Detection And Prevention Of Sinkhole Attack On Zone Routing Protocol

Electronic technology is growing at a rapid rate; more devices are made mobile and wireless, but with those improvement and developments come flaws and malicious opportunities. Cyber attacks are on the rise and no system or device is immune. Many organizations employ multiple layers of firewalls but that doesn’t completely eliminate the threat. Attacks against firewalls and virtual private networks or VPNs are constantly being exploited with new methods everyday, but they are yet another obstacle that a cyber criminal must overcome.

Security is always the main issue for a network, when it is a wireless system the security becomes the main concern for a user. A wireless P2P network is suffering from mainly two security attacks i) Virus Attack ii) Intruders. Intruder does not only mean it want to hack the private information over the network, it also include to use a node bandwidth and increase the Delay of Service for other host over the network. This work is basically based on such type of attack. There are some system that exists on same attack model by comparing the hop time and some other means. But in all such system the Detection system is performed on a centralized system. We are proposing and intelligent predictive system

With the increasing dependency on wireless networks, the need for proper reliability analysis for Mobile ad hoc networks (Manets) is also increasing. Failure of Manets in areas like warfare, nuclear reactors, medical equipment and airplanes can lead to catastrophe. Unlike traditional networks, measuring the reliability of Manets is a tedious task as it involves dynamically changing topology. The existing methods for calculating reliability use two terminal analysis as the basis for calculation. It uses the same method used for traditional computer networks to calculate reliability. However, the method is not very efficient when it comes to the wireless networks as they are far different from traditional networks. It is also a time consuming task to identify all the nodes and links in a wireless network as nodes move freely in the network. In This paper, We are going to discuss about NLN(Node-Link-Node) technique which reduces the complexity of analyzing the reliability in Manets.

The exponential increase use of the Internet to communicate, conduct business transactions, access personal banking, healthcare, education at confront of being anywhere has become an everyday lifestyle for many people around the globe. This reliance on computers, laptops, devices and other Internet of Things to access the Internet means, organizations, businesses and the government have also seen an increase occurrence of sophisticated attacks.

MANETs (Mobile ad-hoc network) is defined as autonomous collection of wireless mobile nodes that are self-configure to construct a network that can communicate over relatively bandwidth constrained wireless links.

This work is based on to detect the malicious nodes from the network which are responsible to trigger grayhole attack in the network. The grayhole is the distributed denial of service attack in which

Attacks on wireless networks are generally designed to compromise the confidentiality and integrity of data, as well as reduce the availability of the network. Network attacks essentially fit into two main categories: passive or active. Passive attacks are those in which an attacker obtains information as it is transmitted over the network for the express purpose of reading the message content, or for traffic analysis. These types of attacks are usually difficult to detect since there is no modification of the data by the attacker. On the other hand, active attacks consist of an attacker modifying data or even sometimes injecting fraudulent data packets into the network. These types of attacks can result in severe damage for the victims. The following figure represents a general classification of network attacks.

In Today’s world multiple Wireless Local Area Networks (WLANs) can coexist in a airspace. Every wireless mobility devices tries to find the access point through probe request using a unique name that is the Service Set Identifier (SSID) of the network to make automatic authentication. As a wireless user you are concerned only with the broadcast SSIDs that let you connect to a WLAN. This paper discusses about the Wireless Mobility devices communication security issues using Basic Service Set Identifier BSSID or Extended Service Set Identifier ESSID which a network administrator need to keep track of. Also it discusses about the available flaws in it and how by modifying the probe request header we can make the connectivity more secure for the new generation of devices.

802.11 wireless Local Area Network (WLAN) becomes most important these days. Whether it would be simple range extender for a home wired Ethernet interface, or as a wireless interface, WLAN provides mobility, ease of access and affordable. Most of the 802.11 wireless network uses the frequency of 2.4GHz, which leads the network to be unsafe and more vulnerable than traditional Ethernet networks. In general, security issues for the Network layer has been discussed rapidly, but where as for MAC layer security mechanisms has not been extensively discussed. Wireless network security has gained attention due to the vulnerabilities exposed in the open communication platform. Most prevalent wireless Medium Access Control (MAC) protocol is IEEE 802.11, which considers all the nodes in the network are safe & cooperative. However, attackers may make nodes misbehave in order to disrupt network performance, obtain extra bandwidth and consume resources. These MAC layer misbehaviors can be called as Denial of Service (DoS) attacks which can disrupt the network operation. Influencing security flaws in the IEEE 802.11 MAC protocol even an average person with basic knowledge on wireless networks can launch MAC-layer denial of service (DOS) attacks. In this paper we study two types of MAC layer Denial Of Service attacks that can be easily operated by an

The expanded probability of listening in, caricaturing, and denial‐of‐service assaults ought to be deliberately considered. Existing connection security procedures are frequently connected inside of remote systems to decrease security dangers. As an advantage, the decentralized way of system control in MANETs gives extra vigor against the single purposes of disappointment of more incorporated methodology

[3] focuses on grey hole attack. Grey hole attack affects the routing services provided by the network. Adhoc-on-demand (AODV) protocol is used for routing of data packets. This paper discusses about the security issues and also the layered architecture of Manet. This paper also gives the various applications of Manet. It also briefs the various work done in the area of adhoc network.

Limited security in wireless sensor networks has led to a number of attacks come to prominence. Ameen et al (2012) identify the most common transmission threats to wireless sensor networks which include data modification, impersonation attacks, eavesdropping, and replaying (p. 97). Kumar and Lee (2012) specify routing threats in wireless sensor networks which they identify as follows:

Abstract :- Survivability of network is its ability of being connected even below failures and attacks. Activity procedure of a device network at intervals the hostile setting leads it to battery drain attacks, as it is not attainable to recharge and even replace device node 's battery power. The motivation provided for the analysis efforts has been given by a plan maximization of network amount, where the amount of network is live of the instant of activity to the aim. Once any of the nodes has exhausted its restricted power offer and becomes in-operational commonly referred as first node failure. Even a completely unique approach for routing protocols, have an impression on from attacks those unit designed to be protected, unit unable to

It is interesting that the biologically inspired approaches to network security because of their similarities between network security and human body resistant to pathogenic attacks. Wireless sensor network is based on low cost and low energy sensor nodes which are connected to physical signals. Such networks are made up of sensors and gateways the data to the end user. This paper used the wireless sensor network nodes and machine learning techniques to distinguish between fake and genuine nodes then desired the inspiration from the human immune system to prevent the role of virtual anti-bodies in system to avoid the fake nodes.

To accomplish availability and reliability network routing protocols should be prevailing compared to jamming attacks. The trustworthiness of distributing data packets from end to end using multi-hop intermediary nodes is a noteworthy problem in the mobile Adhoc network. Due to the intrinsically self-motivated nature of