Denial Of Service Attacks In Networks Research Articles

Learning-Based Distributed Resilient Fault-Tolerant Control Method for Heterogeneous MASs Under Unknown Leader Dynamic

In this article, we consider the distributed fault-tolerant resilient consensus problem for heterogeneous multiagent systems (MASs) under both physical failures and network denial-of-service (DoS) attacks. Different from the existing consensus results, the dynamic model of the leader is unknown for all followers in this article. To learn this unknown dynamic model under the influence of DoS attacks, a distributed resilient learning algorithm is proposed by using the idea of data-driven. Based on the learned dynamic model of the leader, a distributed resilient estimator is designed for each agent to estimate the states of the leader. Then, a new adaptive fault-tolerant resilient controller is designed to resist the effect of physical failures and network DoS attacks. Moreover, it is shown that the consensus can be achieved with the proposed learning-based fault-tolerant resilient control method. Finally, a simulation example is provided to show the effectiveness of the proposed method.

Distributed security secondary control for cyber-physical microgrids systems under network DoS attacks

This paper considers the frequency regulation and power-sharing problems for cyber-physical microgrids (MGs) under network denial-of-service (DoS) attacks and time-varying communication delays. Compared to conventional distributed controllers based on a system model with ideal communication, a distributed security control protocol is designed. Benefiting from the developed security control method, the adverse effects of network DoS attacks and communication delays can be resisted. Then, a sufficient condition, which is used to achieve the achieve frequency restoration and power-sharing, is established according to the frequency and duration of DoS attacks. By using the average dwell time method and the Lyapunov stability theory, it is theoretically proved that the proposed control scheme can guarantee the stability of the overall AC microgrid system. In order to illustrate the proposed scheme, simulation studies are carried out based on an islanded AC microgrid system with four distributed generators (DGs) built in the simulation. The results do show its effectiveness and also verify the established theoretical results.

Fundamental Limits of Volume-based Network DoS Attacks

Volume-based network denial-of-service (DoS) attacks refer to a class of cyber attacks where an adversary seeks to block user traffic from service by sending adversarial traffic that reduces the available user capacity. In this paper, we explore the fundamental limits of volume-based network DoS attacks by studying the minimum required rate of adversarial traffic and investigating optimal attack strategies. We start our analysis with single-hop networks where user traffic is routed to servers following the Join-the-Shortest- Queue (JSQ) rule. Given the service rates of servers and arrival rates of user traffic, we first characterize the feasibility region of the attack and show that the attack is feasible if and only if the rate of the adversarial traffic lies in the region.We then design an attack strategy that is (i). optimal: it guarantees the success of the attack whenever the adversarial traffic rate lies in the feasibility region and (ii). oblivious: it does not rely on knowledge of service rates or user traffic rates. Finally, we extend our results on the feasibility region of the attack and the optimal attack strategy to multi-hop networks that employ Back-pressure (Max-Weight) routing. At a higher level, this paper addresses a class of dual problems of stochastic network stability, i.e., how to optimally de-stabilize a network.

Fundamental Limits of Volume-based Network DoS Attacks

Volume-based network denial-of-service (DoS) attacks refer to a class of cyber attacks where an adversary seeks to block user traffic from service by sending adversarial traffic that reduces the available user capacity. In this paper, we explore the fundamental limits of volume-based network DoS attacks by studying the minimum required rate of adversarial traffic and investigating optimal attack strategies. We start our analysis with single-hop networks where user traffic is routed to servers following the Join-the-Shortest-Queue (JSQ) rule. Given the service rates of servers and arrival rates of user traffic, we first characterize the feasibility region of the attack and show that the attack is feasible if and only if the rate of the adversarial traffic lies in the region. We then design an attack strategy that is (i).optimal: it guarantees the success of the attack whenever the adversarial traffic rate lies in the feasibility region and (ii).oblivious: it does not rely on knowledge of service rates or user traffic rates. Finally, we extend our results on the feasibility region of the attack and the optimal attack strategy to multi-hop networks that employ Back-pressure (Max-Weight) routing. At a higher level, this paper addresses a class of dual problems of stochastic network stability, i.e., how to optimally de-stabilize a network.

Prevention of DoS Attacks by Predicting the Values of Correlation Network Traffic Parameters

The authors propose an approach for the prevention of network denial of service attacks, which is based on predicting the values of the multiple correlation coefficients of the detail coefficients of the discrete wavelet transform of network traffic parameters.

Research on Detection and Defense Mechanisms of DoS Attacks Based on BP Neural Network and Game Theory

DoS (Denial of Service) attacks are becoming one of the most serious security threats to global networks. We analyze the existing DoS detection methods and defense mechanisms in depth. In this paper, BP (back propagation) neural networks and game theory are introduced to design detection methods and defense mechanisms for the DoS attacks. The BP neural network DoS attacks detection model uses KDDCUP99 as the dataset and selects multiple feature vectors from the dataset that can efficiently identify DoS attacks by large-scale training, which improves the accuracy of detecting DoS attacks to 99.977%. Furthermore, we use game theory to perform secondary analysis on DoS attacks that are not recognized by the neural network model, so that the detection rate of Dos attacks increases from 99.97% to 99.998%. Finally, we propose a DoS attacks defense strategy based on game theory. The simulation results show that the proposed detection method and defense strategy are effective for DoS attacks.

Novel Paradigm: Assessment of DOS Flooding Attack through Energy Aware Routing over MANET Environment

One of the most up-andcoming fields for research is mobile ad hoc network. Security is high Priority obligation in wireless ad-hoc network. In ad hoc network the communicating nodes sets new challenges for the security architecture because it doesn’t necessarily feed on fixed infrastructure. In the ad-hoc network denial of service attacks (DOS) forcefully initiate through malicious nodes or attacker which is more vulnerable. In this paper, we are clarify the incident of flooding attack and their exposed to the possibility of being attacked or harmed effects which give chance to a legitimate node for doing dissimilar attacks also. So we get going towards is to recognize the presence or existence of DOS flooding attack using secure routing protocols. This paper proposes a novel mechanism using allowable and limiting threshold for accurately measuring the flooded packets from the usual congestions. Somewhere it also prevents network being down from flooded traffic.. General Terms Energy awareness, limiting threshold