Reconfigurable Architecture for Elliptic Curve Cryptography Using FPGA

The high performance of an elliptic curve (EC) crypto system depends efficiently on the arithmetic in the underlying finite field. We have to propose and compare three levels of Galois Field , , and . The proposed architecture is based on Lopez-Dahab elliptic curve point multiplication algorithm, which uses Gaussian normal basis for field arithmetic. The proposed is based on an efficient Montgomery add and double algorithm, also the Karatsuba-Ofman multiplier and Itoh-Tsujii algorithm are used as the inverse component. The hardware design is based on optimized finite state machine (FSM), with a single cycle 193 bits multiplier, field adder, and field squarer. The another proposed architecture is based on applications for which compactness is more important than speed. The FPGA’s dedicated multipliers and carry-chain logic are used to obtain the small data path. The different optimization at the hardware level improves the acceleration of the ECC scalar multiplication, increases frequency and the speed of operation such as key generation, encryption, and decryption. Finally, we have to implement our design using Xilinx XC4VLX200 FPGA device

An Intrusion Detection Using Machine Learning Algorithm Multi-Layer Perceptron (MlP): A Classification Enhancement in Wireless Sensor Network (WSN)

During several decades, there has been a meteoric rise in the development and use of cutting-edge technology. The Wireless Sensor Network (WSN) is a groundbreaking innovation that relies on a vast network of individual sensor nodes. The sensor nodes in the network are responsible for collecting data and uploading it to the cloud. When networks with little resources are deployed harshly and without regulation, security risks occur. Since the rate at which new information is being generated is increasing at an exponential rate, WSN communication has become the most challenging and complex aspect of the field. Therefore, WSNs are insecure because of this. With so much riding on WSN applications, accuracy in replies is paramount. Technology that can swiftly and continually analyse internet data streams is essential for spotting breaches and assaults. Without categorization, it is hard to simultaneously reduce processing time while maintaining a high level of detection accuracy. This paper proposed using a Multi-Layer Perceptron (MLP) to enhance the classification accuracy of a system. The proposed method utilises a feed-forward ANN model to generate a mapping for the training and testing datasets using backpropagation. Experiments are performed to determine how well the proposed MLP works. Then, the results are compared to those obtained by using the Hoeffding adaptive tree method and the Restricted Boltzmann Machine-based Clustered-Introduction Detection System. The proposed MLP achieves 98% accuracy, which is higher than the 96.33% achieved by the RBMC-IDS and the 97% accuracy achieved by the Hoeffding adaptive tree

Microsoft Word - 52-225.doc

Abstract: Quantum dot Cellular Automata (QCA) offers a new transistorless computing paradigm in nanotechnology. It has the potential for attractive features such as faster speed , smaller size and low power consumption than transistor based technology .By taking the advantages of QCA we are able to design interesting computational architecture. The basic logic elements used in this technology are the inverter and the majority gate (MG). The majority gate is not a universal gate .Hence another important logic gate introduced in this technology is And-Or-Inverter (AOI).In this paper, we propose design of different logical structures using AOI. The rules are introduced in this paper for easy implementation of AOI circuits for different functions and characteristics of AOI is also defined and analyzed. Design implementations using the AOI gate are compared with the conventional CMOS and majority gate based QCA methodology

A SURVEY ON ENERGY EFFICIENT MODULATION AND CODING TECHNIQUES FOR WIRELESS SENSOR NETWORKS

Abstract: A standard Wireless Sensor Network comprises of a huge number of sensor nodes with data processing and communication capabilities. The sensor nodes pass the gathered data using radio transmitter, to a sink either straightforwardly or through other nodes in a multihop approach. Wireless sensor network is a power consuming system, since nodes perform on restricted power batteries which decreases its lifetime. Optimally selected modulation and coding is extremely vital technique in wireless sensor networks. This paper surveys the performance of differentmodulation schemes and error control codes used in sensor networks. The survey also analyzes the role of modulation and coding techniquesto improve the energy efficiency, bandwidth efficiency and lifetime of the sensor nodes