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Virtual machines (VMs) are underlying technologies of IT solutions such as cloud computing. VMs provide\udease of use through their on-demand characteristics and provide huge benefits in terms of lowering costs and\udimproving scalability. VMs are also being used as malware detection systems, and with the rapidly expanding\udusage of mobile devices, besides of their usage as honeypots, VMs are coming to be used as emulators for\uddetecting malware in apps. This is due to the limited resources, such as processing power, available in mobile\uddevices. Currently, the security of applications for mobile devices is checked by running them in VM\udenvironments before they are released to the end user. We argue that such a process may cause or overlook\udserious security threats to the end user. In particular, if a piece of malware can detect its current running\udenvironment, it may change its behavior such that it doesn’t perform malicious operations in environments it\udsuspects to be emulators. In this way, when the malware detects that its running environment is on a VM, it\udmay be able to hide from the security system on the VM. This is a potential security hazard for end users,\udespecially users of mobile devices. In this paper, we present a VM detection method that we argue could be\udused for remotely detecting VM environments. The detection method works by analyzing the pattern of IP\udtimestamps in replies sent from the target environment. The method does not require any installation of\udsoftware on the target machine which further increase its potential harm if it were to be used by malware to\uddetect VM environments. In this paper, we also present a technique to disguise a real PC machine such that it\udshows the similar IP timestamp patterns as the VM. By using this technique, malware may not be able to\uddifferentiate between a real machine and a VM, thus providing protection to PC end users. \u

international journal of computer science and information technology/international journal of computer science and information technology  (chennai. print)

Virtual Machines Detection Methods Using IP Timestamps Pattern Characteristic