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Distributed Detection in Mobile Access Wireless Sensor Networks under Byzantine Attacks

ABSTRACT:

               One of the research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we solve the k-coverage sensor deployment problem to achieve multi-level coverage of an area I. We consider two sub-problems: k-coverage placement and distributed dispatch problems. The placement problem asks how to determine the minimum number of sensors required and their locations in I to guarantee that I is k-covered and the network is connected; the dispatch problem asks how to schedule mobile sensors to move to the designated locations according to the result computed by the placement strategy such that the energy consumption due to movement is minimized. Our solutions to the placement problem consider both the binary and probabilistic sensing models, and allow an arbitrary relationship between the communication distance and sensing distance of sensors. For the dispatch problem.

EXISTING SYSTEM:

          In existing system, we consider reliable data fusion in wireless sensor networks with mobile access points (SENMA) under both static and dynamic Byzantine attacks, in which the malicious nodes report false information with a fixed or time-varying probability, respectively. In SENMA, the mobile access point traverses the network and collects the sensing information from the individual sensor nodes. The major advantage of the SENMA architecture is that it ensures a line of sight path to the access point within the power range of the sensor nodes, allowing the information to be conveyed without routing. This feature makes it a resilient, scalable and energy efficient architecture for wireless sensor networks.

DRAWBACK IN EXISTING SYSTEM:

Due to its high computational complexity, the optimal q-out-of-m scheme is infeasible as the network size increases and/or the attack behavior changes.

EXISTING MODELS:

SENMA (SENSOR NETWORK WITH MOBILE ACCESS POINTS)

PROPOSED SYSTEM:

We proposed simplified q-out-of-m fusion schemes by exploiting the linear relationship between the scheme parameters and the network size. We also derived a near-optimal closed-form solution for the fusion threshold based on the central limit theorem. An important observation is that, even if the percentage of malicious sensors remains fixed, the false alarm rate diminishes exponentially with the network size. This implies that for a fixed percentage of malicious nodes, we can improve the network performance significantly by increasing the density of the nodes.

ADVANTAGES OF PROPOSED SYSTEM:

We show that under a fixed percentage of malicious nodes, the false alarm rate for both approaches diminishes exponentially as the network size increases.

The proposed adaptive fusion scheme can improve the system performance significantly under both static and dynamic attack strategies.

PROPOSED MODEL: