Localization and Detection of Multiple Attacks in Wireless Sensor Networks Using Artificial Neural Network (original) (raw)
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In sensor network node detection plays an important role in many applications. In this report, we are proceeding to go over the methodologies for the node detection based on the position. Likewise, we will survey on how the node will be detected based on different methodologies like distance vector, GPS, etc., Even though the nodes are called up. We also perform surveys on identifying the malicious activity of guests in a sensor network, like wormhole attack. In this paper localization is protected by detecting compromised beacon nodes. Methods adopted are very simple yet effective, and efficiency is guaranteed within the constraints of a sensor's battery life and limited memory. The aims of this paper are reliable communication, cooperative network, expanding of a network and shrinking of the net. The work includes an RSSI technique for locating the situation of the Wi-Fi enabled nodes and determining the variance in the intensity of the signal at individual nodes connected to an admission point, as the number of nodes increases or reductions. Received Signal Strength Indicator (RSSI), On-Demand Multicast Routing Protocol (ODMRP), Mobile Ad Hoc Networks (MANETs), Vehicle-to-vehicle communication among vehicular ad hoc networks (VANETs), Wormhole Attack.
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Presently, wireless sensor network localization algorithms attracted various researchers toward research study and experiments . The location of nodes can be determined by various localization algorithms. These wireless sensor network localization algorithms are vulnerable and can be compromised for their security. There are various network security attacks like wormhole, impersonation, compromise, and duplicate attacks which degrade the performance of WSNs. In this research paper, under various network security attacks, we have tested wireless sensor network localization algorithms under certain performance matrices like mobility of WSN node’s, size of packets, temperature, and node density to find out the compromised WSN node’s residual energy. The simulation result shows how these localization algorithms are vulnerable to network security attacks.
An Application of a Detection and Location Algorithm of Evil Nodes in a Wireless Sensor Network
Wireless Sensor Networks (WSN) is the collection of homogenous, self-organized nodes called sensor nodes. These nodes have the capabilities of sensing, processing and communication of data with each over wirelessly using radio frequency channel. An evil node is a malicious node in WSN which can drop , modify and/or fabricate messages that forwards through it. This node has Sybil, Wormhole and /or Sinkhole attacks. There are many studies to identify the evil node in WSN. Some of these studies proposed using GPS with each node. Other studies proposed the monitoring method (each node monitors all its neighbor nodes continuously), or using authentication and encryption algorithms. All these methods require more power usage and computational processing time or appending more equipments with each node. The proposed system consists of two main stages: The first stage includes detection and determining the number of evil paths depending on sending an encoding messages by the source node gen...
Robust Node Localization with Intrusion Detection for Wireless Sensor Networks
Wireless sensor networks comprise a set of autonomous sensor nodes, commonly used for data gathering and tracking applications. Node localization and intrusion detection are considered as the major design issue in WSN. Therefore, this paper presents a new multi-objective manta ray foraging optimization (MRFO) based node localization with intrusion detection (MOMRFO-NLID) technique for WSN. The goal of the MOMRFO-NLID technique is to optimally localize the unknown nodes and determine the existence of intrusions in the network. The MOMRFO-NLID technique encompasses two major stages namely MRFO based localization of nodes and optimal Siamese Neural Network (OSNN) based intrusion detection. The OSNN technique involves the hyperparameter tuning of the traditional SNN using the MRFO algorithm and consequently increases the detection rate. In order to assess the enhanced performance of the MOMRFO-NLID technique, a series of simulations take place and the results reported superior performance compared to existing techniques interms of distinct evaluation parameters.
Detection and Localization of IDS Based Spoofing Attackers in Wireless Sensor Networks
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A Wireless sensor network consists of a series of sensing devices. These track parameters such as those required for tracking and surveillance and then effectively passes on this information with other such sensors over a specific geographical area within the wireless network. The problem with traditional wireless networks lies in the way that they are positioned in an unattended manner, being controlled remotely by the network operator. This opens up a pathway for attackers, which compromise and capture wireless nodes and launch a variety of attacks that impair the functioning of the system. The proposed system aims to localize and cluster these nodes together, according to their position, wherein the cluster head acts as an Intrusion Detection system by monitoring node behavior such as packet transmission. This information is used to identify the attacked nodes in the wireless sensor network.
Secure Localization: The Review on Possible Attacks of WSN and Their Remedy
2013
The entire field of wireless network security is vast and in an evolutionary stage. Secure localization of nodes in a Wireless Sensor Network (WSN) is an important research subject. When WSNs are deployed in hostile environments, many attacks happen, e.g., wormhole, sinkhole and Sybil attack. Some of them are attack on nodes and some of them are attack on information. So it is necessary to know about all possible attacks and their remedy. In this paper, we depict the attack model and talk about different types of node and doable common attacks against secure localization i.e. attacks on nodes and attacks on information. As well as we do the survey and try to find out the solutions on each attacks.
Bilateration: An Attack-Resistant Localization Algorithm of Wireless Sensor Network
Embedded and Ubiquitous Computing
Most of the state-of-the-art localization algorithms in wireless sensor networks (WSNs) are vulnerable to attacks from malicious or compromised network nodes, whereas the secure localization schemes proposed so far are too complex to be applied to power constrained WSNs. This paper provides a novel secure scheme "Bilateration" which is derived from multilateration but can be calculated more accurately and quickly to resolve the positions of unknown nodes without explicitly distinguishing what kind of location attacks the WSN is facing. This paper also compares Bilateration with three existing multilateration solutions that optimize the location estimation accuracy via LS, LMS and LLMS respectively in a simulated threat environment. The experiment results show that Bilateration gets the best tradeoff among estimation error, filtering ability and computational complexity.
IJERT-Secure Localization: The Review on Possible Attacks of WSN and Their Remedy
International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/secure-localization-the-review-on-possible-attacks-of-wsn-and-their-remedy https://www.ijert.org/research/secure-localization-the-review-on-possible-attacks-of-wsn-and-their-remedy-IJERTV2IS80706.pdf The entire field of wireless network security is vast and in an evolutionary stage. Secure localization of nodes in a Wireless Sensor Network (WSN) is an important research subject. When WSNs are deployed in hostile environments, many attacks happen, e.g., wormhole, sinkhole and Sybil attack. Some of them are attack on nodes and some of them are attack on information. So it is necessary to know about all possible attacks and their remedy. In this paper, we depict the attack model and talk about different types of node and doable common attacks against secure localization i.e. attacks on nodes and attacks on information. As well as we do the survey and try to find out the solutions on each attacks.
Secure localization in wireless sensor networks
2007
ABSTRACT Wireless sensor networks have very promising future to many applications. Ensuring that sensor nodes locations are verified and are protected from malicious attacks will enable sensor networks deployment in mission critical applications. Due to the deployment nature, sensor nodes are highly vulnerable to localization attacks where an adversary can capture the nodes, changes its location or replaces it with a malicious node.
Pollution Attack: A New Attack Against Localization in Wireless Sensor Networks
2009 IEEE Wireless Communications and Networking Conference, 2009
Many secure localization algorithms have been proposed. In these algorithms, collusion attack is usually considered as the strongest attack when evaluating their performance. Also, for ensuring correct localization under the collusion attack, a necessary number of normal beacons are needed and a lower bound on this number has been established (assuming the errors of distance measurements are ignorable). In this paper, we introduce pollution attack, a more powerful attack which can succeed even when the number of normal beacons is more than the lower bound. In this attack, victim node is misled to a special chosen location, which results in a confusion of compromised beacon with normal beacon. We propose a new metric to measure the vulnerability of a normal location reference set to pollution attack, and develop two algorithms to efficiently compute the value of the proposed metric. We also present a method to judge whether the output of the localization algorithm is credible under pollution attack. Simulation results show that the pollution attack can succeed with high probability.