Iraqi Journal of Information and communication technology

In this paper, a new technique is deployed to afford a strong secure algorithm based on dynamic keys strategy to enhance the security of network against cyber- attacks. The objective of this technique is to provide confidentiality and authentication of data between any partners. The proposed technique takes Multiple keys pair(Public and Private) with RSA algorithm which every key pair used to ensure the security of one communication session. Where the proposed technique enhances the communication system by defining a set of ciphers such that not only the key but also the cipher changes on every new data transaction. Simulation results have been achieved using MATLAB R2014a; Single Key RSA (SK- RSA) and proposed Multi Keys RSA (MK- RSA) are compared analysis is made on execution time and secrecy of the communication system. Hence, deploying the MK- RSA algorithm is proving more secure than SK- RSA algorithm with the advantage of no need time of execution for key generation in every communication sessions

The Internet has become open, public and widely used as a source of data transmission and exchanging messages between criminals, terrorists and those who have illegal motivations. Moreover, it can be used for exchanging important data between various military and financial institutions, or even ordinary citizens. One of the important means of exchanging information widely used on the Internet medium is the e- mail. Email messages are digital evidence that has been become one of the important means to adopt by courts in many countries and societies as evidence relied upon in condemnation, that prompts the researchers to work continuously to developىemail analysis tool using the latest technologies to find digital evidence from email messages to assist the forensic expertise into to analyze email groups. This work presents a distinct technique for analyzing and classifying emails based on data processing and extraction, trimming, and refinement, clustering, then using the SWARM algorithm to improve the performance and then adapting support vector machine algorithm to classify these emails to obtain practical and accurate results. This framework, also proposes a hybrid English lexical Dictionary (SentiWordNet3.0) for email forensic analysis, it contains all the sentiwords such as positive and negative and can deal with the Machine Learning algorithm. The proposed system is capable of learning in an environment with large and variable data to test the proposed system will be select available data which is Enron Data set. A high accuracy rate is 92%was obtained in best case. The experiment is conducted the Enron email dataset corpus (May 7, 2015 Version of the dataset)

Particular and timely unified information along with quick and effective query response times is the basic fundamental requirement for the success of any collection of independent data marts (data warehouse) which forms Fact Constellation Schema or Galaxy Schema. Because of the materialized view storage area, the materialization of all views is practically impossible thus suitable Materialized Views (MVs) picking is one of the intelligent decisions in designing a Fact Constellation Schema to get optimal efficiency. This paper presents a framework for picking best-materialized view using Quantum Particle Swarm Optimization (QPSO) algorithm where it is one of the stochastic algorithms in order to achieve the effective combination of good query response time and low query handling cost. The results reveal that the proposed method for picking best- materialized view using QPSO algorithm is better than other techniques via computing the ratio of query response time and compare it to the response time of the same queries on the MVs. Ratio of implementing the query on the base table takes five times more time than the query implementation on the MVs. Where the response time of queries through MVs access 0.084 seconds while by direct access queries 0.422 seconds. This outlines that the performance of query through MVs access is 402.38%better than those directly access via data warehouse-logical

In the long- term evolution(LTE) physical layer, using turbo code is considered the core of the error-correcting code. This paper presents an implementation of LTE turbo decoding using the Log- Maximum a posteriori (MAP) algorithm with reduced number of required cycles approximately by 75% based on serial to parallel operation. Additionally, an improvement for this algorithm based on polynomial regression function is done to reduce the implementation complexity. These system implementations, are designed with 40 bit block size of the input using Xilinx System Generator (XSG) to show its applicability in real time using two approaches; Hardware Co-Simulation and HDL Netlist based on three devices, Xilinx Kintex- 7, Spartan- 6 and Artix- 7.From the hardware implementation observation, the system becomes completely real time by the user control using the switches on the board. Also, this system has taken the resources utilization from the devices less than other works