Malware Detection in Cloud Computing

Abstract

Detecting malicious software is a complex problem. The vast, ever-increasing ecosystem of malicious software and tools presents a daunting challenge for network operators and IT administrators. Antivirus software is one of the most widely used tools for detecting and stopping malicious and unwanted software. However, the elevating sophistication of modern malicious software means that it is increased challenging for any single vendor to develop signatures for every new threat. Indeed, a recent Microsoft survey found more than 45,000 new variants of backdoors, Trojans, and bots during the second half of 2006 [1]. In this paper, we suggest a new model for the detection functionality currently performed by host-based antivirus software. This paper is characterized by two key changes.  Malware detection as a network service: First, the detection capabilities currently provided by host-based antivirus software can be more efficiently and effectively provided as an in-cloud network service. Instead of running complex analysis software on every end host, we suggest that each end host runs a lightweight process to detect new files, send them to a network service for analysis, and then permit access or quarantine them based on a report returned by the network service.  Multi-detection techniques: Second, the identification of malicious and unwanted software should be determined by multiple, Different detection engines Respectively. Suggest that malware detection systems should leverage the detection capabilities of multiple, Collection detection engines to more effectively determine malicious and unwanted files. In the future, we will see an increase in the dependence of cloud computing as consumers increasingly move to mobile platforms for their computing needs. Cloud technologies have become possible by tuberculation in order to share physical server resources between multiple virtual machines (VMs). The advantages of this approach include an increase in the number of clients that can be served for every physical server and the ability to provide software as a service (SaaS). In this paper, previous work on malware detection had been presented, both conventional and in the presence of cloud as storage in order to determine the best approach for detection in the cloud [2]. We also argue the benefits of multiple detection throughout the cloud and present a new approach to coordinate detection across the cloud. Section II provides background and related work the research area, specifically: cloud technologies, security system in the cloud, malware detection and detection in the cloud. Section III, we explain our Proposed System. Section IV we show Remarks of our system. Finally, section V Conclusions the points raised in this paper and provide some ideas for future work.