Identifying Malicious Nodes in Wireless Sensor Networks Based on Correlation Detection

5G relies on its pervasive and convergent cloud-based architecture to accomplish its futuristic challenge of being the next-generation communication platform. However, the new perspectives opened by 5G networks do not go unnoticed. Regardless of their motivation or objectives, cyberattackers find in the new 5G ecosystem, including its tenancy-driven control plane, an attractive greenfield to create new types of denial of services attacks. In this article, we leverage on the virtualised environment of 5G to propose REPEL – an intelligent resource scaling strategy to mitigate DDoS signalling attacks preserving legitimate traffic. Our prevention-based approach uses games theory to build up a defence front line, able to keep services availability and discourage the attacker. To demonstrate the effectiveness and feasibility of our approach, we feed a queuing model with parameters obtained from a testbed, where simulated subscribers connect to a virtualised evolved packet core prototype. The final results show a dramatic signalling losses reduction, which can ensure the appropriate control plane availability under a DDoS attack.

REPEL: A Strategic Approach for Defending 5G Control Plane From DDoS Signalling Attacks

The smart grid provides advanced functionalities, including real-time monitoring, dynamic energy management, advanced pricing mechanisms, and self-healing, by enabling the two-way flow of power and data, as well as the use of Internet of Things (IoT) technologies and devices. However, converting the traditional power grids to smart grids poses severe security challenges and makes their components and services prone to cyber attacks. To this end, advanced techniques are required to mitigate the impact of the potential attacks. In this paper, we investigate the use of honeypots, which are considered to mimic the common services of the smart grid and are able to detect unauthorized accesses, collect evidence, and help hide the real devices. More specifically, the interaction of an attacker and a defender is considered, who both optimize the number of attacks and the defending system configuration, i.e., the number of real devices and honeypots, respectively, with the aim to maximize their individual payoffs. To solve this problem, game theoretic tools are used, considering an one-shot game and a repeated game with uncertainty about the payoff of the attacker, where the Nash Equilibrium (NE) and the Bayesian NE are derived, respectively. Finally, simulation results are provided, which illustrate the effectiveness of the proposed framework.

https://www.mdpi.com/1424-8220/20/15/4199/pdf

Game Theoretic Honeypot Deployment in Smart Grid.

Optimal DoS attack strategy for cyber-physical systems: A Stackelberg game-theoretical approach

Identifying malicious nodes in wireless sensor networks based on correlation detection

Denial of service (DoS) or distributed denial of service (DDoS) attacks based on bandwidth depletion remain a persistent network security threat and have always been an important issue for system administrators and researchers. Defence mechanisms proposed so far to defend against such attacks could not address the problem adequately and efficiently due to lack of quantitative approaches in modelling defence strategies against DoS/DDoS attacks. Game theory is a microeconomic and mathematical tool that provides a quantitative framework to model such attacks. A model based on game theory can act as a decision support system to the defender and augments its capabilities to take best decisions for maintaining an optimum level of network security round the clock against such attacks. Inspired by this, different DoS/DDoS scenarios, where game theory has been used to represent the strategic interaction between the attacker and a defender, are investigated. Based on the strategic interactions, a game theoretical defence mechanism is proposed to mitigate DoS/DDoS attacks. The proposed mechanism is based on two-player zero-sum game. It considers DoS/DDoS attack based on bandwidth depletion where an attacker wants to occupy maximum bandwidth of a link having a limited capacity. The attacker does so by flooding the network with unsolicited or malicious flows. The attacker has to decide an effective attack rate per flow. It has to choose an optimal size of botnet also for a cost-effective attack. It does trade-off analysis prior to attack. If its payoff or benefit obtained is less than the attack cost, it chooses to refrain from launching such a costlier DoS/DDoS attack. On the other hand, to set an upper bound on network traffic, the defender needs to set an optimum threshold per flow so that maximum attack flows are either dropped or redirected to a honeypot deployed in the network. Arbitrary setting of a threshold for flow rates can also cause a loss of legitimate flows. The defender chooses the optimum threshold value with precise estimation to minimize loss of legitimate flows. The defender also does trade-off analysis and sets the threshold in a way that can minimize the attacker’s payoff. This optimization problem is presented as a game between the attacker and defender. Action sets and objective functions of both players are defined. The network constrains are modelled and payoffs are calculated. The game converges to Nash equilibrium. The best course of actions is deduced from the Nash strategies. Results obtained by simulation and numerical calculations are in favour of the proposed game theoretical defence mechanism and strongly advocate the worthiness of using game theory to defend against DoS and DDoS attacks to strengthen network security.

/pdf/using-game-theory-to-model-dos-attack-and-defence-9yqaxxvaqn.pdf

Using game theory to model DoS attack and defence

Game Theoretical Defense Mechanism Against Reputation Based Sybil Attacks

DDoS attacks deplete network bandwidth and render the services unavailable to normal users. In spite of various qualitative and rule based defense mechanisms, the threat persists continuously because such mechanisms do not capture the incentive oriented attacker’s intentions. Game theory promises to provide incentive based decision support system to defend against such attacks. The current work proposes a defense mechanism designed as two player zero sum finite horizon repeated game where decisions to allow or drop an incoming traffic at edge router are taken based on a flow-rate threshold. The flow-rate threshold is dynamically adjusted and updated based on maximum payoff obtained by the defender at a particular stage of the game. Payoff is computed by quantifying network conditions and parameters. The normal and attack traffic are modelled using normal and poisson distribution functions respectively. Using these functions, drop and pass probabilities of flows are computed. Further, costs and benefits in respect of the attacker and defender are computed based on the bandwidth utilized by the flows. Subsequently, payoff functions are designed for attacker and defender. Payoff functions are optimized to construct baseline optimal strategies. Nash Equilibrium is obtained using numerical computations which suggests an optimal flow-rate threshold to be set by the defender to secure the network against DDoS attacks round the clock.

Game Theoretical Defense Mechanism Against Bandwidth Based DDoS Attacks

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Using game theory to model DoS attack and defence

Game Theoretical Defense Mechanism Against Reputation Based Sybil Attacks

Game Theoretical Defense Mechanism Against Bandwidth Based DDoS Attacks