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An Efficient Threat Detection System for Mimicking Attacks in Cyberspace
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Botnet is one of the major reasons for malicious activities in cyberspace. It is a group of interconnected program that communicates with other programs in order to perform an illegal operation by botmaster through command and control mechanism, which leads to the possibility of stealing personal data such as mail accounts, bank accounts, credential details etc., Cyber behavior is the activities that human engage in interacting with internet. The attacker attacks the system as a genuine user by changing the proxy settings and performs their malicious activities. We proposed Mimicking Detection Algorithm which mainly focused on attacks such as Mimicking attack, flash crowd, DDOS and Information phishing attack from the client side by using statistical methodology for calculating the flow of page request. Fine correntropy is used for accurate detection and to measure the similarity between two random variables. Thus our approach is able to detect mimicking attacks from online cyber events.
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