Relevant bibliographies by topics / Byzantines Attack

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Academic literature on the topic 'Byzantines Attack'

Author: Grafiati
Published: 14 March 2023

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Journal articles on the topic "Byzantines Attack"

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Böhm, Marcin. "Constantine X Doukas (1059–1067) versus Uzes – about the Nomads on Boats on the Danube in 1064." Studia Ceranea 11 (December 30, 2021): 39–49. http://dx.doi.org/10.18778/2084-140x.11.02.

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The reign of the Doukas dynasty in 1059–1078 was a time when new threats to the Byzantine Empire emerge in Europe and Asia. One of them was the increased activity of Turkmen who were penetrating the lands belonging to the Byzantines. A manifestation of these threats was visible during the rule of Constantine X Doukas (1059–1067) in 1064. We have there an invasion of the tribe of Uzes, who crossed the Danube. They ventured so far, as the vicinity of Thessalonica and the province of Hellas, plundering everything in their path. Their actions surprised the defense of the Byzantines. This attack on the empire was related to their crossing of the Danube, about which Michael Attaliates and Skylitzes Continuatus provides us with interesting information. The main aim of this paper therefore will be related to issues linked to the types of vessels used by Uzes to cross this river, as well as an attempt to assess their boatbuilding skills.
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Veselinović, Ivana. "The role of the despotess Irene Kantakouzene in the political life of the Serbian Despotate." Zbornik radova Filozofskog fakulteta u Pristini 52, no. 2 (2022): 177–90. http://dx.doi.org/10.5937/zrffp52-36443.

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Despotess Irene was considered the second person of the Serbian despotate in Serbian historiography. Owing to Serbian and Byzantine sources that mention her actions, this paper attempts to answer the question of her joint rule with despot Đurađ Branković in Serbian state, as an independent political factor. The first example of this is Efsigmen Charter from 1429, which the despot issued together with his wife. In addition, the miniature on Irene's charter shows her with a sceptre in her hand, a royal sign, although her and Đurađ's son had already been nominated for the heir to the throne, as indicated by the red shoes. Her activity is seen in the presence of a large number of Byzantines in Serbia, and then in the administration of the Serbian state. Of the Byzantines who lived in Serbia, the brother of the despotess Irene, Toma Kantakouzene was very important. He became the commander of the Serbian army, which was very unusual for the Middle Ages in Serbia. In 1435, during Đurađ's visit to Požun, Irene ruled the country as we know, based on the Dubrovnik mission she received. In addition, the despotess was a member of the state council, and most likely the court council. Mavro Orbini left a note on Irene's role in the diplomatic marriage between Mara Branković and Sultan Murad II, which Serbia used as means of preventing the Ottoman attack on the country. The fact that most points to Irene's active political role is the question of the successor of the despot Đurađ. Mavro Orbini and Michael Kritovoulos wrote that Đurađ Branković appointed his wife to rule after his death, which was certainly related to the division in the family due to the deprivation of the throne of the blinded Grgur. Thus, Irene would be a person around whom the family would gather and reconcile, and who would rule the country. Her sudden death and the transfer of part of the ruling family to the Ottoman territory subsequently confirmed her right to power and the division that existed between the Branković family over the ruler and the country's foreign policy.
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Yang, Xiong, Wang, and Zhang. "Analysis of Byzantine Attacks for Target Tracking in Wireless Sensor Networks." Sensors 19, no. 15 (August 5, 2019): 3436. http://dx.doi.org/10.3390/s19153436.

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Herein, the problem of target tracking in wireless sensor networks (WSNs) is investigated in the presence of Byzantine attacks. More specifically, we analyze the impact of Byzantine attacks on the performance of a tracking system. First, under the condition of jointly estimating the target state and the attack parameters, the posterior Cramer–Rao lower bound (PCRLB) is calculated. Then, from the perspective of attackers, we define the optimal Byzantine attack and theoretically find a way to achieve such an attack with minimal cost. When the attacked nodes are correctly identified by the fusion center (FC), we further define the suboptimal Byzantine attack and also find a way to realize such an attack. Finally, in order to alleviate the negative impact of attackers on the system performance, a modified sampling importance resampling (SIR) filter is proposed. Simulation results show that the tracking results of the modified SIR filter can be close to the true trajectory of the moving target. In addition, when the quantization level increases, both the security performance and the estimation performance of the tracking system are improved.
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Wang, Xiaoxue, Hongqi Zhang, Anas Bilal, Haixia Long, and Xiaowen Liu. "WGM-dSAGA: Federated Learning Strategies with Byzantine Robustness Based on Weighted Geometric Median." Electronics 12, no. 5 (March 1, 2023): 1190. http://dx.doi.org/10.3390/electronics12051190.

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Federated learning techniques accomplish federated modeling and share global models without sharing data. Federated learning offers a good answer to complex data and privacy security issues. Although there are many ways to target federated learning, Byzantine attacks are the ones we concentrate on. Byzantine attacks primarily impede learning by tampering with the local model parameters provided by a client to the master node throughout the federation learning process, leading to a final global model that diverges from the optimal solution. To address this problem, we combine aggregation rules with Byzantine robustness using a gradient descent optimization algorithm based on variance reduction. We propose a WGM-dSAGA method with Byzantine robustness, called weighted geometric median-based distributed SAGA. We replace the original mean aggregation strategy in the distributed SAGA with a robust aggregation rule based on weighted geometric median. When less than half of the clients experience Byzantine attacks, the experimental results demonstrate that our proposed WGM-dSAGA approach is highly robust to different Byzantine attacks. Our proposed WGM-dSAGA algorithm provides the optimal gap and variance under a Byzantine attack scenario.
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Salama, Hatem Mahmoud, Mohamed Zaki Abd El Mageed, Gouda Ismail Mohamed Salama, and Khaled Mahmoud Badran. "CSMCSM." International Journal of Information Security and Privacy 15, no. 1 (January 2021): 44–64. http://dx.doi.org/10.4018/ijisp.2021010103.

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Many MANET research works are based on the popular informal definition that MANET is a wireless ad-hoc network that has neither infrastructure nor backbone and every network node is autonomous and moves depending on its mobility. Unfortunately, this definition pays no attention to the network servers that are essential in core-based, mission-critical, and military MANETs. In core-based MANETs, external intrusion detection systems (IDS) cannot detect internal Byzantine attacks; in addition, internal Byzantine fault tolerant (BFT) systems are unqualified to detect typical external wireless attack. Therefore, there is a real need to combine both internal and external mobile ad-hoc network (MANET) ID systems. Here, CSMCSM is presented as a two-level client server model for comprehensive security in MANETs that integrates internal and external attack detectors in one device. The internal component is based on a BFT consensus algorithm while the external component employs decision tree to classify the MANET attacks.
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Wang, Jingyao, Xingming Deng, Jinghua Guo, and Zeqin Zeng. "Resilient Consensus Control for Multi-Agent Systems: A Comparative Survey." Sensors 23, no. 6 (March 7, 2023): 2904. http://dx.doi.org/10.3390/s23062904.

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Due to the openness of communication network and the complexity of system structures, multi-agent systems are vulnerable to malicious network attacks, which can cause intense instability to these systems. This article provides a survey of state-of-the-art results of network attacks on multi-agent systems. Recent advances on three types of attacks, i.e., those on DoS attacks, spoofing attacks and Byzantine attacks, the three main network attacks, are reviewed. Their attack mechanisms are introduced, and the attack model and the resilient consensus control structure are discussed, respectively, in detail, in terms of the theoretical innovation, the critical limitations and the change of the application. Moreover, some of the existing results along this line are given in a tutorial-like fashion. In the end, some challenges and open issues are indicated to guide future development directions of the resilient consensus of multi-agent system under network attacks.
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Amir, Y., B. Coan, J. Kirsch, and J. Lane. "Prime: Byzantine Replication under Attack." IEEE Transactions on Dependable and Secure Computing 8, no. 4 (July 2011): 564–77. http://dx.doi.org/10.1109/tdsc.2010.70.

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Wan, Fangyi, Ting Ma, Yi Hua, Bin Liao, and Xinlin Qing. "Secure distributed estimation under Byzantine attack and manipulation attack." Engineering Applications of Artificial Intelligence 116 (November 2022): 105384. http://dx.doi.org/10.1016/j.engappai.2022.105384.

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ABORISADE, D. O., A. S. SODIYA, A. A. ODUMOSU, O. Y. ALOWOSILE, and A. A. ADEDEJI. "A SURVIVABLE DISTRIBUTED DATABASE AGAINST BYZANTINE FAILURE." Journal of Natural Sciences Engineering and Technology 15, no. 2 (November 22, 2017): 61–72. http://dx.doi.org/10.51406/jnset.v15i2.1684.

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Distributed Database Systems have been very useful technologies in making a wide range of information available to users across the World. However, there are now growing security concerns, arising from the use of distributed systems, particularly the ones attached to critical systems. More than ever before, data in distributed databases are more susceptible to attacks, failures or accidents owing to advanced knowledge explosions in network and database technologies. The imperfection of the existing security mechanisms coupled with the heightened and growing concerns for intrusion, attack, compromise or even failure owing to Byzantine failure are also contributing factors. The importance of survivable distributed databases in the face of byzantine failure, to other emerging technologies is the motivation for this research. Furthermore, It has been observed that most of the existing works on distributed database only dwelled on maintaining data integrity and availability in the face of attack. There exist few on availability or survibability of distributed databases owing to internal factors such as internal sabotage or storage defects. In this paper, an architecture for entrenching survivability of Distributed Databases occasioned by Byzantine failures is proposed. The proposed architecture concept is based on re-creating data on failing database server based on a set threshold value.The proposed architecture is tested and found to be capable of improving probability of survivability in distributed database where it is implemented to 99.6% from 99.2%.
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Makani, Ruchi, and Busi V. Ramana Reddy. "Performance Evaluation of Cognitive Internet on Things Under Routing Attacks." International Journal of Sensors, Wireless Communications and Control 10, no. 1 (February 7, 2020): 15–24. http://dx.doi.org/10.2174/2210327909666181217122655.

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Background & Objective:: In past few years, Cognitive Radio (CR) paradigm has emerged as a promising and revolutionary solution to avoid problems of spectrum paucity and inefficiency in spectrum usage. Efficiently utilization of the spectrum offers high network performance. CRs are proficient to identify and adopt the unused spectrum in order to allow secondary users to occupy it without interfering the primary user’s activity. Cognitive Internet on Things (CIoT) is an integration of several technologies and communication solutions which can be effectively realized as Cognitive Radio Adhoc Networks (CRAHN). In CRANH, on-demand routing protocols are the best suitable protocols due to their dynamic feature of available un-utilized channel/spectrum selection. Methods: Here, firstly, Ad-Hoc On-Demand Distance Vector (AODV) routing protocol has been modified and further evaluated to address route selection challenges in CIoT framework. Secondly, the effects on network performance under network layer routing attacks (i.e. blackhole attack, byzantine attack and flooding attacks) are evaluated. Conclusion: The simulations results demonstrate network performance increase with more channels and degrade differently under attacks.
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Dissertations / Theses on the topic "Byzantines Attack"

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Sironen, Erkki. "The late Roman and early Byzantine inscriptions of Athens and Attica : an edition with appendices on scripts, sepulchral formulae and occupations /." Helsinki : Hakapaino Oy, 1997. http://bibpurl.oclc.org/web/25751.

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Alam, Mohammad Rafiqul. "Detecting wormhole and Byzantine attacks in mobile ad hoc networks." Thesis, Curtin University, 2011. http://hdl.handle.net/20.500.11937/1701.

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The recent advancements in the wireless technology and their wide-spread utilization have made tremendous enhancements in productivity in the corporate and industrial sectors. However, these recent progresses have also introduced new security vulnerabilities. Since the wireless shared medium is completely exposed to outsiders, it is susceptible to attacks that could target any of the OSI layers in the network stack. For example, jamming of the physical layer, disruption of the medium access control (MAC) layer coordination packets, attacks against the routing infrastructure, targeted attacks on the transport protocol, or even attacks intended to disrupt specific applications. Unfortunately, the effects of applying the security techniques used in wired networks, such as access control and authentication, to wireless and mobile networks have been unsatisfactory due the unique features of such networks. As a result, achieving security goals for mobile ad hoc networks (MANET) has gained significant attention in recent years. Many critical applications of MANET, such as emergency rescue operations, military tactical communication, and business operations like mining and oil drilling platforms, require a friendly and cooperative environment.The aim of this study is to design detection mechanisms for traditional wormhole and Byzantine wormhole attacks by using the topological comparison and round trip time (RTT) measurements. The first step for detecting traditional wormhole attack is that an initiator of the detection process populates its one-hop neighbor list, and also calculates the average round trip time (RTTavg). Meanwhile, a list of suspected neighbors is generated on the basis of RTTavg and RTT. Then, topological information is exchanged between the initiator and all the suspected neighbors to detect the presence of a wormhole link.In this thesis, we also focus on detecting Byzantine wormhole attack in MANET. In the case of detecting such attacks, the initiator creates its one hop neighbor list and calculates the average RTTavg. The initiator also generates a suspected list of its three hop neighbors. In the next phase, the initiator exchanges topological information with all the one hop neighbors to detect the presence of any Byzantine wormhole tunnel. One of the major concerns for the topological comparison based approach is to give the initially suspected nodes a second chance to prove their reliability by exchanging topological information.We have implemented the detection algorithms in ad hoc on demand distance vector (AODV) and optimized link state routing (OLSR) routing protocols. Then, performance evaluation of the proposed detection mechanisms is conducted. We also compared our proposed detection methods with some of the existing detection methods by simulation. The results show that our schemes can achieve better detection performance.
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KALLAS, KASSEM. "A Game-Theoretic Approach for Adversarial Information Fusion in Distributed Sensor Networks." Doctoral thesis, Università di Siena, 2017. http://hdl.handle.net/11365/1005735.

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Every day we share our personal information through digital systems which are constantly exposed to threats. For this reason, security-oriented disciplines of signal processing have received increasing attention in the last decades: multimedia forensics, digital watermarking, biometrics, network monitoring, steganography and steganalysis are just a few examples. Even though each of these fields has its own peculiarities, they all have to deal with a common problem: the presence of one or more adversaries aiming at making the system fail. Adversarial Signal Processing lays the basis of a general theory that takes into account the impact that the presence of an adversary has on the design of effective signal processing tools. By focusing on the application side of Adversarial Signal Processing, namely adversarial information fusion in distributed sensor networks, and adopting a game-theoretic approach, this thesis contributes to the above mission by addressing four issues. First, we address decision fusion in distributed sensor networks by developing a novel soft isolation defense scheme that protects the network from adversaries, specifically, Byzantines. Second, we develop an optimum decision fusion strategy in the presence of Byzantines. In the next step, we propose a technique to reduce the complexity of the optimum fusion by relying on a novel nearly-optimum message passing algorithm based on factor graphs. Finally, we introduce a defense mechanism to protect decentralized networks running consensus algorithm against data falsification attacks.
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Tzavella, Elissavet. "Urban and rural landscape in early and middle Byzantine Attica (4th-12th c. AD)." Thesis, University of Birmingham, 2013. http://etheses.bham.ac.uk//id/eprint/4321/.

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The present study synthesiszes archaeological and historical evidence concerning Attica (Greece), the hinterland of Athens, in the Early and Middle Byzantine periods (4th-12th c.). Although the Byzantine monuments of Attica have been thoroughly studied, no coherent picture of how these relate to broader patterns of occupation and land usage has thus far been presented. In the main, the period under discussion is generally interpreted in three ways: Regarding Late Antiquity, research has often focused on the transition from paganism to Christianity, and to the characterisation of Attica as a ‘stronghold of paganism’. During the so-called ‘Dark-Ages’, Attica is most often presented as being ‘desolate’. Regarding the Middle Byzantine period, archaeological research is dominated by architectural and art-historical study of churches. The present study presents Attica within wider trends which took place in the Byzantine Empire, and which caused its transformation in terms of demography, settlement pattern, administration, road networks, economy, defense and ecclesiastical institutions. After a detailed catalogue and interpretation of all available archaeological material, Attica appears less ‘exceptional’ in Late Antiquity, less ‘desolate’ in the ‘Dark-Ages’, while in the Middle Byzantine period, emergence of a strong local elite matches the erection of monuments of high artistic quality.
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Wang, Qianlong. "Blockchain-Empowered Secure Machine Learning and Applications." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1625183576139299.

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Han, Kai. "Scheduling Distributed Real-Time Tasks in Unreliable and Untrustworthy Systems." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/26917.

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In this dissertation, we consider scheduling distributed soft real-time tasks in unreliable (e.g., those with arbitrary node and network failures) and untrustworthy systems (e.g., those with Byzantine node behaviors). We present a distributed real-time scheduling algorithm called Gamma. Gamma considers a distributed (i.e., multi-node) task model where tasks are subject to Time/Utility Function (or TUF) end-to-end time constraints, and the scheduling optimality criterion of maximizing the total accrued utility. The algorithm makes three novel contributions. First, Gamma uses gossip for reliably propagating task scheduling parameters and for discovering task execution nodes. Second, Gamma achieves distributed real-time mutual exclusion in unreliable environments. Third, the algorithm guards against potential disruption of message propagation due to Byzantine attacks using a mechanism called Launcher-Attacker-Infective-Susceptible-Immunized-Removed-Consumer (or LAISIRC). By doing so, the algorithm schedules tasks with probabilistic termination-time satisfactions, despite system unreliability and untrustworthiness. We analytically establish several timeliness and non-timeliness properties of the algorithm including probabilistic end-to-end task termination time satisfactions, optimality of message overheads, mutual exclusion guarantees, and the mathematical model of the LAISIRC mechanism. We conducted simulation-based experimental studies and compared Gamma with its competitors. Our experimental studies reveal that Gammaâ s scheduling algorithm accrues greater utility and satisfies a greater number of deadlines than do competitor algorithms (e.g., HVDF) by as much as 47% and 45%, respectively. LAISIRC is more tolerant to Byzantine attacks than competitor protocols (e.g., Path Verification) by obtaining as much as 28% higher correctness ratio. Gammaâ s mutual exclusion algorithm accrues greater utility than do competitor algorithms (e.g., EDF-Sigma) by as much as 25%. Further, we implemented the basic Gamma algorithm in the Emulab/ChronOS 250-node testbed, and measured the algorithmâ s performance. Our implementation measurements validate our theoretical analysis and the algorithm's effectiveness and robustness.
Ph. D.
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Chen, Ho-Chun, and 陳和均. "The Study of Byzantine Attack in Large Scale Wireless Sensor Networks." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/n2y87u.

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碩士
國立臺灣大學
電信工程學研究所
106
In this thesis, we study the problem of Byzantine attacks in large scale wireless sensor networks (WSNs). WSN is a critical technology in the future Internet of Things era, supporting various applications such as smart home, environmental monitoring, Internet of vehicles, etc. A WSN generally consists of some sensors and a fusion center (FC). Each sensor makes an observation about a phenomenon of interest, and transmits local message to the FC, who then makes a final decision based on those messages. Due to the exposed nature of the sensors and the characteristics of wireless channel, WSN is prone to be attacked and faulty. One of the attacks against WSN is called the Byzantine attack, which the attacker compromises some sensors and sends falsified messages to the FC. Unlike channel errors caused by noise or interference, Byzantine attack is targeted and may be more harmful to the system. It''s thus an important and challenging goal to design a robust system that is immune to the attack, and this is the purpose of our research. The effect of Byzantine attack has been studied a lot in recent years, however, many works formulate it as a simple hypothesis testing problem by assuming each sensor being independently compromised with probability alpha_t, where alpha_t is the fraction of Byzantine sensors. We call this model the i.i.d. mixture model since the local messages are i.i.d. to a mixture distribution. It''s easy to obtain the optimal error exponent in this problem formulation, however, we are not satisfied with the model since in practice it''s unlikely an attacker randomly attack the sensors each time. To fix this assumption, we introduce a parameter that indicates the indices of compromised sensors and formulate the Byzantine attack as a composite hypothesis testing problem. Using the idea of Hoeffding test in conventional composite hypothesis testing, we propose a "Hoeffding-type test''. The Hoeffding-type test depends only on the type of local messages, and achieves an error exponent which is the same as the optimal exponent in i.i.d. mixture model. We also show that it''s easy to generalize the Hoeffding-type test so that it becomes universal over all possible attack distributions. Since Hoeffding-type test only uses the type information, we further propose an "Order-aware Hoeffding-type test''. In the order-aware test, we perform joint detection of the indices parameter and the underlying hypothesis by brute-force search. Although the order-aware test seems to be using more information than the Hoeffding-type test, we show that they are equivalent in the asymptotic regime. The proposed detect algorithms can be applied in two kinds of defense scheme: 1. Direct Detect: FC has no information on the identities of Byzantine sensors and performs detection with all local messages 2. Clustering and Detect: FC will first identifies the Byzantines and clusters the sensors into two groups through some side information. For each group, independent detection is performed then results from both groups are combined using 0-AND rule. We show that the Clustering Detect scheme performs better than Direct Detect scheme, and FC can''t be blinded unless all sensors are compromised. Finally, some numerical results are presented to compare the two defense scheme.
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(9154928), Aritra Mitra. "New Approaches to Distributed State Estimation, Inference and Learning with Extensions to Byzantine-Resilience." Thesis, 2020.

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In this thesis, we focus on the problem of estimating an unknown quantity of interest, when the information required to do so is dispersed over a network of agents. In particular, each agent in the network receives sequential observations generated by the unknown quantity, and the collective goal of the network is to eventually learn this quantity by means of appropriately crafted information diffusion rules. The abstraction described above can be used to model a variety of problems ranging from environmental monitoring of a dynamical process using autonomous robot teams, to statistical inference using a network of processors, to social learning in groups of individuals. The limited information content of each agent, coupled with dynamically changing networks, the possibility of adversarial attacks, and constraints imposed by the communication channels, introduce various unique challenges in addressing such problems. We contribute towards systematically resolving some of these challenges.

In the first part of this thesis, we focus on tracking the state of a dynamical process, and develop a distributed observer for the most general class of LTI systems, linear measurement models, and time-invariant graphs. To do so, we introduce the notion of a multi-sensor observable decomposition - a generalization of the Kalman observable canonical decomposition for a single sensor. We then consider a scenario where certain agents in the network are compromised based on the classical Byzantine adversary model. For this worst-case adversarial setting, we identify certain fundamental necessary conditions that are a blend of system- and network-theoretic requirements. We then develop an attack-resilient, provably-correct, fully distributed state estimation algorithm. Finally, by drawing connections to the concept of age-of-information for characterizing information freshness, we show how our framework can be extended to handle a broad class of time-varying graphs. Notably, in each of the cases above, our proposed algorithms guarantee exponential convergence at any desired convergence rate.

In the second part of the thesis, we turn our attention to the problem of distributed hypothesis testing/inference, where each agent receives a stream of stochastic signals generated by an unknown static state that belongs to a finite set of hypotheses. To enable each agent to uniquely identify the true state, we develop a novel distributed learning rule that employs a min-protocol for data-aggregation, as opposed to the large body of existing techniques that rely on "belief-averaging". We establish consistency of our rule under minimal requirements on the observation model and the network structure, and prove that it guarantees exponentially fast convergence to the truth with probability 1. Most importantly, we establish that the learning rate of our algorithm is network-independent, and a strict improvement over all existing approaches. We also develop a simple variant of our learning algorithm that can account for misbehaving agents. As the final contribution of this work, we develop communication-efficient rules for distributed hypothesis testing. Specifically, we draw on ideas from event-triggered control to reduce the number of communication rounds, and employ an adaptive quantization scheme that guarantees exponentially fast learning almost surely, even when just 1 bit is used to encode each hypothesis.
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Tseng, Yi-Ying, and 曾奕穎. "Countering Byzantine Attacks in a Network with Random Linear Network Coding." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/88fyjp.

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碩士
國立東華大學
電機工程學系
100
Network coding is an elegant technique where, instead of simply relaying the packets of information they receive, the nodes of a network are allowed to combine \emph{several} packets together for transmission and this technique can be used to achieve the maximum possible information flow in a network. Recent implementations of network coding for wired and wireless environments have demonstrated its practical benefits, especially in multicast communication. Because communication in wireless environment is essentially multicast, network coding has highly attracted research attention in this field. Due to that one transmitting information is actually combination of multiple other information , network coding has variety of applications such as P2P, redundant data storage, switch and etc. However, this special characteristic also exposes network coding systems to a wide range of error attacks, especially Byzantine attacks. When some adversary nodes generate error data in the network with network coding, those erroneous information will be mixed at intermeidate nodes and thus corrupt all the information reaching a destination. In short, network coding will propagate errors. Recent research has shown that network coding can be combined with classical cryptography for secure communication, such as using concept of ECC (error correcting code) to perform end-to-end error correction or misbehavaior detection. Nevertheless, when it comes to Byzantine attacks, these results have limited effect. In fact, unless we find out those adversary nodes and isolate them, network coding may perform much worse than pure routing in the presence of malicious nodes. Our research develops a distributed hierarchical algorithm based on random linear network coding to locate malicious nodes.
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Cheng, Sheng-Hong, and 鄭勝鴻. "Defense and Detection of Sybil Attack Using Byzantine Agreement Algorithm in Mobile Ad Hoc Network." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/24pgmr.

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碩士
淡江大學
資訊工程學系碩士班
106
The topology of mobile ad hoc networks (MANET) is dynamic, can be quickly configured, and lacks features such as wireless APs and adapters. Due to these benefits, a MANET system is able to be applied to specific situations, such as search and rescue operations, military use or emergency operations. Based on the routing protocol, node connections provide information to each other and can jointly establish a complete transmission path independently. But security is a major issue in MANET systems. Because MANET system are open and perform on a non-centralized infrastructure, they lacks security considerations in routing protocols, which make MANET systems more difficult to secure than wired networks. Attacks are easily exploited by its weaknesses. In this study, we conducted further research on the most common Sybil Attack of MANET systems. The common Sybil attack may cause packet flow redirection and other extended effects. We used the simulation environment NS-3 Project to create a consensus-based practical Byzantine Fault Tolerance algorithm to explore solutions to the Sybil attack''s threat to free mobile networks. Ensuring that all the original network nodes that are vulnerable to tampering are protected can ensure the integrity of the data during transmission. We must demonstrate in the simulation experiment that this method can have an ideal performance in both network and security performance. The goal is to ensure that the general network has the security of the network form under the infrastructure without being compromised.
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Books on the topic "Byzantines Attack"

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Los dorismos del Corpus Bucolicorum. Amsterdam: A.M. Hakkert, 1990.

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Book chapters on the topic "Byzantines Attack"

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Hancock, James F. "Spice trade in the dark ages of Europe." In Spices, scents and silk: catalysts of world trade, 146–56. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249743.0012.

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Abstract This chapter narrates the state of world trade during the fall of the Western Roman Empire under waves of Germanic tribe movements during the 'Völkerwanderung' or Migration Period. It contains nine subchapters that are about the collapse of the Western Roman Empire, spice use in Europe during the dark ages, the level of western trade in the early medieval age, Mediterranean trade in the early medieval period, early medieval trade in Europe, the Radhanites: medieval tycoons, the rise of the Gotlanders, Rus' trade with the Muslims and Byzantines through Khazaria, and lastly, Rus' attacks on the Islamic and Byzantine Worlds.
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Fiat, Amos, Jared Saia, and Maxwell Young. "Making Chord Robust to Byzantine Attacks." In Algorithms – ESA 2005, 803–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11561071_71.

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Pooja, A. Saraswathi, Rampa Theresa, Satya Govind, and Anuja Aloy Mary. "Detection of Byzantine Attack in Cognitive Radio Network." In Advances in Intelligent Systems and Computing, 459–68. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5029-4_37.

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He, Xiaofan, and Huaiyu Dai. "Case Study II: HMM-Based Byzantine Attack Detection." In SpringerBriefs in Electrical and Computer Engineering, 51–62. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75868-8_5.

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He, Xiaofan, and Huaiyu Dai. "Case Study III: CFC-Based Byzantine Attack Detection." In SpringerBriefs in Electrical and Computer Engineering, 63–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75868-8_6.

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Zhang, Linyuan, Guoru Ding, and Qihui Wu. "Byzantine Attack and Defense in Wireless Data Fusion." In Encyclopedia of Wireless Networks, 147–50. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-78262-1_301.

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Zhang, Linyuan, Guoru Ding, and Qihui Wu. "Byzantine Attack and Defense in Wireless Data Fusion." In Encyclopedia of Wireless Networks, 1–4. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-32903-1_301-1.

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Abrardo, Andrea, Mauro Barni, Kassem Kallas, and Benedetta Tondi. "Security Attacks and Defenses in Distributed Sensor Networks." In Information Fusion in Distributed Sensor Networks with Byzantines, 29–43. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-32-9001-3_3.

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Bing, Yuchen, Long Wang, and Zesheng Chen. "A Spectrum Sensing Method for UAV Swarms Under Byzantine Attack." In Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021), 1748–58. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9492-9_172.

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Singla, Gagan, and Pallavi Kaliyar. "A Secure Routing Protocol for MANETs Against Byzantine Attacks." In Lecture Notes in Electrical Engineering, 571–78. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6154-8_56.

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Conference papers on the topic "Byzantines Attack"

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Stanev, Kamen. "THE FIFTH SLAVIC SIEGE OF THESSALONIKI." In THE PATH OF CYRIL AND METHODIUS – SPATIAL AND CULTURAL HISTORICAL DIMENSIONS. Cyrillo-Methodian Research Centre – Bulgarian Academy of Sciences, 2023. http://dx.doi.org/10.59076/2815-3855.2023.33.16.

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The fifth Slavic siege of Thessaloniki took place in 676 – 678 and it shows that the relationship between the Slavic tribes and Byzantium, as well as between the Slavic tribes themselves, is much more complex than is traditionally presented in the historiography. The hostile actions of the slavs against the city can be divided into two periods. In the first stage participated the Rhynchines, Strymonites and Sagudates. During this period, in Thessaloniki, as Byzantine allies, there was also a Slavic squad, without specifying which tribe it was from. The fact that the Dragovites, who lived west of the city during this period, are not among the tribes fighting with Thessaloniki shows that perhaps it is from them the slavs in question, allies of the Byzanatines.This is also the reason why the first two years there is no real siege, only separate attacks on land and sea. At one point, the Slavic squad, which was helping Thessaloniki, turned against the Byzantines. This is the moment when the Draguvites appear among the tribes invading the city and at the same time move to a classic siege using siege machines. After the failure of the siege, the Draguvites fell into some form of dependence on the empire, and over the next two centuries there was no evidence of hostilities between them and the Byzantines. In contrast, the Strymonites and Rhynchines continued their raids for another decade.
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Amir, Yair, Brian Coan, Jonathan Kirsch, and John Lane. "Byzantine replication under attack." In 2008 IEEE International Conference on Dependable Systems and Networks With FTCS and DCC (DSN). IEEE, 2008. http://dx.doi.org/10.1109/dsn.2008.4630088.

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Sun, Ziteng, Chuang Zhang, and Pingyi Fan. "Optimal Byzantine Attack and Byzantine Identification in Distributed Sensor Networks." In 2016 IEEE Globecom Workshops (GC Wkshps). IEEE, 2016. http://dx.doi.org/10.1109/glocomw.2016.7848991.

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Wan, Wei, Shengshan Hu, jianrong Lu, Leo Yu Zhang, Hai Jin, and Yuanyuan He. "Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/106.

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Federated learning (FL) enables multiple clients to collaboratively train an accurate global model while protecting clients' data privacy. However, FL is susceptible to Byzantine attacks from malicious participants. Although the problem has gained significant attention, existing defenses have several flaws: the server irrationally chooses malicious clients for aggregation even after they have been detected in previous rounds; the defenses perform ineffectively against sybil attacks or in the heterogeneous data setting. To overcome these issues, we propose MAB-RFL, a new method for robust aggregation in FL. By modelling the client selection as an extended multi-armed bandit (MAB) problem, we propose an adaptive client selection strategy to choose honest clients that are more likely to contribute high-quality updates. We then propose two approaches to identify malicious updates from sybil and non-sybil attacks, based on which rewards for each client selection decision can be accurately evaluated to discourage malicious behaviors. MAB-RFL achieves a satisfying balance between exploration and exploitation on the potential benign clients. Extensive experimental results show that MAB-RFL outperforms existing defenses in three attack scenarios under different percentages of attackers.
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Xia, Qi, Zeyi Tao, Zijiang Hao, and Qun Li. "FABA: An Algorithm for Fast Aggregation against Byzantine Attacks in Distributed Neural Networks." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/670.

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Many times, training a large scale deep learning neural network on a single machine becomes more and more difficult for a complex network model. Distributed training provides an efficient solution, but Byzantine attacks may occur on participating workers. They may be compromised or suffer from hardware failures. If they upload poisonous gradients, the training will become unstable or even converge to a saddle point. In this paper, we propose FABA, a Fast Aggregation algorithm against Byzantine Attacks, which removes the outliers in the uploaded gradients and obtains gradients that are close to the true gradients. We show the convergence of our algorithm. The experiments demonstrate that our algorithm can achieve similar performance to non-Byzantine case and higher efficiency as compared to previous algorithms.
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Ji, Jinlong, Xuhui Chen, Qianlong Wang, Lixing Yu, and Pan Li. "Learning to Learn Gradient Aggregation by Gradient Descent." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/363.

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In the big data era, distributed machine learning emerges as an important learning paradigm to mine large volumes of data by taking advantage of distributed computing resources. In this work, motivated by learning to learn, we propose a meta-learning approach to coordinate the learning process in the master-slave type of distributed systems. Specifically, we utilize a recurrent neural network (RNN) in the parameter server (the master) to learn to aggregate the gradients from the workers (the slaves). We design a coordinatewise preprocessing and postprocessing method to make the neural network based aggregator more robust. Besides, to address the fault tolerance, especially the Byzantine attack, in distributed machine learning systems, we propose an RNN aggregator with additional loss information (ARNN) to improve the system resilience. We conduct extensive experiments to demonstrate the effectiveness of the RNN aggregator, and also show that it can be easily generalized and achieve remarkable performance when transferred to other distributed systems. Moreover, under majoritarian Byzantine attacks, the ARNN aggregator outperforms the Krum, the state-of-art fault tolerance aggregation method, by 43.14%. In addition, our RNN aggregator enables the server to aggregate gradients from variant local models, which significantly improve the scalability of distributed learning.
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Zhu, Heng, and Qing Ling. "Bridging Differential Privacy and Byzantine-Robustness via Model Aggregation." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/337.

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This paper aims at jointly addressing two seemly conflicting issues in federated learning: differential privacy (DP) and Byzantine-robustness, which are particularly challenging when the distributed data are non-i.i.d. (independent and identically distributed). The standard DP mechanisms add noise to the transmitted messages, and entangles with robust stochastic gradient aggregation to defend against Byzantine attacks. In this paper, we decouple the two issues via robust stochastic model aggregation, in the sense that our proposed DP mechanisms and the defense against Byzantine attacks have separated influence on the learning performance. Leveraging robust stochastic model aggregation, at each iteration, each worker calculates the difference between the local model and the global one, followed by sending the element-wise signs to the master node, which enables robustness to Byzantine attacks. Further, we design two DP mechanisms to perturb the uploaded signs for the purpose of privacy preservation, and prove that they are (epsilon,0)-DP by exploiting the properties of noise distributions. With the tools of Moreau envelop and proximal point projection, we establish the convergence of the proposed algorithm when the cost function is nonconvex. We analyze the trade-off between privacy preservation and learning performance, and show that the influence of our proposed DP mechanisms is decoupled with that of robust stochastic model aggregation. Numerical experiments demonstrate the effectiveness of the proposed algorithm.
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Deng, Gelei, Yuan Zhou, Yuan Xu, Tianwei Zhang, and Yang Liu. "An Investigation of Byzantine Threats in Multi-Robot Systems." In RAID '21: 24th International Symposium on Research in Attacks, Intrusions and Defenses. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3471621.3471867.

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Xiao, Guomei, Bo Mi, Darong Huang, Yang Liu, Yang Li, and Yuan Weng. "Anonymous Voting System Against Byzantine Attacks." In 2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS). IEEE, 2021. http://dx.doi.org/10.1109/safeprocess52771.2021.9693543.

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Gouissem, A., K. Abualsaud, E. Yaacoub, T. Khattab, and M. Guizani. "Federated Learning Stability Under Byzantine Attacks." In 2022 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2022. http://dx.doi.org/10.1109/wcnc51071.2022.9771594.

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