Data Mining Technique to Data Collection and Analysis for Cyber Forensic

Abstract

In the world of Digital forensic the uncovered digital may contain vital information for digital data investigation for investigator. Digital data collected from the crime scene leads to find out the clue after performing analysis by the examiner. This process of data examination data collection and analysis plays important role in cyber world for the forensic investigator. The cybercrime is a part of computer forensics where the digital evidences are analyze by the investigator and to perform analysis special measurements and techniques are required in order to use this details that has to be accepted in court of law for law enforcement. The data collection of evidence is a key aspect for the investigator, such kind of digital data has to be collected from different sources at the crime scene and this process involves to collect each and every evidence of digital crime scene and later this gather data will be analyze by the experts to reach to the conclusion. In this paper the proposed method collected the data from the crime scene efficiently which includes log data, transactional data, physical drive data, and network data; later this collected data analyzed to find out the theft node in the network. In this paper FTK 4.0 digital forensic tool used to reduce plenty of time for data processing and later report will be produce that will be accepted tin the court of law. This paper also focuses the data collection method with in the network and reach to the faulty node and later this faulty node analyzed with all collected data for forensic analysis. For this standard algorithm used to analyze the performance of distinct features used for network attacks. Kmeans clustering methodology is used to create cluster of victim node and represent victim data in systematic manner for the ease of law enforcement.