Conference Paper

Quantifying eavesdropping vulnerability in sensor networks.

DOI: 10.1145/1080885.1080887 Conference: Proceedings of the 2nd Workshop on Data Management for Sensor Networks, in conjunction with VLDB, DMSN 2005, Trondheim, Norway, August 30, 2005
Source: DBLP

ABSTRACT With respect to security, sensor networks have a number of considerations that separate them from traditional distributed systems. First, sensor devices are typically vulnerable to physical compromise. Second, they have significant power and processing constraints. Third, the most critical security issue is protecting the (statistically derived) aggregate output of the system, even if individual nodes may be compromised. We suggest that these considerations merit a rethinking of traditional security techniques: rather than depending on the resilience of cryptographic techniques, in this paper we develop new techniques to tolerate compromised nodes and to even mislead an adversary. We present our initial work on probabilistically quantifying the security of sensor network protocols, with respect to sensor data distributions and network topologies. Beginning with a taxonomy of attacks based on an adversary's goals, we focus on how to evaluate the vulnerability of sensor network protocols to eavesdropping. Different topologies and aggregation functions provide different probabilistic guarantees about system security, and make different trade-offs in power and accuracy.

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    ABSTRACT: This paper concerns the eavesdropping attacks from the eavesdroppers’ perspective, which is new since most of current studies consider the problem from the good nodes’ perspective. In this paper, we originally propose an analytical framework to quantify the effective area and the probability of the eavesdropping attacks. This framework enables us to theoretically evaluate the impact of node density, antenna model, and wireless channel model on the eavesdropping attacks. We verify via extensive simulations that the proposed analytical framework is very accurate. Our results show that the probability of eavesdropping attacks significantly vary, depending on the wireless environments (such as shadow fading effect, node density, and antenna types). This study lays the foundation toward preventing the eavesdropping attacks in more effective and more economical ways.
    Journal of Computational Science 11/2014; DOI:10.1016/j.jocs.2014.10.006 · 1.57 Impact Factor
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    ABSTRACT: This paper concerns the eavesdropping problem from the eavesdroppers' perspective, which is new since most of previous studies only concentrate on the good nodes. We propose an analytical framework to investigate the eavesdropping attacks, taking account into various channel conditions and antenna models. Our extensive numerical results show that the probability of eavesdropping attacks heavily depends on the shadow fading effect, the path loss effect and the antenna models; particularly, they imply that using directional antennas at eavesdroppers can increase the probability of eavesdropping attacks when the path loss effect is less notable. This study is helpful for us to prevent the eavesdropping attacks effectively and economically.
    IEEE International Conference on Communication Systems; 11/2014
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    ABSTRACT: Pervasive mobile and low-end wireless technologies, such as radio-frequency identification (RFID), wireless sensor networks and the impending vehicular ad-hoc networks (VANETs), make the wireless scenario exciting and in full transformation. For all the above (and similar) technologies to fully unleash their potential in the industry and society, there are two pillars that cannot be overlooked: security and privacy. Both properties are especially relevant if we focus on ad-hoc wireless networks, where devices are required to cooperate – e.g. from routing to the application layer – to attain their goals. In this paper, we survey emerging and established wireless ad-hoc technologies and we highlight their security/privacy features and deficiencies. We also identify open research issues and technology challenges for each surveyed technology.
    Computer Communications 09/2014; 51. DOI:10.1016/j.comcom.2014.06.003 · 1.35 Impact Factor

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