A. Kumaravel

An application of non-uniform cellular automata for efficient cryptography

One of the core issues for robust cryptographic systems is to deal with the rate of diffusion and distribution of keys. We try to strengthen this aspect by increasing the length of block ciphers. We present a new encryption and decryption algorithm for block cipher that supports 27 bit block size. All components in our system are chosen to be based on cellular automata so as to achieve higher parallelism and to simplify the in hardware and software implementation for applications with high degree of security. The main objective of this paper is to increase the complexity by novel schemes of mixing (reversible cellular automata) RCA and (non-uniform reversible cellular automata) NRCA. We apply set of different bit permutation methods for this purpose .This paper establishes the proof for existence of yet another approach for a high quality pseudorandom bit sequences generated by non uniform cellular automata.

Multi-classification approach for detecting network attacks

Intrusion Detection System (IDS) has increasingly become a crucial issue for computer and network systems. Intrusion poses a serious security risk in a network environment. The ever growing new intrusion types pose a serious problem for their detection. The acceptability and usability of Intrusion Detection Systems get seriously affected with the data in network traffic. A large number of false alarms mean a lot in terms of the acceptability of Intrusion Detection Systems[1].In this paper we consider the dataset with multi classes and propose the classification for each type of attacks in a separate layer. In this work, a multi-classification approach for detecting network attacks is designed and developed to achieve high efficiency and improve the detection and classification rate accuracy [6].

VehNode: Wireless Sensor Network platform for automobile pollution control

The strength of sensor networks is quite vast when it is applied for collecting physical data in real time and storing for further analysis. The impossible measurements by conventional methods have now become possible by using this technology. Air quality which is one of the most important factors for the sustainable development and is one of the challenging areas researchers dealt with long time. The major source of environment pollution happens to be Vehicular Pollution. The high influx of vehicles to urban areas, and conventional pollution control measures used by concerned agencies has led to the drastic increase of air pollution. Here we address this problem by introducing VehNode, a WSN based Vehicular pollution monitoring platform which is capable of measuring different types of pollutant concentrations contained in smoke produced by the vehicle and reports the status automatically whenever required to the concerned agencies. We assure the existence of Wireless Sensor Network platform for automobile pollution control focusing on an easy accessibility of real time data via the Web by following the Web of Things approach. This will form a basis to connect each vehicle as an entity for a web of things infrastructure enabling the direct interaction with existing web applications of the concerned agencies. The real time data will be available to three main groups of users: Owner of the Vehicle, Traffic department and national environmental agencies.