IJRR

International Journal of Research and Review

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Review Article

Year: 2016 | Month: July | Volume: 3 | Issue: 7 | Pages: 12-19

Modern Approaches to Cyber Attack Detection

Ikporo Stephen C.

Department of Computer Science, Ebonyi State University, Abakaliki - Nigeria.

ABSTRACT

The world is quickly developing into a virtual environment known as cyberspace, where individuals can communicate with one another, or search for knowledge to broaden their horizons. However, some individuals use this cyberspace for their own devious actions, targeting unsuspecting individuals for their own enjoyment or profit. Cyber-attacks on computer and network system have continued to threaten the global information infrastructure, targeting data files, services, network or even service port.  The most dangerous aspect of these attacks is how sophisticated they have become in recent times, thereby almost defiling all countermeasures always employed to detect and prevent them.  Modern approach of cyber-attack detection is an advanced scientific technique deployed to prevent these sophisticated attacks on cyber networks which had become a serious threat to our network and cyberspace. There are some existing approaches used in detecting cyber-attacks on computers and networks such as signature recognition and anomaly detection and others. In this paper, a new approach to cyber-attack detection has been proposed so as to detect any type of cyber-attack. This approach uses attack-norm separation techniques for scientific discovery of data, features and characteristic of cyber signal and noise. Attack profiling and analytical discovery techniques are used to generalize the data, features and characteristics that exist in cyber-attack and norm data. Well established signal detection models are also leveraged in the physical space. It’s significant to the society is that it will enables us to take the least amount of relevant data necessary to achieve detection accuracy and efficiency.

Keywords: Cyber Attack, Cyber Space, Threat, Computer Network, Security Detection.

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