12,330 research outputs found
Anomaly Detection in Wireless Sensor Networks Based on Improved GM Model
Aiming at the problems of poor detection effect, high rate of missed detection and high rate of false detection in traditional methods, an anomaly detection method for wireless sensor networks based on improved GM model is proposed. The multilateral measurement method is used to locate the nodes in the wireless sensor network, and the state tracking of the running track of the located nodes is carried out. According to the tracking results, the self similarity between nodes is measured by Hurst index. Based on the measurement results, the improved GM model is used to predict the abnormal nodes. The abnormal values of the wireless sensor network are calculated by the distance between adjacent points, and the state of the current node is judged, this completes the anomaly detection of wireless sensor networks. The experimental results show that the proposed method is effective in anomaly detection of wireless sensor networks, and the rate of missed detection and false detection is low
Hierarchical Design Based Intrusion Detection System For Wireless Ad hoc Network
In recent years, wireless ad hoc sensor network becomes popular both in civil
and military jobs. However, security is one of the significant challenges for
sensor network because of their deployment in open and unprotected environment.
As cryptographic mechanism is not enough to protect sensor network from
external attacks, intrusion detection system needs to be introduced. Though
intrusion prevention mechanism is one of the major and efficient methods
against attacks, but there might be some attacks for which prevention method is
not known. Besides preventing the system from some known attacks, intrusion
detection system gather necessary information related to attack technique and
help in the development of intrusion prevention system. In addition to
reviewing the present attacks available in wireless sensor network this paper
examines the current efforts to intrusion detection system against wireless
sensor network. In this paper we propose a hierarchical architectural design
based intrusion detection system that fits the current demands and restrictions
of wireless ad hoc sensor network. In this proposed intrusion detection system
architecture we followed clustering mechanism to build a four level
hierarchical network which enhances network scalability to large geographical
area and use both anomaly and misuse detection techniques for intrusion
detection. We introduce policy based detection mechanism as well as intrusion
response together with GSM cell concept for intrusion detection architecture.Comment: 16 pages, International Journal of Network Security & Its
Applications (IJNSA), Vol.2, No.3, July 2010. arXiv admin note: text overlap
with arXiv:1111.1933 by other author
Intrusion-aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks
Existing anomaly and intrusion detection schemes of wireless sensor networks
have mainly focused on the detection of intrusions. Once the intrusion is
detected, an alerts or claims will be generated. However, any unidentified
malicious nodes in the network could send faulty anomaly and intrusion claims
about the legitimate nodes to the other nodes. Verifying the validity of such
claims is a critical and challenging issue that is not considered in the
existing cooperative-based distributed anomaly and intrusion detection schemes
of wireless sensor networks. In this paper, we propose a validation algorithm
that addresses this problem. This algorithm utilizes the concept of
intrusion-aware reliability that helps to provide adequate reliability at a
modest communication cost. In this paper, we also provide a security resiliency
analysis of the proposed intrusion-aware alert validation algorithm.Comment: 19 pages, 7 figure
Distributed CESVM-DR anomaly detection for wireless sensor network
Nowadays, the advancement of the sensor technology, has introduced the smart living community where the sensor is communicating with each other or to other entities. This has introduced the new term called internet-of-things (IoT). The data collected from sensor nodes will be analyzed at the endpoint called based station or sink for decision making. Unfortunately, accurate data is not usually accurate and reliable which will affect the decision making at the base station. There are many reasons constituted to the inaccurate and unreliable data like the malicious attack, harsh environment as well as the sensor node failure itself. In a worse case scenario, the node failure will also lead to the dysfunctional of the entire network. Therefore, in this paper, an unsupervised one-class SVM (OCSVM) is used to build the anomaly detection schemes in recourse constraint Wireless Sensor Networks (WSNs). Distributed network topology will be used to minimize the data communication in the network which can prolong the network lifetime. Meanwhile, the dimension reduction has been providing the lightweight of the anomaly detection schemes. In this paper Distributed Centered Hyperellipsoidal Support Vector Machine (DCESVM-DR) anomaly detection schemes is proposed to provide the efficiency and effectiveness of the anomaly detection schemes
Sleep Deprivation Attack Detection in Wireless Sensor Network
Deployment of sensor network in hostile environment makes it mainly
vulnerable to battery drainage attacks because it is impossible to recharge or
replace the battery power of sensor nodes. Among different types of security
threats, low power sensor nodes are immensely affected by the attacks which
cause random drainage of the energy level of sensors, leading to death of the
nodes. The most dangerous type of attack in this category is sleep deprivation,
where target of the intruder is to maximize the power consumption of sensor
nodes, so that their lifetime is minimized. Most of the existing works on sleep
deprivation attack detection involve a lot of overhead, leading to poor
throughput. The need of the day is to design a model for detecting intrusions
accurately in an energy efficient manner. This paper proposes a hierarchical
framework based on distributed collaborative mechanism for detecting sleep
deprivation torture in wireless sensor network efficiently. Proposed model uses
anomaly detection technique in two steps to reduce the probability of false
intrusion.Comment: 7 pages,4 figures, IJCA Journal February 201
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