159 research outputs found

    Effect of 3D Wormholes Attack in Performance Analysis of Wireless Sensor Network for Cellular, Grid and Random Topologies

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    Wireless sensor networks (WSN) are usually originated for gathering records from insecure surroundings. Nearly all security protocols for WSN believe that the opponent can do entirely management over a sensing element node by manner of direct physical access. The looks of sensing element networks joined of the most technology within the future has exposed varied challenges to researchers. Wireless sensor networks are composed of huge variety of small sensing element nodes, running singly and in various cases with none access to renewable energy resources. Additionally security being basic to the acceptance and the use of sensing element networks for various applications, conjointly completely different set of challenges in sensing element networks square measure existed. In this paper, specialization will be on security of Wireless Sensor Networks for various topologies with 3D wormhole attack. DOI: 10.17762/ijritcc2321-8169.15051

    Security threats on wireless sensor network protocols

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    In this paper, we investigate security issues and challenges facing researchers in wireless sensor networks and countermeasures to resolve them. The broadcast nature of wireless communication makes Wireless Sensor Networks prone to various attacks. Due to resources limitation constraint in terms of limited energy, computation power and memory, security in wireless sensor networks creates different challenges than wired network security. We will discuss several attempts at addressing the issues of security in wireless sensor networks in an attempt to encourage more research into this area

    Research on a Denial of Service (DoS) Detection System Based on Global Interdependent Behaviors in a Sensor Network Environment

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    This research suggests a Denial of Service (DoS) detection method based on the collection of interdependent behavior data in a sensor network environment. In order to collect the interdependent behavior data, we use a base station to analyze traffic and behaviors among nodes and introduce methods of detecting changes in the environment with precursor symptoms. The study presents a DoS Detection System based on Global Interdependent Behaviors and shows the result of detecting a sensor carrying out DoS attacks through the test-bed

    A Study on Intrusion Detection System in Wireless Sensor Networks

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    The technology of Wireless Sensor Networks (WSNs) has become most significant in present day. WSNs are extensively used in applications like military, industry, health, smart homes and smart cities. All the applications of WSN require secure communication between the sensor nodes and the base station. Adversary compromises at the sensor nodes to introduce different attacks into WSN. Hence, suitable Intrusion Detection System (IDS) is essential in WSN to defend against the security attack. IDS approaches for WSN are classified based on the mechanism used to detect the attacks. In this paper, we present the taxonomy of security attacks, different IDS mechanisms for detecting attacks and performance metrics used to assess the IDS algorithm for WSNs. Future research directions on IDS in WSN are also discussed

    A Prey-Predator Defence Mechanism For Ad Hoc On-Demand Distance Vector Routing Protocol

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    This study proposes a nature-based system survivability model. The model was simulated, and its performance was evaluated for the mobile ad hoc wireless networks. The survivability model was used to enable mobile wireless distributed systems to keep on delivering packets during their stated missions in a timely manner in the presence of attacks. A prey-predator communal defence algorithm was developed and fused with the Ad hoc On-demand Distance Vector (AODV) protocol. The mathematical equations for the proposed model were formulated using the Lotka-Volterra theory of ecology. The model deployed a security mechanism for intrusion detection in three vulnerable sections of the AODV protocol. The model simulation was performed using MATLAB for the mathematical model evaluation and using OMNET++ for protocol performance testing. The MATLAB simulation results, which used empirical and field data, have established that the adapted Lotka-Volterra-based equations adequately represent network defense using the communal algorithm. Using the number of active nodes as a measure of throughput after attack (with a maximum throughput of 250 units), the proposed model had a throughput of 230 units while under attack and the intrusion was nullified within 2 seconds. The OMNET++ results for protocol simulation that use throughput, delivery ratio, network delay, and load as performance metrics with the OMNET++ embedded datasets showed good performance of the model, which was better than the existing conventional survivability systems. The comparison of the proposed model with the existing model is also presented. The study concludes that the proposed communal defence model was effective in protecting the entire routing layer (layer 2) of the AODV protocol when exposed to diverse forms of intrusion attacks

    NeuDetect: A neural network data mining system for wireless network intrusion detection

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    This thesis proposes an Intrusion Detection System, NeuDetect, which applies Neural Network technique to wireless network packets captured through hardware sensors for purposes of real time detection of anomalous packets. To address the problem of high false alarm rate confronted by the current wireless intrusion detection systems, this thesis presents a method of applying the artificial neural networks technique to the wireless network intrusion detection system. The proposed system solution approach is to find normal and anomalous patterns on preprocessed wireless packet records by comparing them with training data using Back-propagation algorithm. An anomaly score is assigned to each packet by calculating the difference between the output error and threshold. If the anomaly score is positive then the wireless packet is flagged as anomalous and is negative then the packet is flagged as normal. If the anomaly score is zero or close to zero it will be flagged as an unknown attack and will be sent back to training process for re-evaluation

    Seluge++: A Secure Over-the-Air Programming Scheme in Wireless Sensor Networks

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    Over-the-air dissemination of code updates in wireless sensor networks have been researchers’ point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge

    Transport mechanism for wireless micro sensor network

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    Wireless sensor network (WSN) is a wireless ad hoc network that consists of very large number of tiny sensor nodes communicating with each other with limited power and memory constrain. WSN demands real-time routing which requires messages to be delivered within their end-to-end deadlines (packet lifetime). This report proposes a novel real-time with load distribution (RTLD) routing protocol that provides real time data transfer and efficient distributed energy usage in WSN. The RTLD routing protocol ensures high packet throughput with minimized packet overhead and prolongs the lifetime of WSN. The routing depends on optimal forwarding (OF) decision that takes into account of the link quality, packet delay time and the remaining power of next hop sensor nodes. RTLD routing protocol possesses built-in security measure. The random selection of next hop node using location aided routing and multi-path forwarding contributes to built-in security measure. RTLD routing protocol in WSN has been successfully studied and verified through simulation and real test bed implementation. The performance of RTLD routing in WSN has been compared with the baseline real-time routing protocol. The simulation results show that RTLD experiences less than 150 ms packet delay to forward a packet through 10 hops. It increases the delivery ratio up to 7 % and decreases power consumption down to 15% in unicast forwarding when compared to the baseline routing protocol. However, multi-path forwarding in RTLD increases the delivery ratio up to 20%. In addition, RTLD routing spreads out and balances the forwarding load among sensor nodes towards the destination and thus prolongs the lifetime of WSN by 16% compared to the baseline protocol. The real test bed experiences only slight differences of about 7.5% lower delivery ratio compared to the simulation. The test bed confirms that RTLD routing protocol can be used in many WSN applications including disasters fighting, forest fire detection and volcanic eruption detection
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