A Primer on Intelligent Defense Mechanism to Counter Cloud Silent Attacks

Abstract

Cloud security is a key to both Cloud clients and vendors, and this has prodded intensified massive research around this domain. The contractual continuous Cloud security research is as well fuelled by the abrupt popping up of attacks that even extend to silent or stealth. Moreover these silent or stealth attacks are characterised by low observability along with bad traceability resulting in their difficulty detection, traceability and prevention. Due to the nature of silent or stealth attacks that have difficulty detection, traceability and prevention calibre, it means traditional and/or ordinary security mechanisms won’t be sufficient to compact such attacks. In turn the nearby remedy to tackle these attacks is to incorporate method(s) that can curb trends that has hidden patterns. This then calls for techniques that have capabilities for revealing hidden patterns, thus Hidden Markov Model will find its projected usage in the proposed model. As a way to offer maximum security when dealing with these sophisticated kinds of attacks, a conjuncture of cryptography will also be fused in the proposed model. A logical series of actions will be executed such that once a possible attack is sensed, then a proactive action is triggered to avoid an invasion by this attack. The intelligence is derived from the previously learning by Hidden Markov Model, although continuous active learning is still guaranteed as this algorithm carries the Machine Learning algorithm standards, along with the proactive action is triggered.