CRIME DETECTION SYSTEM USING DATA MINING AND FORENSIC TECHNIQUES

Abstract

The system proposes a security system, named the Crime Detection System using Data Mining and
Forensic Techniques (CDSDM) at system call (SC) level, which creates personal profiles for users to keep track of
their usage habits as the forensic features. The CDSDM uses a local computational grid to detect malicious behaviors
in a real-time manner the proposed work is regarded with Digital forensics technique and crime detection mechanism.
The number of hacking and crime incidents is increasing each year. The system designed Crime Detection System
(CDS) that implements predefined algorithms for identifying the attacks over a network. Therefore, in this project, a
security system, named the Crime Detection System using Data Mining (CDSDM), is proposed to detect insider attacks
at SC level by using data mining and forensic techniques. By analyzing the corresponding system calls the system can
identify the user forensic features to improve the accuracy of crime detection and will able to port the CDSDM to a
parallel system to shorten detection response time.