A Secure Mechanism Design-Based and Game Theoretical Model for MANETs

Rachedi, Abderrezak; Benslimane, Abderrahim; Otrok, Hadi; Mohammed, Noman; Debbabi, Mourad

doi:10.1007/s11036-009-0164-7

Cited by 10 publications

(4 citation statements)

References 24 publications

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“…Similarly, to balance the nodes' energy consumption and avoid the situation where there are some higher energy level nodes still in a dead network, the selection of a lower energy level node should have a higher cost than selecting a higher energy level node. Thus, we define the cost matrices for the simulation as follows: C1 = [5.5, 7.5, 11, 25, 31, 37, 43, 52, 63], C2 = [6,8,11,23,30,35,42,50,62], C3 = [6.5, 8.5, 12, 21, 28, 33, 40, 48, 60], C4 = [8,10,13,18,25,30,37,45,55], C5 = [8.5, 11, 15, 19, 27, 32, 38, 47, 58], C6 = [9,10,15,20,28,32,38,48,59], C7 = [9,12,16,15,20,28,33,40,50], C8 = [10,13,18,16,21,28,34,42,51], and C9 = [11,…”

Section: Simulation Experiments and Resultsmentioning

confidence: 99%

“…Following this approach, the authors of [19] present low overhead truthful routing protocol (LOTTO), a low-overhead truthful routing protocol for route discovery in MANETs with selfish nodes by designing incentives based on VCG mechanism [12], to prevent nodes from revealing fake information and ensure truth telling to be the dominant strategy among all nodes. In [20], a mechanism-design-based model is proposed to motivate nodes that do not belong to the confident community to participate in being selected as RA, by giving them incentives in the form of trust. An RA selection algorithm is also proposed in this paper to select nodes based on a predefined selection criteria function and nodes location.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Incentive-Based Optimal Nodes Selection Mechanism for Threshold Key Management in MANETs with Selfish Nodes

Guo

Wang

et al. 2013

International Journal of Distributed Sensor Networks

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Most of the previous work on threshold-cryptography-based distributed CA concentrates on the initial systems configurations and concrete protocols design, ignoring the efficiency and effectiveness of the key management service during its operation, and always assuming that there are honest nodes to carry out the service faithfully. This paper focuses on developing a selection mechanism in MANETs with selfish nodes, to dynamically select a coalition of nodes carrying out the threshold key management service optimally during system operation. First, we formulate the dynamic nodes selection problem as a combinatorial optimization problem, with the objectives of maximizing the success ratio of key management service and minimizing the nodes' cost of security and energy. Then, to ensure truth telling is the dominant strategy for any node in our scenario, we extend the payment structure of the classical Vickrey-Clarke-Groves (VCG) mechanism design framework and divide the payment into pieces to the nodes, with the consideration of their actual execution effectiveness. Simulations show that the proposed mechanism enjoys improvements of both the success ratio of key management service and lifetime of the network, as well as reductions of both the cost of participating nodes and compromising probability of MANETs, compared with the existing work.

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Section: Simulation Experiments and Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Incentive-Based Optimal Nodes Selection Mechanism for Threshold Key Management in MANETs with Selfish Nodes

Guo

Wang

et al. 2013

International Journal of Distributed Sensor Networks

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“…Incentive is proposed through the game theory as it is the case in [14], where authors enhance the security in mobile ad hoc networks. They motivate nodes to cooperate by increasing their reputation with an authority, which provides them some privileges in the network.…”

Section: B Incentive Approaches Based On Infrastructure Deploymentmentioning

confidence: 99%

A Job Market Signaling Scheme for Incentive and Trust Management in Vehicular Ad Hoc Networks

Haddadou

Rachedi

Ghamri‐Doudane

2015

IEEE Trans. Veh. Technol.

101

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International audienceIn collaborative wireless networks with a low infrastructure, the presence of misbehaving nodes can have a negative impact on network performance. In particular, we are interested in dealing with this nasty presence in road safety applications, based on vehicular ad hoc networks (VANETs). In this work, we consider as harmful the presence of malicious nodes, which spread false and forged data; and selfish nodes, which cooperate only for their own benefit. To deal with this, we propose a Distributed Trust Model (DTM2), adapted from the job market signaling model. DTM2 is based on allocating credits to nodes and securely managing these credits. To motivate selfish nodes to cooperate more, our solution establishes the cost of reception to access data, forcing them to earn credits. Moreover, to detect and exclude malicious nodes, DTM2 requires the cost of sending, using signaling values inspired form economics and based on the node's behavior, so that the more a node is malicious, the higher its sending cost, thus limiting their participation in the network. Similarly, rewards are given to nodes whose sent messages are considered as truthful, and that paid a sending cost considered as correct. The latter is a guarantee for the receivers about the truthfulness of the message since, in case of message refusal, the source node is not rewarded despite its payment. We validated DTM2 via a theoretical study using Markov chains; and with a set of simulations, in both urban and highway scenarios. Both theoretical and simulation results show that DTM2 excludes from the network 100% of malicious nodes, without causing any false positive detection. Moreover, our solution guarantees a good ratio of reception even in the presence of selfish nodes

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“…The proposed incentive models for cooperation are using the concept of virtual cash. For instance, many incentive models based on game theory are proposed [13,14]. The nodes are rewarded for forwarding packets by trading virtual cash with source and next hop nodes [13].…”

Section: Non-cooperative Nodes Monitoring and Detection Modelsmentioning

confidence: 99%

How MIMO cross-layer design enables QoS while detecting non-cooperative nodes in wireless multi-hop networks

Rachedi¹,

Badis²,

Benslimane³

2014

Journal of Network and Computer Applications

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In Journal of Network and Computer Applications (JNCA). DOI: 10.1016/j.jnca.2014.07.011International audienceWireless Multi-hop Networks (WMNs) are based on the cooperation between nodes. The non-cooperative (selfish) nodes can affect the quality of services (QoS) delivered by the network. The solutions proposed in literature are based on the monitoring mechanism to detect non-cooperative nodes. However, the monitoring mechanism has to tackle a significant false alarm rate. The origin of these issues is mainly related to the interferences and the costs of the monitoring mechanism. In WMNs based on Single-Input Single-Output (SISO) technology, the interferences at the monitor (detector) node can affect the assessment and the accuracy of the monitor node's observation. In this paper, we use Multi-Input and Multi-Output (MIMO) technology to tackle these drawbacks and to perform the monitoring mechanism without affecting the QoS. We propose a new MAC protocol based on the well-known SPACE-MAC protocol, named MIMODog. The collision at the monitor node can be avoided by tuning the antennas' weights. Therefore, the signal coming from other nodes than the monitored one can be nullified. Thus, this solution allows an important improvement of the accuracy of the monitor node's observation. Moreover, we propose a monitoring capacity analysis using graph theory particularly Conflict Graph (CG), and asymptotic study. We illustrate that the capacity consumed in the case of MIMODog is costly compared to SPACE-MAC, but the accuracy of the observation is better. We demonstrate that the number of monitor nodes is $\Theta(\frac{M}{\sqrt{n\ln n}})$ for a MIMO network with randomly located nodes n, each equipped with M antennas. Indeed, numerical results nlnn illustrate that by using MIMODog, the network can have a constant improvement M on an asymptotic number of monitor nodes compared to SISO 802.11 DCF MAC

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A Secure Mechanism Design-Based and Game Theoretical Model for MANETs

Cited by 10 publications

References 24 publications

Incentive-Based Optimal Nodes Selection Mechanism for Threshold Key Management in MANETs with Selfish Nodes

Incentive-Based Optimal Nodes Selection Mechanism for Threshold Key Management in MANETs with Selfish Nodes

A Job Market Signaling Scheme for Incentive and Trust Management in Vehicular Ad Hoc Networks

How MIMO cross-layer design enables QoS while detecting non-cooperative nodes in wireless multi-hop networks

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