Clone Detection for Efficient System in WSN Using AODV

Wireless sensor networks accommodate a whole lot to thousands of sensor nodes and are wide employed in civilian and security applications. One in every of the intense physical attacks faced by the wireless sensor network is node clone attack. So 2 node clone detection protocols area unit introduced via distributed hash table and arbitrarily directed exploration to detect node clones. The previous primarily based on a hash table value that is already distributed and provides key based facilities like checking and caching to observe node clones. The later one is exploitation probabilistic directed forwarding technique and border determination. The simulation results for storage consumption, communication value and detection chance is completed exploitation NS2 and obtained arbitrarily directed exploration is that the best one having low communication value and storage consumption and has smart detection chance

Danger theory based node replication attacks detection in mobile wireless sensor network

Mobile wireless sensor networks (MWSNs) are commonly deployed in a harsh climate, notably unattended without any tamper-resistant tools; thereby an attacker can easily capture the sensor nodes in a very limited time. Once captured, the attacker can duplicate the sensor and subsequently deploys numerous clone nodes into the network in minimum time duration. This new breed of attack is called node replication attack, and while several solutions have been proposed to address such a security threat, they are mainly centralized and somewhat limited to static WSN. In this paper, we propose a hybrid (centralized and distributed) node replication attack detection method for MWSN, which operates based on Danger Theory in human immune system. As depicted in Danger Theory, the proposed method consists of two main security approaches, namely attack detection and security control. These approaches perform a multi-level detection, which is not only responsible to identify but also to verify the existence of clone nodes in the network. Performance evaluation demonstrates the efficiency (in terms of true and false positives) of the proposed detection method in detecting clone nodes in MWSN environment

AMISEC: Leveraging Redundancy and Adaptability to Secure AmI Applications

Security in Ambient Intelligence (AmI) poses too many challenges due to the inherently insecure nature of wireless sensor nodes. However, there are two characteristics of these environments that can be used effectively to prevent, detect, and confine attacks: redundancy and continuous adaptation. In this article we propose a global strategy and a system architecture to cope with security issues in AmI applications at different levels. Unlike in previous approaches, we assume an individual wireless node is vulnerable. We present an agent-based architecture with supporting services that is proven to be adequate to detect and confine common attacks. Decisions at different levels are supported by a trust-based framework with good and bad reputation feedback while maintaining resistance to bad-mouthing attacks. We also propose a set of services that can be used to handle identification, authentication, and authorization in intelligent ambients. The resulting approach takes into account practical issues, such as resource limitation, bandwidth optimization, and scalability

Clone Node Detection in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are often deployed in unfavourable situations where an assailant can physically capture some of the nodes, first can reprogram, and then, can replicate them in a large number of clones, easily taking control over the network. This replication node is also called as Clone node. The clone node or replicated node behave as a genuine node. It can damage the network. In node replication attack detecting the clone node important issue in Wireless Sensor Networks. A few distributed solutions have been recently proposed, but they are not satisfactory. First, they are intensity and memory demanding: A serious drawback for any protocol to be used in the WSN- resource constrained environment. In this project first investigate the selection criteria of clone detection schemes with regard to device types, detection methodologies, deployment strategies, and detection ranges. Further, they are vulnerable to the specific assailant models introduced in this paper. In this scenario, a particularly dangerous attack is the replica attack, in which the assailant takes the secret keying materials from a compromised node, generates a large number of assailant-controlled replicas that share the node’s keying materials and ID, and then spreads these replicas throughout the network. With a single captured node, the assailant can create as many replica nodes as he has the hardware to generate.. The replica nodes are controlled by the assailant, but have keying materials that allow them to seem like authorized participants in the network. Our implementation specifies, user will specify its ID, which means client id, secret key will be create, and then include the port number. The witness node will verify the internally bounded user Id and secret key. The witness node means original node. If the verification is success, the information collecting to the packets that packets are send to the destination