Optimal Scanning Bandwidth Strategy Incorporating Uncertainty about Adversary's Characteristics

In this paper we investigate the problem of designing a spectrum scanning strategy to detect an intelligent Invader who wants to utilize spectrum undetected for his/her unapproved purposes. To deal with this problem we model the situation as two games, between a Scanner and an Invader, and solve them sequentially. The first game is formulated to design the optimal (in maxmin sense) scanning algorithm, while the second one allows one to find the optimal values of the parameters for the algorithm depending on parameters of the network. These games provide solutions for two dilemmas that the rivals face. The Invader's dilemma consists of the following: the more bandwidth the Invader attempts to use leads to a larger payoff if he is not detected, but at the same time also increases the probability of being detected and thus fined. Similarly, the Scanner faces a dilemma: the wider the bandwidth scanned, the higher the probability of detecting the Invader, but at the expense of increasing the cost of building the scanning system. The equilibrium strategies are found explicitly and reveal interesting properties. In particular, we have found a discontinuous dependence of the equilibrium strategies on the network parameters, fine and the type of the Invader's award. This discontinuity of the fine means that the network provider has to take into account a human/social factor since some threshold values of fine could be very sensible for the Invader, while in other situations simply increasing the fine has minimal deterrence impact. Also we show how incomplete information about the Invader's technical characteristics and reward (e.g. motivated by using different type of application, say, video-streaming or downloading files) can be incorporated into scanning strategy to increase its efficiency.Comment: This is the last draft version of the paper. Revised version of the paper was published in EAI Endorsed Transactions on Mobile Communications and Applications, Vol. 14, Issue 5, 2014, doi=10.4108/mca.2.5.e6. arXiv admin note: substantial text overlap with arXiv:1310.724

Game Theory Approaches in Taxonomy of Intrusion Detection for MANETs

MANETs are self configuring networks that are formed by a set of wireless mobile nodes and have no fixed network infrastructure nor administrative support. Since transmission range of wireless network interfaces is limited, forwarding hosts may be needed. Each node in a wireless ad hoc network functions is as both a host and a router. Due to their communication type and resources constraint, MANETs are vulnerable to diverse types of attacks and intrusions so, security is a critical issue. Network security is usually provided in the three phases: intrusion prevention, intrusion detection and intrusion tolerance phase. However, the network security problem is far from completely solved. Researchers have been exploring the applicability of game theory approaches to address the network security issues. This paper reviews some existing game theory solutions which are designed to enhance network security in the intrusion detection phase. Keywords: Mobile Ad hoc Network (MANET), Intrusion detection system (IDS), Cluster head, host based, Game theory

Intrusion Detection in Mobile Adhoc Network with Bayesian model based MAC Identification

Mobile Ad-hoc Networks (MANETs) are a collection of heterogeneous, infrastructure less, self-organizing and battery powered mobile nodes with different resources availability and computational capabilities. The dynamic and distributed nature of MANETs makes them suitable for deployment in extreme and volatile environmental conditions. They have found applications in diverse domains such as military operations, environmental monitoring, rescue operations etc. Each node in a MANET is equipped with a wireless transmitter and receiver, which enables it to communicate with other nodes within its wireless transmission range. However, due to limited wireless communication range and node mobility, nodes in MANET must cooperate with each other to provide networking services among themselves. Therefore, each node in a MANET acts both as a host and a router. Present Intrusion Detection Systems (IDSs) for MANETs require continuous monitoring which leads to rapid depletion of a node?s battery life. To avoid this issue we propose a system to prevent intrusion in MANET using Bayesian model based MAC Identification from multiple nodes in network. Using such system we can provide lightweight burden to nodes hence improving energy efficiency

Intrusion Detection in Mobile Ad-Hoc Networks using Bayesian Game Methodology

The dynamic and distributed nature of MANETs make them vulnerable to various types of attacks like black hole attack, traffic distortion, IP spoofing, DoS attack etc. Malicious nodes can launch attacks against other normal nodes and deteriorate the overall performance of the entire network [1�3]. Unlike in wired networks, there are no fixed checkpoints like router and switches in MANETs, where the Intrusion Detection System (IDS) can be deployed .However, due to limited wireless communication range and node mobility, nodes in MANET must cooperate with each other to provide networking services among themselves. Therefore, each node in a MANET acts both as a host and a router. Present Intrusion Detection Systems (IDSs) for MANETs require continuous monitoring which leads to rapid depletion of a node�s battery life. To avoid this issue we propose a system to prevent intrusion in MANET using Bayesian model based MAC Identification from multiple nodes in network. Using such system we can provide lightweight burden to nodes hence improving energy efficiency. Simulated results shows improvement in estimated delay and average bits transfer parameter

Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

Bayesian signaling game based efficient security model for MANETs

Game Theory acts as a suitable tool offering promising solutions to security-related concerns in Mobile Ad Hoc Networks (i.e., MANETs). In MANETs, security forms a prominent concern as it includes nodes which are usually portable and require significant coordination between them. Further, the absence of physical organisation makes such networks susceptible to security breaches, hindering secure routing and execution among nodes. Game Theory approach has been manipulated in the current study to achieve an analytical view while addressing the security concerns in MANETs. This paper offers a Bayesian-Signaling game model capable of analysing the behaviour associated with regular as well as malicious nodes. In the proposed model, the utility of normal nodes has been increased while reducing the utility linked to malicious nodes. Moreover, the system employs a reputation system capable of stimulating best cooperation between the nodes. The regular nodes record incessantly to examine their corresponding nodes’ behaviours by using the belief system of Bayes-rules. On its comparison with existing schemes, it was revealed that the presented algorithm provides better identification of malicious nodes and attacks while delivering improved throughput and reduced false positive rate