Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Virtual machine introspection based spurious process detection in virtualized cloud computing environment(Institute of Electrical and Electronics Engineers Inc., 2015) M.a, M.A.; Jaidhar, C.D.Virtual Machines are prime target for adversary to take control by exploiting the identified vulnerability present in it. Due to increasing number of Advanced Persistent Attacks such as malware, rootkit, spyware etc., virtual machine protection is highly challenging task. The key element of Advanced Persistent Threat is rootkit that provides stealthy control of underlining Operating System (kernel). Protecting individual guest operating system by using antivirus and commercial security defense mechanism is cost effective and ineffective for virtualized environment. To solve this problem, Virtual Machine Introspection has emerged as one of the promising approaches to secure the state of the virtual machine. Virtual Machine Introspection inspects the state of multiple virtual machines by operating outside the virtual machine i.e. at hypervisor level. In this work, Virtual Machine Introspection based malicious process detection approach is proposed. It extracts the high level information such as system call details, opened known backdoor ports from introspected memory to identify the spurious process. It triggers an alert in response to detected intrusion. © 2015 IEEE.Item Hypervisor and virtual machine dependent Intrusion Detection and Prevention System for virtualized cloud environment(Institute of Electrical and Electronics Engineers Inc., 2015) M.a, M.A.; Jaidhar, C.D.Cloud Computing enabled by virtualization technology exhibits revolutionary change in IT Infrastructure. Hypervisor is a pillar of virtualization and it allows sharing of resources to virtual machines. Vulnerabilities present in virtual machine leveraged by an attacker to launch the advanced persistent attacks such as stealthy rootkit, Trojan, Denial of Service (DoS) and Distributed Denial of Service (DDoS) attack etc. Virtual Machines are prime target for malignant cloud user or an attacker to launch attacks as they are easily available for rent from Cloud Service Provider (CSP). Attacks on virtual machine can disrupt the normal operation of cloud infrastructure. In order to secure the virtual environment, defence mechanism is highly imperative at each virtual machine to identify the attacks occurring at virtual machine in timely manner. This work proposes In-and-Out-of-the-Box Virtual Machine and Hypervisor based Intrusion Detection and Prevention System for virtualized environment to ensure robust state of the virtual machine by detecting followed by eradicating rootkits as well as other attacks. We conducted experiments using popular open source Host based Intrusion Detection System (HIDS) called Open Source SECurity Event Correlator (OSSEC). Both Linux and windows based rootkits, DoS attack, Files integrity verification test are conducted and they are successfully detected by OSSEC. © 2015 IEEE.Item Execution time measurement of virtual machine volatile artifacts analyzers(IEEE Computer Society help@computer.org, 2016) M.a, M.A.A.; Jaidhar, C.D.Due to a rapid revaluation in a virtualization environment, Virtual Machines (VMs) are target point for an attacker to gain privileged access of the virtual infrastructure. The Advanced Persistent Threats (APTs) such as malware, rootkit, spyware, etc. are more potent to bypass the existing defense mechanisms designed for VM. To address this issue, Virtual Machine Introspection (VMI) emerged as a promising approach that monitors run state of the VM externally from hypervisor. However, limitation of VMI lies with semantic gap. An open source tool called LibVMI address the semantic gap. Memory Forensic Analysis (MFA) tool such as Volatility can also be used to address the semantic gap. But, it needs to capture a memory dump (RAM) as input. Memory dump acquires time and its analysis time is highly crucial if Intrusion Detection System IDS (IDS) depends on the data supplied by FAM or VMI tool. In this work, live virtual machine RAM dump acquire time of LibVMI is measured. In addition, captured memory dump analysis time consumed by Volatility is measured and compared with other memory analyzer such as Rekall. It is observed through experimental results that, Rekall takes more execution time as compared to Volatility for most of the plugins. Further, Volatility and Rekall are compared with LibVMI. It is noticed that examining the volatile data through LibVMI is faster as it eliminates memory dump acquire time. © 2015 IEEE.