As individual and digital devices are developed in recent years, cyber crimes are also rapidly increasing. Risks of cyber crimes are higher when they occur in companies or government organizations.
As the world is transformed into advanced knowledge information society, conventional crimes are degenerated into cyber crimes abusing Internet and networks, and digital forensics are increasing exponentially. Particularly, criminals occasionally commit diverse financial crimes by intelligently abusing regulations with deep knowledge of laws related to financial crimes, such as money laundering and tax evasion.
The abnormal transaction detection system is designed to prevent crimes by detecting and tracking abnormal transaction data in real time based on rules through real-time analysis of integrated log data and transaction data.
Forensic technology in the big data era will require much more advanced level than now, and its importance will further increase.
Analysis of huge volume of data requires precision forensic technology as well as enhanced accuracy and speed in analysis through intelligent predictive analysis. In such big data environment, information security accident should be prevented, and forensic technology is needed for precise log analysis to rapidly and accurately solve it if an accident occurs.
– Example of financial accident (1):
The criminal obtains information needed for financial transaction using detour routes, such as hacking Web hard and e-mail, and leakage of personal information, which are relatively easier than attacking financial transaction by incapacitating security programs.
– Example of financial accident (2):
Crime methods are increasingly diversified as criminals ask for compensation by disguising as accidents after transferring personal certification means, abusing weak point in the Electronic Financial Transaction Act that financial companies are required to verify customer’s intentional accident or gross negligence when financial accident is occurred.
FDS system generates data mart to be suitable for FDS operation, and supports functions of assessing risks, managing risk models and reports by extracting, converting and refining log information produced by security agents and data in main systems and information systems.