A novel approach for the fast detection of black holes in mobile ad hoc networks

Mobile ad hoc networks are infrastructure-less wireless networks that rely on node cooperation to properly work. In this kind of networks, attack detection and reaction is a key issue to the whole network. The most common threat in mobile ad hoc network scenarios consists in the presence of a certain percentage of selfish nodes, which try to reduce the consumption of their own resources to prolong their battery lifetime. Those nodes do not collaborate on forwarding activities, therefore affecting the overall network performance. Watchdogs are well-known mechanisms to detect threats and attacks from misbehaved and selfish nodes in computer networks. The problem behind the use of watchdogs is that while they can be quite effective in detecting selfishness by using their traffic overhearing behaviour, they can also cause a relatively high level of false negatives, thereby reducing their accuracy. This article proposes a collaborative approach for detecting selfish nodes in mobile ad hoc networks. It is based on using a set of collaborative watchdogs, which collaborate to enhance their individual and collective performance. By using both an analytical study and simulation, we demonstrate that our approach is able to improve accuracy and detection speed, while reducing the impact of false-negative eventsThis work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under grant TIN2011-27543-C03-01.Serrat Olmos, MD.; Hernández Orallo, E.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2013). A novel approach for the fast detection of black holes in mobile ad hoc networks. Concurrent Engineering: Research and Applications. 21(3):177-185. https://doi.org/10.1177/1063293X13493448S177185213Buchegger, S., & Le Boudec, J.-Y. (2005). Self-policing mobile ad hoc networks by reputation systems. IEEE Communications Magazine, 43(7), 101-107. doi:10.1109/mcom.2005.1470831Buttyán, L., & Hubaux, J.-P. (2003). Mobile Networks and Applications, 8(5), 579-592. doi:10.1023/a:1025146013151Groenevelt, R., Nain, P., & Koole, G. (2005). The message delay in mobile ad hoc networks. Performance Evaluation, 62(1-4), 210-228. doi:10.1016/j.peva.2005.07.018Hortelano, J., Calafate, C. T., Cano, J. C., de Leoni, M., Manzoni, P., & Mecella, M. (2010). Black-Hole Attacks in P2P Mobile Networks Discovered through Bayesian Filters. Lecture Notes in Computer Science, 543-552. doi:10.1007/978-3-642-16961-8_77Li, Y., Su, G., Wu, D. O., Jin, D., Su, L., & Zeng, L. (2011). The Impact of Node Selfishness on Multicasting in Delay Tolerant Networks. IEEE Transactions on Vehicular Technology, 60(5), 2224-2238. doi:10.1109/tvt.2011.2149552Marti, S., Giuli, T. J., Lai, K., & Baker, M. (2000). Mitigating routing misbehavior in mobile ad hoc networks. Proceedings of the 6th annual international conference on Mobile computing and networking - MobiCom ’00. doi:10.1145/345910.345955T.V.P, S., & A, S. (2010). Modeling the Behavior of Selfish Forwarding Nodes to Stimulate Cooperation in MANET. International journal of Network Security & Its Applications, 2(2), 147-160. doi:10.5121/ijnsa.2010.2212Xu, L., Lin, Z., & Ye, A. (2006). Analysis and Countermeasure of Selfish Node Problem in Mobile Ad Hoc Network. 2006 10th International Conference on Computer Supported Cooperative Work in Design. doi:10.1109/cscwd.2006.253072Zhong, S., Chen, J., & Yang, Y. R. (s. f.). Sprite: a simple, cheat-proof, credit-based system for mobile ad-hoc networks. IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428). doi:10.1109/infcom.2003.1209220Zhu, H., Fu, L., Xue, G., Zhu, Y., Li, M., & Ni, L. M. (2010). Recognizing Exponential Inter-Contact Time in VANETs. 2010 Proceedings IEEE INFOCOM. doi:10.1109/infcom.2010.546226

A New Scheme for Minimizing Malicious Behavior of Mobile Nodes in Mobile Ad Hoc Networks

The performance of Mobile Ad hoc networks (MANET) depends on the cooperation of all active nodes. However, supporting a MANET is a cost-intensive activity for a mobile node. From a single mobile node perspective, the detection of routes as well as forwarding packets consume local CPU time, memory, network-bandwidth, and last but not least energy. We believe that this is one of the main factors that strongly motivate a mobile node to deny packet forwarding for others, while at the same time use their services to deliver its own data. This behavior of an independent mobile node is commonly known as misbehaving or selfishness. A vast amount of research has already been done for minimizing malicious behavior of mobile nodes. However, most of them focused on the methods/techniques/algorithms to remove such nodes from the MANET. We believe that the frequent elimination of such miss-behaving nodes never allowed a free and faster growth of MANET. This paper provides a critical analysis of the recent research wok and its impact on the overall performance of a MANET. In this paper, we clarify some of the misconceptions in the understating of selfishness and miss-behavior of nodes. Moreover, we propose a mathematical model that based on the time division technique to minimize the malicious behavior of mobile nodes by avoiding unnecessary elimination of bad nodes. Our proposed approach not only improves the resource sharing but also creates a consistent trust and cooperation (CTC) environment among the mobile nodes. The simulation results demonstrate the success of the proposed approach that significantly minimizes the malicious nodes and consequently maximizes the overall throughput of MANET than other well known schemes.Comment: 10 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS July 2009, ISSN 1947 5500, Impact Factor 0.42

Analysis of a Reputation System for Mobile Ad-Hoc Networks with Liars

The application of decentralized reputation systems is a promising approach to ensure cooperation and fairness, as well as to address random failures and malicious attacks in Mobile Ad-Hoc Networks. However, they are potentially vulnerable to liars. With our work, we provide a first step to analyzing robustness of a reputation system based on a deviation test. Using a mean-field approach to our stochastic process model, we show that liars have no impact unless their number exceeds a certain threshold (phase transition). We give precise formulae for the critical values and thus provide guidelines for an optimal choice of parameters.Comment: 17 pages, 6 figure

PROTECT: Proximity-based Trust-advisor using Encounters for Mobile Societies

Many interactions between network users rely on trust, which is becoming particularly important given the security breaches in the Internet today. These problems are further exacerbated by the dynamics in wireless mobile networks. In this paper we address the issue of trust advisory and establishment in mobile networks, with application to ad hoc networks, including DTNs. We utilize encounters in mobile societies in novel ways, noticing that mobility provides opportunities to build proximity, location and similarity based trust. Four new trust advisor filters are introduced - including encounter frequency, duration, behavior vectors and behavior matrices - and evaluated over an extensive set of real-world traces collected from a major university. Two sets of statistical analyses are performed; the first examines the underlying encounter relationships in mobile societies, and the second evaluates DTN routing in mobile peer-to-peer networks using trust and selfishness models. We find that for the analyzed trace, trust filters are stable in terms of growth with time (3 filters have close to 90% overlap of users over a period of 9 weeks) and the results produced by different filters are noticeably different. In our analysis for trust and selfishness model, our trust filters largely undo the effect of selfishness on the unreachability in a network. Thus improving the connectivity in a network with selfish nodes. We hope that our initial promising results open the door for further research on proximity-based trust

A power efficient method against misbehaving node in reputation system to prevent sybil attack in mobile ad-hoc network

Mobile ad-hoc network has become a very important field of study for students and researchers owing to its wide application. In mobile ad-hoc network all nodes are responsible for routing and forwarding of packets, hence all nodes are required to act selflessly for proper functioning of mobile ad-hoc network. The presence of selfish behavior in a node can degrade the performance of the mobile ad hoc network to a large extent. Several works have been done for identification and punishment of the misbehaving nodes in mobile ad hoc network. We propose here a method where some selected neighbors are participated in detecting misbehaving nodes in power effective manners. These neighbors participating in selfish node detection are chosen randomly. It also alerts all other nodes about the misbehaving links in the network. The simulation studies show that this does the job efficiently with less power consumption in the network. The power effectiveness of the algorithm also reduces the number of misbehaving nodes because many nodes show misbehavior to save their power