Research Methodology
3.1 Problem Definition
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
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4.2: Bloom Filter to add the destination IP address in bins to detect DDoS.
After that, it uses the concept of Bloom filter. Bloom filter is a data structure used to test whether an element is a member of a given set or not. It has a two-dimensional bin table of k levels by m bins with k independent hash functions. It is used to keep track of the recent arrival rates of packets of different destination IP addresses passing through a router within a sampling period t as shown in fig. 4.2. In proposed system, it stores the IP address in data structure and checks it on the behalf of misuse detection method. Once whole of the information is derived, the complete data is analyzed statistically by using association between the nodes respective to the current node.
Proposed system is a cooperative system in which each host will monitor its surrounding nodes and maintain a database about the transmission of its own as well as its neighbor nodes transmission.
MODULE DESCRIPTION
There are basic 4 different modules in which proposed system works:
DISTRIBUTED DETECTION
The basic idea is to set up a monitor at each node in the network to produce evidences and to share them among all the nodes .An evidence is a set of relevant information about the network
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Towards the end of 2013, OPM began to upgrade their cybersecurity polices. They added new tools and capabilities to various networks throughout their agency. The results of the new security upgrades, OPM was able to identify two different cybersecurity incidents on its systems. May of 2015 OPM discovered that their system has been under attack. Information such as background investigation records of current, former, and prospective Federal employees and contractors were stolen. After an extensive forensics investigation, it was determined that the types of information in these records include identification information such as Social Security Numbers, educational history, employment history, information about immediate family and other personal
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In order to avoid this problem, a technique called probability distribution algorithm is introduced. In probability distribution algorithm, the random traffic between the primary network users are analyzed. The nearby nodes behaviors are learnt by the secondary node. The probability of the traffic in the neighboring nodes are studied by the node that tries to transmit data. When the traffic is free then the secondary node establishes the connection. If there is traffic then the secondary node searches for other nodes. Thus the data transmission occurs in this CR
They function in IP security provision, inside and outside network attack detection, data recovery, risk analysis, attack patterns detection, future attacks prediction and detection of anomalies in the network system. The main properties of network forensics analysis tools include collection of information (Dhishan)[6].
Ad hoc networks are a new prototype of wireless communication for mobile hosts (which we call nodes).In an Ad hoc network, there is no fixed particular infrastructure such as base stations and mobile nodes. Mobile nodes that are within each other’s radio frequency range communicate directly via wireless links, while those that are far apart depend on other nodes to forward messages as routers. Ad hoc networks are peer to peer networks of mobile nodes. They are mostly used in sensor networks, habitat monitoring and robotic collaboration. In the recent times, Ad hoc networks have evoked increasing interest as adjustable distributed application environments. These days many people are using different types of wireless devices, such as laptops, mobile phones, PDAs (personal digital assistant) and mp3 players, as part of their professional and private lives. For the most part, these devices are used separately because the network applications do not interact. Ad hoc wireless communication between devices can be defined as a scheme, often indicated as the Ad hoc network, which allows devices to establish communication between the nodes anytime and anywhere to transfer data without the aid of a central infrastructure. The concepts of mobile Ad hoc networking along with its applications that can be envisioned are being described in this report. Ad hoc networking covers different types of positions in a communication. An Ad hoc Network framework can comprise of a
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.
The various detection methods are produced based on the mobility models and the network assumptions. Due to the resource constrained nature of the sensor nodes the detection methods encountered have following limitations. The paper presents the classification of various detection methods. Based on the mobility model also the detection methods have been classified which has been discussed in this paper. From the discussion it is found that Efficient Distributed Detection method suits well for detecting replicated nodes in the Wireless Sensor Networks.
In ad-hoc wireless network, mobile nodes are connected by wireless links. The network is an autonomous and self-configured. It doesn’t have fixed infrastructure or centralized management. The mobile nodes in network are free to move from one place to another. Each node has transmitter and receiver which is used to send and receives the data and communicates with other nodes which are in their communication range. If any node wants to forward packet to the node which is out of range, co-operation of other nodes required; this is known as multi-hop communication. In multi-hop communication message send and received by various intermediate nodes. The network topology frequently changes due to the mobility of nodes as they move within, move into, or move out of the network. In recent years, the ad-hoc wireless network rapidly increases being used in various applications i.e. military purpose, civilian and commercial uses without the fixed infrastructure and human interference.
Abstract: Wireless Sensor Network is a collection of homogeneous/heterogeneous wireless devices used to monitor the changes in the surrounding of the wireless device. Each wireless device present in the network has the capability of sensing the changes in the surrounding environment. Homogeneous sensors are those which have same computational power, energy etc. Each node is battery powered which is used to transmit the sensed data over the network. So efficient transmission of data in Wireless Sensor Network is important and to transmit the data unaltered over the network to the receiver security is important
Since data are transmitted wirelessly between sensor nodes, it is usually prone to eavesdropping and interception. It is important to maintain the privacy of data among sensor nodes even from trusted cooperating sensor nodes of the WSNs. It is necessary to prevent recovering the privacy of the data, even it is overheard or decrypted by the adversaries.
Abstract—Mobile Ad-hoc Network (MANET) is a kind of wireless network. A Wireless ad-hoc network is a temporary network with no network infrastructure. The nodes communicate with each other, they co-operate by forwarding data packets to other nodes in the network. Thus the nodes find a path to the destination node using routing protocols. Due to the security vulnerabilities of the routing protocols, wireless ad-hoc networks are unprotected to attacks of the malicious nodes. One of these attacks is the Sinkhole Attack. Sinkhole attack is a kind of routing attack in MANET. A sinkhole node tries to attract all the network packets to it-self from all neighboring nodes. This paper focuses on to detect and prevent sinkhole node. The detection techniques which make use of proactive routing protocol have better packet delivery ratio and correct detection probability. The detection techniques which make use of reactive routing protocols have low overheads, but have high packet loss problem. Therefore, using a hybrid detection technique which combines the advantages of