Rajani Muraleedharan

Jamming attack detection and countermeasures in wireless sensor network using ant system

Sensors have varied constraints, which makes the network challenging for communicating with its peers. In this paper, an extension to the security of physical layer of a predictive sensor network model using the ant system is proposed. The Denial of Service (DoS) attack on sensor networks not only diminishes the network performance but also affects the reliability of the information making detection of a DoS threat is more crucial than recovering from the attack. Hence, in this paper, a novel approach in detecting the DoS attack is introduced and analyzed for a variety of scenarios. The DoS attack is dependent on the vulnerabilities in each layer, with the physical layer being the lowest layer and the first to be attacked by jammers. In this paper, the physical layer DoS attack is analyzed and a defense mechanism is proposed. Classification of the jammer under various attack scenarios is formulated to predict the genunity of the DoS attacks on the sensor nodes using receiver operating characteristics (ROC). This novel approach helps in achieving maximum reliability on DoS claims improving the Quality of Service (QoS) of WSN.

Contourlet Based Image Compression for Wireless Communication in Face Recognition System

This paper proposes to use Contourlet transform for image compression and feature extraction for wireless face recognition system. The properties of face images and face recognition techniques are incorporated into the design of wireless transmission for such a system. The reasons for utilizing contourlet transform are two-folded. Firstly, in face recognition, the edge information is crucial in deriving features, and the edges within a face image are not just horizontal or vertical. When the coefficients are transmitted through the fading channel, the reconstruction from the Stein-thresholded noisy coefficients by contourlet achieves less mean square error than by wavelet. Secondly, when the network resources limit the transmission of full-set coefficients, the lower band coefficients can serve as a scaled-down version of the face image, for a coarser face recognition as screening. A prioritized transmission of the coefficients take full advantage of the wireless channel. Simulation shows that the wireless face recognition system works as well as a wired one, while gaining the cost efficiency, and the flexibility in deployment. An interesting phenomenon is discovered on FERET database that when the transmission error rate is increased linearly, the recognition performance degradation is not linear; instead, the performance stays the same for a large range of error rates, which illustrates that contourlet based face recognition system can tolerate the transmission error up to some threshold.

A predictive sensor network using ant system

The need for a robust predictive sensor communication network inspired this research. There are many critical issues in a communication network with different data rate requirements, limited power and bandwidth. Energy consumption is one of the key issues in a sensor network as energy dissipation occurs during routing, communication and monitoring of the environment. This paper covers the routing of a sensor communication network by applying an evolutionary algorithm -- the ant system. The issues considered include optimal energy, data fusion from different sensor types and predicting changes in environment with respect to time.

Detecting Sybil attacks in image senor network using cognitive intelligence

Wireless Sensor Network has become state-of-art technology of the 21st century, the application ranges from academic to military operations. These tiny sensors can be deployed in open environment, where security to neither data nor hardware can be guaranteed. Unfortunately, due to the resource constraints traditional security schemes cannot be applied directly, therefore designing protocols that can operate securely using smart inherent features is the only viable option. In this paper, Sybil, a denial of service attack on Image Sensor Network is analyzed and the characteristic of the cognitive protocol against this attack is evaluated based on the networks reliability and quality of service.

Security: Cross Layer Protocol in Wireless Sensor Network

Application such as health monitoring, disaster relief mission, etc. require secure communication of messages. In this paper, we propose a novel approach of using an evolutionary algorithm with self adapting nature to avoid denial of service (DoS) attack. This approach is best suited for applications where energy and computation power is sparse. Detection of DoS claims and countermeasures taken while maximizing quality of service (QoS) is explained with results.

Cross Layer Denial of Service Attacks in Wireless Sensor Network Using Swarm Intelligence

Need for secure communication in wireless sensor network applications such as health monitoring system, building or infrastructure access systems, tsunami warning systems, etc. inspired this research. This paper is an extension to the smart building access system proposed. In this paper, a cross-layer security mechanism is proposed to detect denial of service (DoS) attacks and the countermeasures taken to avoid the same without comprising any network resources.

Cognitive security protocol for sensor based VANET using swarm intelligence

Intelligent Transportation system (ITS) using wireless and mobile ad-hoc sensor network has inspired many autonomous applications. Vehicular Ad-hoc network (VANET) is an emerging technology where vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communicate wirelessly using dedicated short-range communication band. In sensor based VANET (S-VANET) issues like response time, data aging, bandwidth, packet delivery, message prioritization and communication cost is a major concern. In this paper, we apply cognitive security protocol that disseminates information using distributed sensor technology while prioritizing prevention of data aging, efficient quality-of-service (QoS) and robustness against denial-of-service (DoS) attack. The reliability and optimality of the protocol is computed based on current mission response time and maintaining message authentication, integrity, confidentiality and non-repudiation.

Increasing QoS and Security in 4G Networks Using Cognitive Intelligence

Mobile networks have become an essential part of our day to day lives. The information shared requires secure communications with high reliability and quality-of-service (QoS). Hence, designing a 4G network to provide secure IP-based service by trading off constraints such as battery life, bandwidth and size to mobile users is a challenging task. In this paper, a cognitive framework using an evolutionary algorithm, Swarm Intelligence, is proposed. This framework uses a novel approach that utilizes a cost function that chooses the optimal parameters to provide an adaptive quality of service (QoS) based on the users needs. This approach ensures interoperability and scalability between different modulation techniques in the physical layer and enhances security against denial of service attacks such as jamming attacks and signaling attack.

Robustness of predictive sensor network routing in fading channels

Sensors have varied constraints, which make the network challenging for communicating with peers. In this paper, an extension, to the physical layer of the previous predictive sensor network model using the ant system is proposed. The tiny and low-cost sensor nodes are made of RF wireless links, where the states of the nodes vary with respect to time and environment. The ant system is a learning algorithm, that can be used to solve any NP hard communication problem and possesses characteristics such as robustness and versatility. The ant system possesses unique features that keep the network functional by detecting weak links and re-routing the agents. The swarm agents are distributed along the network, where the agent communicates with its neighbors (agents) by means of pheromone deposition and tabu list. The transition probability in the ant system includes an objective function, which is influenced by the poset weights. The poset weights on each of the orthogonal communication parameters greatly affects the decisions made by ant system. The agents carry updated information of its previous nodes, which helps in monitoring the strength of the communication links. Through simulation, comparison between DSSS-BPSK and Bluetooth-GFSK signals are shown. This paper demonstrates the robustness of the model under slow/fast fading, and energy loss at node during transmission. Implementation of this algorithm should be able to handle hostile environmental conditions and human tampering of data. The performance of the network is evaluated based on accuracy and response time of the agents within the network.

Resource optimization in distributed biometric recognition using wireless sensor network

Distributed, autonomous and energy efficient protocols are best suited for wireless sensor networks, where network needs and events are dynamic. In this paper, a wireless face recognition system with limited resources such as energy, memory and bandwidth is analyzed. The performance of the applications is influenced by the protocol adaptability and quality of information. Performance comparisons are completed using 1. In-network image compression using Contourlet and Wavelet transforms versus raw image data transmission, 2. longevity of sensors versus network throughput. Balancing resource constraints, maintaining network lifetime and throughput is a non-deterministic polynomial computation time problem. Thus a meta-heuristic combinatorial algorithm, based on swarm intelligence, forms the cognitive routing protocol. The network efficiency considers energy consumption, response time, probability of correct acceptance, processing and computation time for wireless image transmission.