Detection and Classification of Malicious Threats in Cloud Computing Using Ensemble Method

Abstract

Cloud computing is a highly-preferred option for organizations around the newlineglobe, it is very scalable and internet based computing resource provided in the form newlineof flexible services. Security is a key concern factor in any cloud solution due to its newlinedistributed nature. Security and privacy are huge obstacles faced in its success for the newlineon-demand service as it is easily vulnerable to intruders for any kind of attacks. In newlinerecent years, statistical reports have revealed a large number of security breaches that newlineoccurred in the virtual network layer of cloud computing. A huge upsurge in network newlinetraffic has paved the way to security breaches which are more complicated and newlinewidespread in nature. Tackling these attacks has become inefficient application of newlinetraditional network-based intrusion detection systems (IDS) environment. In today s newlinescenario, varied intrusion detection system (IDS) tools and techniques are available newlinein cloud platform as the typical technique to discover attacks on cloud infrastructure. newlineThe traditional or existing intrusion detection systems (IDS) is turning out to be newlineineffective and inefficient due to heavy traffic and its dynamic behavior. These newlinereasons have given rise to develop an innovative way to enhance the intrusion newlinedetection system in cloud computing newline