Informatics Publishing Limited

R. Buvana Nayaki ¹, J. Mark Jain ¹

Affiliations
1 Computer Science and Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur-628215, IN

Abstract

The Insider Threat is minimally addressed by current information security practices, yet the insider poses the most serious threat to organization for various reasons. Forensic investigation of the malicious insider is a technique used to prove the presence of malicious insider with digital evidence. The first phase is the network monitoring and packet capturing. The information in a network are transferred using packets, these packets are monitored and captured and the important features are extracted. The administrator uses this network monitoring and packet investigation inorder to gather the needed information‘s. The Analyzation of the log files are performed inorder to extract the pattern from files. The extracted features from packets and the log files are compared and the patterns are extracted. The data pattern‘s are grouped into clusters to trace the anomaly, clusters are classified as legal and anomaly pattern with the help of clustering algorithm. If anomaly is traced the user‘s past activities are referred and a cross check is made with captured packets. The computational intelligence algorithm is used to provide the digital evidence by cross checking log and packets, with this algorithm the presence of Malicious Insider in the critical networks are proved.

Keywords

Insider Threat, Intelligence Analyses, Privacy, Data Mining, Network Forensics, Attack Pattern.

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D. Kesavaraja ¹, A. Suthan ², J. Mark Jain ¹

Affiliations
1 Department of Computer Science and Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, Tamilnadu, IN
2 Department of Computer Applications, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, Tamilnadu, IN

Abstract

Congestion control has been always a major problem when network and data transmission gets involved. With the emergence of cloud computing the same problem applies to cloud computing environment too. In this paper we consider the problem of congestion control in cloud web computing environment which support both multirate multicast sessions and unicast sessions. Our work proposes an efficient congestion control mechanism using genetic algorithm, which identifies service state information of the communication. A Subserver justifies packet speed labeled by identifier and it decides the rapidness in which the receiver should receive the packet. Based on the receiver's requirement speed, the sub server splits the packets and forwards it. Also it identifies service state information for allocating bandwidth to the receivers. We propose an architecture that significantly reduces this implementation complexity but still achieves approximately fair bandwidth allocations. The congestion-control mechanism takes into account the diverse user requirements when different receivers within a multicast session have proper fitness functions in GA, but does not require the network to have any knowledge about the receiver utility functions.

Keywords

Cloud Computing, Congestion Control, Genetic Algorithm, Multi Cast, Traffic Flow, Packet Transfer.

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