Science 26, no. 11 (November 28, 2020): 1435–54. http://dx.doi.org/10.3897/jucs.2020.076.
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One of huge problem for recent IT systems are attacks on their resources called Distributed Denial of Service attacks. Many servers which are accessible from public network were a victim of such attacks or could be in the future. Unfortunately, there is still no effective method for protecting network servers against source of the attack, while such attack could block network resources for many hours. Existing solutions for protecting networks and IoT systems are using mainly firewalls and IDS/IPS mechanisms, which is not sufficient. This article presents the method minimizing the DDoS attacks. Proposed method provides possibilities for the network administrators to protect their servers and IoT network resources during the attack. The proposed fuzzy adaptive algorithm is using Ordered Fuzzy Numbers for predicting amount of packets which could be passed over the network boarder gateway. Proposed solution will give the opportunity for ordinary users to finish their work when the attack occurs.
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van Heerden, R. P., B. Irwin, I. D. Burke, and L. Leenen. "A Computer Network Attack Taxonomy and Ontology." International Journal of Cyber Warfare and Terrorism 2, no. 3 (July 2012): 12–25. http://dx.doi.org/10.4018/ijcwt.2012070102.
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Computer network attacks differ in the motivation of the entity behind the attack, the execution and the end result. The diversity of attacks has the consequence that no standard classification exists. The benefit of automated classification of attacks, means that an attack could be mitigated accordingly. The authors extend a previous, initial taxonomy of computer network attacks which forms the basis of a proposed network attack ontology in this paper. The objective of this ontology is to automate the classification of a network attack during its early stages. Most published taxonomies present an attack from either the attacker's or defender's point of view. The authors’ taxonomy presents both these points of view. The framework for an ontology was developed using a core class, the “Attack Scenario”, which can be used to characterize and classify computer network attacks.
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Lalar, Sacachin, Shashi Bhushan, and Surender Surender. "Analysis of Clone Detection Approaches in Static Wireless Sensor Networks." Oriental journal of computer science and technology 10, no. 3 (August 5, 2017): 653–59. http://dx.doi.org/10.13005/ojcst/10.03.14.
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Wireless Sensor Networks (WSNs) are developing very fast in the wireless networks. The wireless sensor network has the characteristics of limited memory, small size and limited battery. WSNs are vulnerable to the different types of attacks due to its characteristics. One of the attacks is clone node attack in which attacker capture the nodes from the network and stoles the information from it and replicates it in the network. From the clone nodes, the attacker can easily launch the different type of attacks in the network. To detect the clone node, different methods has been implemented .Each method having advantages and limitations. In the this paper, we explain the different methods to detect the clone nodes in the static wireless sensor network and compare their performance based on the communication cost and memory.
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Wang, Rui, Yingxian Chang, Lei Ma, Hao Zhang, Xin Liu, Jianfei Chen, Donglan Liu, Yong Zhang, and Bing Su. "The Border Attack Defense System is Software-Based." Journal of Physics: Conference Series 2074, no. 1 (November 1, 2021): 012041. http://dx.doi.org/10.1088/1742-6596/2074/1/012041.
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Abstract Now the computer has been completely towards the public, the network in daily life is more and more widely used, but at the same time, the potential network security problems are also more and more serious. Some sophisticated computer people in order to make money, crack other personal users or company information, a variety of network attacks one after another. Cyber attack has become an extremely feared existence for ordinary people because of its wide range of attacks, strong attack force and obvious hiding effect, which seriously threatens the security of personal information network. If attacked by this kind of attack, the loss borne by each person or company is immeasurable. In order to maintain network security, the defense system is also improving day by day, and finally presents software. This paper mainly makes a detailed understanding of the border attack and defense system, and analyzes the main reasons and inevitability of the software of the border attack and defense system.
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BERCHE, BERTRAND, CHRISTIAN VON FERBER, TARAS HOLOVATCH, and YURIJ HOLOVATCH. "TRANSPORTATION NETWORK STABILITY: A CASE STUDY OF CITY TRANSIT." Advances in Complex Systems 15, supp01 (June 2012): 1250063. http://dx.doi.org/10.1142/s0219525912500634.
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The goals of this paper are to present criteria, that allow to a priori quantify the attack stability of real world correlated networks of finite size and to check how these criteria correspond to analytic results available for infinite uncorrelated networks. As a case study, we consider public transportation networks (PTN) of several major cities of the world. To analyze their resilience against attacks, either the network nodes or edges are removed in specific sequences (attack scenarios). During each scenario the size S(c) of the largest remaining network component is observed as function of the removed share c of nodes or edges. To quantify the PTN stability with respect to different attack scenarios we use the area below the curve described by S(c) for c ∈ [0, 1] recently introduced (Schneider, C. M. et al. [PNAS 108 (2011) 3838]) as a numerical measure of network robustness. This measure captures the network reaction over the whole attack sequence. We present results of the analysis of PTN stability against node and link-targeted attacks.
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Al-Rushdan, Huthifh, Mohammad Shurman, and Sharhabeel Alnabelsi. "On Detection and Prevention of Zero-Day Attack Using Cuckoo Sandbox in Software-Defined Networks." International Arab Journal of Information Technology 17, no. 4A (July 31, 2020): 662–70. http://dx.doi.org/10.34028/iajit/17/4a/11.
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Networks attacker may identify the network vulnerability within less than one day; this kind of attack is known as zero-day attack. This undiscovered vulnerability by vendors empowers the attacker to affect or damage the network operation, because vendors have less than one day to fix this new exposed vulnerability. The existing defense mechanisms against the zero-day attacks focus on the prevention effort, in which unknown or new vulnerabilities typically cannot be detected. To the best of our knowledge the protection mechanism against zero-day attack is not widely investigated for Software-Defined Networks (SDNs). Thus, in this work we are motivated to develop a new zero-day attack detection and prevention mechanism for SDNs by modifying Cuckoo sandbox tool. The mechanism is implemented and tested under UNIX system. The experiments results show that our proposed mechanism successfully stops the zero-day malwares by isolating the infected clients, in order to prevent the malwares from spreading to other clients. Moreover, results show the effectiveness of our mechanism in terms of detection accuracy and response time
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Li, Yunpeng, and Xi Li. "Research on Multi-Target Network Security Assessment with Attack Graph Expert System Model." Scientific Programming 2021 (May 7, 2021): 1–11. http://dx.doi.org/10.1155/2021/9921731.
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With the rapid development of the Internet, network attacks often occur, and network security is widely concerned. Searching for practical security risk assessment methods is a research hotspot in the field of network security. Network attack graph model is an active detection technology for the attack path. From the perspective of the attacker, it simulated the whole network attack scenario and then presented the dependency among the vulnerabilities in the target network in the way of directed graph. It is an effective tool for analyzing network vulnerability. This paper describes in detail the common methods and tools of network security assessment and analyzes the construction of theoretical model of attack graph, the optimization technology of attack graph, and the research status of qualitative and quantitative analysis technology of attack graph in network security assessment. The attack graph generated in the face of large-scale network is too complex to find the key vulnerability nodes accurately and quickly. Optimizing the attack graph and solving the key attack set can help the security manager better understand the security state of the nodes in the network system, so as to strengthen the security defense ability and guarantee the security of the network system. For all kinds of loop phenomena of directed attribute attack graph, the general method of eliminating loop is given to get an acyclic attack graph. On the basis of acyclic attack graph, an optimization algorithm based on path complexity is proposed, which takes atomic attack distance and atomic weight into consideration, and on the basis of simplified attack graph, minimum-cost security reinforcement is carried out for the network environment. Based on the ant colony algorithm, the adaptive updating principle of changing pheromone and the local searching strategy of the adaptive genetic algorithm are proposed to improve the ant colony algorithm. The experimental results show that compared with the ant colony algorithm, the improved ant colony algorithm can speed up the process of solving the optimal solution. When the number of attack paths is large, the advantages of the improved ant colony algorithm in solving accuracy and late search speed are more obvious, and it is more suitable for large-scale networks.
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Rajeshwari, T., and C. Thangamani. "Attack Impact Discovery and Recovery with Dynamic Bayesian Networks." Asian Journal of Computer Science and Technology 8, S1 (February 5, 2019): 74–79. http://dx.doi.org/10.51983/ajcst-2019.8.s1.1953.
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The network attacks are discovered using the Intrusion Detection Systems (IDS). Anomaly, signature and compound attack detection schemes are employed to fetch malicious data traffic activities. The attack impact analysis operations are carried out to discover the malicious objects in the network. The system objects are contaminated with process injection or hijacking. The attack ramification model discovers the contaminated objects. The dependency networks are built to model the information flow over the objects in the network. The dependency network is a directed graph built to indicate the data communication over the objects. The attack ramification models are designed with intrusion root information. The attack ramifications are applied to identify the malicious objects and contaminated objects. The attack ramifications are discovered with the information flows from the attack sources. The Attack Ramification with Bayesian Network (ARBN) scheme discovers the attack impact without the knowledge of the intrusion root. The probabilistic reasoning approach is employed to analyze the object state for ramification process. The objects lifetime is divided into temporal slices to verify the object state changes. The system call traces and object slices are correlated to construct the Temporal Dependency Network (TDN). The Bayesian Network (BN) is constructed with the uncertain data communication activities extracted from the TDN. The attack impact is fetched with loopy belief propagation on the BN model. The network security system is built with attack impact analysis and recovery operations. Live traffic data analysis process is carried out with improved temporal slicing concepts. Attack Ramification and Recovery with Dynamic Bayesian Network (ARRDBN) is built to support attack impact analysis and recovery tasks. The unsupervised attack handling mechanism automatically discovers the feasible solution for the associated attacks.
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Alamsyah, Hendri, Riska, and Abdussalam Al Akbar. "Analisa Keamanan Jaringan Menggunakan Network Intrusion Detection and Prevention System." JOINTECS (Journal of Information Technology and Computer Science) 5, no. 1 (January 25, 2020): 17. http://dx.doi.org/10.31328/jointecs.v5i1.1240.
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Security is an important aspect to be considered in computer networks. This security system can be a detection and prevention of attacks that are being done by the attacker (intruders). The problem of attacks that occur in computer networks is that intruders can do port scanning, enter the system using open ports such as telnet, ftp and others.. The purpose of this study is the implementation of IDPS, can be from. To do network security from various attack threats, a system that can detect and prevent it directly is needed. The method that can be used is Intrusion Detection and Prevention System (NIDPS). NIDPS can exchange and block the attacks. This security system is collaborated with IP Tables. IP Tables is used to filter incoming data packets and drop packets of data that are indicated by attack. With the Intrusion Detection and Prevention system, it can detect attacks and prevent them by blocking data packets sent by intruders through port scanning, FTP attacks, and telnets.
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Satvir Kaur, Gureshpal Singh, Baljinder Singh. "Detection and Prevention of DDoS Attack Using Gateway Mechanism." International Journal on Recent and Innovation Trends in Computing and Communication 7, no. 2 (February 28, 2019): 21–26. http://dx.doi.org/10.17762/ijritcc.v7i2.5227.
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Denial of service is one of the most terrible attacks is the cloning attack of the node, where the attacker captures the knot and extracts its secret information, create replicas and enter them in the network field other malevolent behavior. To detect and mitigate this attack, several static-based detection schemes have been proposed. The detection algorithm based on the node location speed was proposed, to detect the attack of nodes clones in the wireless network. This algorithm reduces the costs of communication, routing, overloading the entire network and improving network performance.
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K*, Parvathy. "Wormhole Attacks in Wireless Sensor Networks (Wsn) & Internet of Things (IoT): A Review." International Journal of Recent Technology and Engineering 10, no. 1 (May 30, 2021): 199–203. http://dx.doi.org/10.35940/ijrte.a5873.0510121.
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In the current world people are using the sensing networks called IoT and WSN as the subset of IoT in various applications. The employment of these sensor networks is rapidly increasing. Due to the longer usage of these sensor networks security issues are eventually happening and has the possibility of developing the attacks in the network. In this review, focuses on wormhole attacks in wireless sensor network (WSN) and Internet of Things (IoT) creating a tunnels i.e., wormhole link in between source and the destination node in the network. The classification of wormhole attack in both WSN and IoT are presented based on the mode of attacker. The detection mechanisms of wormhole attack are specified in both WSN and IoT. It hypothesizes the detection strength is more in IoT than the WSN based on the analysis, the parameters of the detection algorithm that the WSN is about 20% while in IoT is 70%.
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Dhamodharan, Udaya Suriya Raj Kumar, and Rajamani Vayanaperumal. "Detecting and Preventing Sybil Attacks in Wireless Sensor Networks Using Message Authentication and Passing Method." Scientific World Journal 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/841267.
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Wireless sensor networks are highly indispensable for securing network protection. Highly critical attacks of various kinds have been documented in wireless sensor network till now by many researchers. The Sybil attack is a massive destructive attack against the sensor network where numerous genuine identities with forged identities are used for getting an illegal entry into a network. Discerning the Sybil attack, sinkhole, and wormhole attack while multicasting is a tremendous job in wireless sensor network. Basically a Sybil attack means a node which pretends its identity to other nodes. Communication to an illegal node results in data loss and becomes dangerous in the network. The existing method Random Password Comparison has only a scheme which just verifies the node identities by analyzing the neighbors. A survey was done on a Sybil attack with the objective of resolving this problem. The survey has proposed a combined CAM-PVM (compare and match-position verification method) with MAP (message authentication and passing) for detecting, eliminating, and eventually preventing the entry of Sybil nodes in the network. We propose a scheme of assuring security for wireless sensor network, to deal with attacks of these kinds in unicasting and multicasting.
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Yang, Yong, Kaijun Xu, and Honghui Xiang. "Analysis on Chinese Airline Network Invulnerability." Journal of Systems Science and Information 7, no. 4 (September 25, 2019): 359–72. http://dx.doi.org/10.21078/jssi-2019-359-14.
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Abstract Air transportation systems are often subject to failures or attacks induced by unexpected abominable weather or temporal airspace occupation, while complex networks have been springing up as a convenient yet efficient tool to represent and analyze various realistic complex systems such as realistic airline system. In terms of Chinese airline network formed during the spring festival timespan, structural empirical research and invulnerability simulation analysis against various deliberate attack strategies were made using complex network theory, where nodes and edges denotes domestic airports and direct flights between them respectively. The analysis results indicate: The presented airline network is a small net-work with scale-free characteristics, and correlation shows remarkable hierarchical structure and obvious assortative characteristics; The network shows obvious invulnerability under deliberate node attack, while shows partly robustness under edge attack even with obvious attack effects against various attack strategies.
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Ancy Breen, W., S. Durga Devi, E. Sushmitha, and V. Suveetha. "Reducing the Effectiveness of Gray-Hole Attack in Manet." International Journal of Engineering & Technology 7, no. 3.34 (September 1, 2018): 305. http://dx.doi.org/10.14419/ijet.v7i3.34.19213.
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MANET is the mobile ad-hoc network. Security is very important especially when transmitting the data packets from one node to another. MANET is constructed by grouping mobile wireless nodes with no fixed infrastructure. In order to forward the packets, all the nodes in the network must cooperate with each other, so that the nodes beyond the radio ranges can communicate. Each node acts as a router and MANET is infrastructure-less networks. Hence, MANET is open to more security attacks such as Gray-hole attack, Black-hole attack and worm-hole attack. Due to the dynamism in network topology, MANETS are highly vulnerable and are prone to malicious attack. Security issue is highly challenging in MANET. Understanding the different form of possible attacks and providing good security solutions is important for secure data transmission between nodes. The most dangerous attack among these attacks is Gray-hole attack. In this paper, it proposed a method for reducing the Gray-hole attack. Our proposed algorithm MAODV identifies the malicious node before the data transmission process and it greatly reduces the dropping of data packets.
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Li, Muhai, and Ming Li. "An Adaptive Approach for Defending against DDoS Attacks." Mathematical Problems in Engineering 2010 (2010): 1–15. http://dx.doi.org/10.1155/2010/570940.
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In various network attacks, the Distributed Denial-of-Service (DDoS) attack is a severe threat. In order to deal with this kind of attack in time, it is necessary to establish a special type of defense system to change strategy dynamically against attacks. In this paper, we introduce an adaptive approach, which is used for defending against DDoS attacks, based on normal traffic analysis. The approach can check DDoS attacks and adaptively adjust its configurations according to the network condition and attack severity. In order to insure the common users to visit the victim server that is being attacked, we provide a nonlinear traffic control formula for the system. Our simulation test indicates that the nonlinear control approach can prevent the malicious attack packets effectively while making legitimate traffic flows arrive at the victim.
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Feng, Xinzhi, Yang Yang, Xiaozhong Qi, Chunming Xu, and Ze Ji. "Output Feedback NCS of DoS Attacks Triggered by Double-Ended Events." Security and Communication Networks 2021 (February 10, 2021): 1–14. http://dx.doi.org/10.1155/2021/6643034.
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In recent years, the research of the network control system under the event triggering mechanism subjected to network attacks has attracted foreign and domestic scholars’ wide attention. Among all kinds of network attacks, denial-of-service (DoS) attack is considered the most likely to impact the performance of NCS significantly. The existing results on event triggering do not assess the occurrence of DoS attacks and controller changes, which will reduce the control performance of the addressed system. Aiming at the network control system attacked by DoS, this paper combines double-ended elastic event trigger control, DoS attack, and quantitative feedback control to study the stability of NCS with quantitative feedback of DoS attack triggered by a double-ended elastic event. Simulation examples show that this method can meet the requirements of control performance and counteract the known periodic DoS attacks, which save limited resources and improve the system’s antijamming ability.
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Stiawan, Deris, Mohd Yazid Idris, Reza Firsandaya Malik, Siti Nurmaini, Nizar Alsharif, and Rahmat Budiarto. "Investigating Brute Force Attack Patterns in IoT Network." Journal of Electrical and Computer Engineering 2019 (April 1, 2019): 1–13. http://dx.doi.org/10.1155/2019/4568368.
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Internet of Things (IoT) devices may transfer data to the gateway/application server through File Transfer Protocol (FTP) transaction. Unfortunately, in terms of security, the FTP server at a gateway or data sink very often is improperly set up. At the same time, password matching/theft holding is among the popular attacks as the intruders attack the IoT network. Thus, this paper attempts to provide an insight of this type of attack with the main aim of coming up with attack patterns that may help the IoT system administrator to analyze any similar attacks. This paper investigates brute force attack (BFA) on the FTP server of the IoT network by using a time-sensitive statistical relationship approach and visualizing the attack patterns that identify its configurations. The investigation focuses on attacks launched from the internal network, due to the assumption that the IoT network has already installed a firewall. An insider/internal attack launched from an internal network endangers more the entire IoT security system. The experiments use the IoT network testbed that mimic the internal attack scenario with three major goals: (i) to provide a topological description on how an insider attack occurs; (ii) to achieve attack pattern extraction from raw sniffed data; and (iii) to establish attack pattern identification as a parameter to visualize real-time attacks. Experimental results validate the investigation.
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Adhana, Finandito, and I. Ketut Gede Suhartana. "Deteksi Serangan Denial of Service di Situs Web dengan Wireshark Menggunakan Metode IDS Berbasis Anomali." JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) 8, no. 4 (February 4, 2020): 375. http://dx.doi.org/10.24843/jlk.2020.v08.i04.p02.
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Denial of Service (DoS) attacks are increasingly dangerous. This DoS attack works by sending data packets continuously so that the target being attacked cannot be operated anymore. DoS attacks attack the most websites, thus making the website inaccessible. An anomaly based intrusion detection system (IDS) is a method used to detect suspicious activity in a system or network on the basis of anomaly pattern arising from such interference. Wireshark is software used to analyze network traffic packets that have various kinds of tools for network professionals.
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., Sonika, Sandeep Kumar Arora, and Mahedi Masud. "Review on Security Based Vehicular Ad-Hoc Network." International Journal of Engineering & Technology 7, no. 3.8 (July 7, 2018): 125. http://dx.doi.org/10.14419/ijet.v7i3.8.16846.
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VANET a vehicular ad-hoc network provides the security to vehicles. To provide security in VANET, we are using Elliptical curve cryptography. In this paper we are going to discuss various techniques of cryptography, the techniques such are Advanced Encryption Standard, Data Encryption Standard, and Triple Data Encryption Standard. These techniques are part of symmetric and asymmetric cryptography. In addition to this there are some attacks which we are discussing in this paper like, masquerade attack, replay attack, insider attack, mutual authentication attack, and parallel session attack. These attacks are on different layer. At the end we are comparing these attacks with each other and compare their quality of services.
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Sharma, Vishal, Kyungroul Lee, Soonhyun Kwon, Jiyoon Kim, Hyungjoon Park, Kangbin Yim, and Sun-Young Lee. "A Consensus Framework for Reliability and Mitigation of Zero-Day Attacks in IoT." Security and Communication Networks 2017 (2017): 1–24. http://dx.doi.org/10.1155/2017/4749085.
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“Internet of Things” (IoT) bridges the communication barrier between the computing entities by forming a network between them. With a common solution for control and management of IoT devices, these networks are prone to all types of computing threats. Such networks may experience threats which are launched by exploitation of vulnerabilities that are left unhandled during the testing phases. These are often termed as “zero-day” vulnerabilities, and their conversion into a network attack is named as “zero-day” attack. These attacks can affect the IoT devices by exploiting the defense perimeter of the network. The existing solutions are capable of detecting such attacks but do not facilitate communication, which affects the performance of the network. In this paper, a consensus framework is proposed for mitigation of zero-day attacks in IoT networks. The proposed approach uses context behavior of IoT devices as a detection mechanism followed by alert message protocol and critical data sharing protocol for reliable communication during attack mitigation. The numerical analysis suggests that the proposed approach can serve the purpose of detection and elimination of zero-day attacks in IoT network without compromising its performance.
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Fan, Cong, Nitheesh Murugan Kaliyamurthy, Shi Chen, He Jiang, Yiwen Zhou, and Carlene Campbell. "Detection of DDoS Attacks in Software Defined Networking Using Entropy." Applied Sciences 12, no. 1 (December 31, 2021): 370. http://dx.doi.org/10.3390/app12010370.
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Software Defined Networking (SDN) is one of the most commonly used network architectures in recent years. With the substantial increase in the number of Internet users, network security threats appear more frequently, which brings more concerns to SDN. Distributed denial of Service (DDoS) attacks are one of the most dangerous and frequent attacks in software defined networks. The traditional attack detection method using entropy has some defects such as slow attack detection and poor detection effect. In order to solve this problem, this paper proposed a method of fusion entropy, which detects attacks by measuring the randomness of network events. This method has the advantages of fast attack detection speed and obvious decrease in entropy value. The complementarity of information entropy and log energy entropy is effectively utilized. The experimental results show that the entropy value of the attack scenarios 91.25% lower than normal scenarios, which has greater advantages and significance compared with other attack detection methods.
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Kumar Baitha, Anuj, and Prof Smitha Vinod. "Session Hijacking and Prevention Technique." International Journal of Engineering & Technology 7, no. 2.6 (March 11, 2018): 193. http://dx.doi.org/10.14419/ijet.v7i2.6.10566.
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Session Hijacking is an attack which is basically used to gain the unauthorized access between an authorized session connections. This is usually done to attack the social network website and banking websites in order to gain the access over the valid session as well as over the website too. These attacks are one of the commonly experienced cyber threats in today’s network. Most of the websites and networks are vulnerable from this kind of attack. For providing the protection I have given the multiple ways to protecting from this session hijacking attack. I have especially focused on one of the major attacks in this session hijacking attack SSL Strip attack which play very vital role in this kind of attack. Sometimes this session hijacking attack is also known as the Man in the Middle attack (MIMA).In this paper, I have covered many security mechanisms to stay away and protect you and the network. This session hijacking attack is very dangers for the security perspective. Even it can steal all users’ most sensitive data. This can create a big loss for the users financially. From all these types of attack, I have proposed many mechanisms to help the users to stay away from the attack. The main objective of this paper is to give detail information of session hijacking and countermeasure from session hijacking attacks.
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Asabere, Nana Yaw, Elikem Fiamavle, Joseph Agyiri, Wisdom Kwawu Torgby, Joseph Eyram Dzata, and Nina Pearl Doe. "SARCP." International Journal of Decision Support System Technology 14, no. 1 (January 2022): 1–21. http://dx.doi.org/10.4018/ijdsst.286691.
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In the domain of cyber security, the defence mechanisms of networks has traditionally been placed in a reactionary role. Cyber security professionals are therefore disadvantaged in a cyber-attack situation due to the fact that it is vital that they maneuver such attacks before the network is totally compromised. In this paper, we utilize the Betweenness Centrality network measure (social property) to discover possible cyber-attack paths and then employ computation of similar personality of nodes/users to generate predictions about possible attacks within the network. Our method proposes a social recommender algorithm called socially-aware recommendation of cyber-attack paths (SARCP), as an attack predictor in the cyber security defence domain. In a social network, SARCP exploits and delivers all possible paths which can result in cyber-attacks. Using a real-world dataset and relevant evaluation metrics, experimental results in the paper show that our proposed method is favorable and effective.
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BAO, ZHE-JING, WEN-JUN YAN, and CHUANG-XIN GUO. "RISK ASSESSMENT OF ATTACK-INDUCED CASCADE IN COMPLEX NETWORKS." International Journal of Modern Physics C 22, no. 08 (August 2011): 765–73. http://dx.doi.org/10.1142/s0129183111016579.
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For the complex networks, including scale-free, small-world, local-world and random networks, the global quantitative evaluation of attack-induced cascade is investigated in this paper by introducing the risk assessment, which integrates the probability of occurrence with the damage size of attacks on nodes. It is discovered by simulations, among the several kinds of networks, that the small-world network has the largest risk assessment of attack-induced cascade; the risk assessment of three other networks are all very low and the most protection against attack should be given to the small-world network accordingly. Furthermore, the percentage of the most fragile nodes in the scale-free network is very low, compared with that in the small-world network.