Cognitive Security Framework For Heterogeneous Sensor Network Using Swarm Intelligence

Rapid development of sensor technology has led to applications ranging from academic to military in a short time span. These tiny sensors are deployed in environments where security for data or hardware cannot be guaranteed. Due to resource constraints, traditional security schemes cannot be directly applied. Unfortunately, due to minimal or no communication security schemes, the data, link and the sensor node can be easily tampered by intruder attacks. This dissertation presents a security framework applied to a sensor network that can be managed by a cohesive sensor manager. A simple framework that can support security based on situation assessment is best suited for chaotic and harsh environments. The objective of this research is designing an evolutionary algorithm with controllable parameters to solve existing and new security threats in a heterogeneous communication network. An in-depth analysis of the different threats and the security measures applied considering the resource constrained network is explored. Any framework works best, if the correlated or orthogonal performance parameters are carefully considered based on system goals and functions. Hence, a trade-off between the different performance parameters based on weights from partially ordered sets is applied to satisfy application specific requirements and security measures. The proposed novel framework controls heterogeneous sensor network requirements,and balance the resources optimally and efficiently while communicating securely using a multi-objection function. In addition, the framework can measure the affect of single or combined denial of service attacks and also predict new attacks under both cooperative and non-cooperative sensor nodes. The cognitive intuition of the framework is evaluated under different simulated real time scenarios such as Health-care monitoring, Emergency Responder, VANET, Biometric security access system, and Battlefield monitoring. The proposed three-tiered Cognitive Security Framework is capable of performing situation assessment and performs the appropriate security measures to maintain reliability and security of the system. The first tier of the proposed framework, a crosslayer cognitive security protocol defends the communication link between nodes during denial-of-Service attacks by re-routing data through secure nodes. The cognitive nature of the protocol balances resources and security making optimal decisions to obtain reachable and reliable solutions. The versatility and robustness of the protocol is justified by the results obtained in simulating health-care and emergency responder applications under Sybil and Wormhole attacks. The protocol considers metrics from each layer of the network model to obtain an optimal and feasible resource efficient solution. In the second tier, the emergent behavior of the protocol is further extended to mine information from the nodes to defend the network against denial-of-service attack using Bayesian models. The jammer attack is considered the most vulnerable attack, and therefore simulated vehicular ad-hoc network is experimented with varied types of jammer. Classification of the jammer under various attack scenarios is formulated to predict the genuineness of the attacks on the sensor nodes using receiver operating characteristics. In addition to detecting the jammer attack, a simple technique of locating the jammer under cooperative nodes is implemented. This feature enables the network in isolating the jammer or the reputation of node is affected, thus removing the malicious node from participating in future routes. Finally, a intrusion detection system using `bait\u27 architecture is analyzed where resources is traded-off for the sake of security due to sensitivity of the application. The architecture strategically enables ant agents to detect and track the intruders threateningthe network. The proposed framework is evaluated based on accuracy and speed of intrusion detection before the network is compromised. This process of detecting the intrusion earlier helps learn future attacks, but also serves as a defense countermeasure. The simulated scenarios of this dissertation show that Cognitive Security Framework isbest suited for both homogeneous and heterogeneous sensor networks

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

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

Balancing the performance of a sensor network using an ant system

Abstract- In a sensor network consisting of both wired and wireless links, the nodes sense, collect and distribute dynamic information from one sensor to the other. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. The sensors also have limited memory and functionality to support communications. Therefore, there is a need to balance energy usage with obtaining the shortest communication distance. This paper presents a novel approach to selecting message routes using an ant system. Parameters controlling the convergence of the ant system are analyzed in terms of wired and wireless networks. I

Sensor Communication Networks Using Swarming Intelligence

Abstract- Energy consumption is currently a key issue in research for future sensor networks. This paper presents a novel approach to sensor network routing based on energy consumption. The unique routing algorithm uses swarm intelligence, which is computationally efficient

Decision Making In a Building Access System Using Swarm Intelligence & POSETS

Abstract- The need for a new decision making approach for selecting communication routes in a biometric sensor network supporting a building access application[1] inspired this research. This paper uses swarm intelligence[2] to choose the optimal route in a distributed, time-varying, wireless building sensor network and partially ordered sets called POSets [ 3] to properly weight the performance parameters based on the time varying access needs. I

Increased Efficiency of Face Recognition System using Wireless Sensor Network

This research was inspired by the need of a flexible and cost effective biometric security system. The flexibility of the wireless sensor network makes it a natural choice for data transmission. Swarm intelligence (SI) is used to optimize routing in distributed time varying network. In this paper, SI maintains the required bit error rate (BER) for varied channel conditions while consuming minimal energy. A specific biometric, the face recognition system, is discussed as an example. Simulation shows that the wireless sensor network is efficient in energy consumption while keeping the transmission accuracy, and the wireless face recognition system is competitive to the traditional wired face recognition system in classification accuracy

Robustness of Predictive Sensor Network Routing in Fading Channels

Sensors and their corresponding communication network operate under a variety of constraints, which make effective and robust network routing challenging. In this paper, an extension to the sensor network routing that takes into account physical layer predictions and models [1] using the ant system is proposed. This paper demonstrates the robustness of this approach under slow or fast fading conditions. Implementation of this algorithm should be able to handle hostile environmental conditions. The performance of the network is evaluated based on the bit rate accuracy and response time of the communication routing agents within the network