Detecting and Locating Man-in-the-Middle Attacks in Fixed Wireless Networks

We propose a novel method to detect and locate a Man-in-the-Middle attack in a fixed wireless network by analyzing round-trip time and measured received signal strength from fixed access points. The proposed method was implemented as a client-side application that establishes a baseline for measured round trip time (RTTs) and received signal strength (RSS) under no-threat scenarios and applies statistical measures on the measured RTT and RSS to detect and locate Man-in-the-Middle attacks.We show empirically that the presence of a Man-in-the-Middle attack incurs a significantly longer delay and larger standard deviation in measured RTT compared to that measured without a Man-in-the-Middle attack.We evaluated three machine learning algorithms on the measured RSS dataset to estimate the location of a Man-in-the-Middle attacker.Experimental results show that the proposed method can effectively detect and locate a Man-in-the-Middle attack and achieves a mean location estimation error of 0.8 meters in an indoor densely populated metropolitanenvironment.</p

Prevention Of Session Hijacking And IP spoofing With Sensor Nodes And Cryptographic Approach

Many web applications available today make use of some way of session to be able to communicate between the server and client. Unfortunately, it is possible for an attacker to exploit session in order to impersonate another user at a web application. The session hijacking is the most common type of attack in the infrastructure type of network. The confidentially is not providing under this attack to user information. Session hijacking attack is launched by making fake access point. If we detect the fake access point then we can stop session hijacking, and various techniques had been proposed. In this paper, we are giving a new mechanism to detect the fake access point with the use of sensor nodes in the network. In this mechanism we are also giving the protection against IP Spoofing by the use of public private key cryptography key exchange algorithm. We also discuss the results through simulations in Network Simulator 2

Detecting man-in-the-middle and wormhole attacks in wireless mesh networks

Wireless networks are being used increasingly in industrial, health care, military and public-safety environments. In these environments security is extremely important because a successful attack against the network may pose a threat to human life. To secure such wireless networks against hostile attack requires both preventative and detective measures. In this paper we propose a novel intrusion detection mechanism that identifies man-in-the-middle and wormhole attacks against wireless mesh networks by external adversaries. A simple modification to the wireless MAC protocol is proposed to expose the presence of an adversary conducting a frame-relaying attack. We evaluate the modified MAC protocol experimentally and show the detection mechanism to have a high detection rate, no false positives and a small computational and communication overhead