Intrusion Detection and Tolerance in Next Generation Wireless Network

Intrusion Detection and Tolerance in Next Generation Wireless Network

Deshraj Ahirwar (UIT RGPV, India), P. K. Shukla (University Institute of Technology, India), Kirti Raj Bhatele (UIT RGPV, India), Prashant Shukla (SIRT RGPV, India) and Sachin Goyal (UIT RGPV, India)
Copyright: © 2015 |Pages: 23
DOI: 10.4018/978-1-4666-8687-8.ch011
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Abstract

Organizations focuses IDPSes for respective purposes, e.g. identifying problems with security strategies, manually presented threats and deterring individuals from violating security policies. IDPSes have become a necessary technique to the security infrastructure of approximate each association. IDPSes typical record information interrelated to practical events, security administrators of essential observed events and construct write up. Many IDPSes can also respond to a detected threat by attempting to thwart it succeeding. These use several response techniques, which involve the IDPS restricting the attack, changing the security environment or the attack's content. Sensor node should diverge in size from a shoebox down to the small size, although functioning “motes” of genuine microscopic dimensions have to be formed. The cost of sensor nodes is variable, from a few to thousands of dollars, depend on the complexity of the sensor nodes. Size and cost constraints on sensor nodes represent in corresponding constraints on resources such as energy, memory, computational velocity and communications bandwidth. The arrangement of the WSNs alters itself from a star network to efficient multi-hop wireless mesh network. The proliferation technique between the hops of the network can be routing or flooding.
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Introduction

An intrusion detection system is a software application that monitors system activities for malicious policy violations and generates reports to a management station. IDS come up to in a “flavors” and move toward the goal of detecting suspicious traffic in different types. There are network based and host based intrusion detection systems. System should try to stop an intrusion attempt but it is not expected of a monitoring system. Intrusion detection and prevention systems are primarily listening on identifying possible incidents, logging information, and reporting attempts (Scarfone & Mell, 2007). A wireless sensor network of spatially distributed autonomous sensors to test environmental conditions, for example temperature, sound, pressure, etc. and to cooperatively pass data through the network to prime location. Modern networks are bi-directional. Development of wireless sensor networks was aggravated by military applications such as battlefield surveillance; presently networks are second-hand in many industrial and consumer applications, e.g. industrial process monitoring and control, machine health monitoring. The various Topologies is illustrated in Figure 1.

Figure 1.

Topologies of devices

The WSN is built of “nodes” – from a few to several hundreds or even thousands, Node is coupled to one sensors. Sensor network node has typically several parts: a radio transceiver with an internal antenna to an external antenna, a microcontroller, an electronic circuit for interfacing with the sensors and an energy source, the embedded form of energy harvesting. Sensor node may fluctuate in size from a shoebox down to the different size, although functioning “motes” of genuine microscopic dimensions to be displayed. The cost of sensor nodes is variable, A few to huge of dollars, depending on the difficult of the sensor nodes. Size and cost parameter (Nitin, Mattord, Verma, 2008) on sensor nodes generate in corresponding constraints on objects e.g. energy, memory, computational speed and communications bandwidth. Architecture of the WSNs be divert from a star network to powerful multi-hop wireless mesh network. The transmission strategies for hops of the network will be routing or flooding. Wireless sensor networks are rising research area.

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Anomaly-Based Intrusion Detection System

Anomaly-Based Intrusion Detection System, is for detecting computer intrusions and false use by monitoring system activity and identify as either normal or anomalous. It is based on heuristics, rather than patterns, Try to define any type of cybercrime. It conflicts to signature based systems used to perceive attacks.

In order to find attack traffic, the system should train to be aware of system activity. It can be skilled in several ways, mostly artificial intelligence (Heberlein, 1990) type techniques. Systems using neural networks proposes great effect. Second process is to characterize normal usage of the system comprises mathematical model, and flag any deviation from this as an attack. It shows strict anomaly recognition.

Some faults are in anomaly-based Intrusion Detection, identified as high false positive speed and the ability to be fooled by a correctly delivered attack. Efforts prepared to address for issues through tactics used by PAYL and MCPAD. The Interconnection among computing devices in wireless network is illustrated with the help of Figure 2.

Figure 2.

Interconnection of computing devices in wireless network

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