A game theoretic-based distributed detection method for VM-to-hypervisor attacks in cloud environment

Nezarat, Amin; Shams, Yaser

doi:10.1007/s11227-017-2025-7

Cited by 10 publications

(2 citation statements)

References 19 publications

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“…Eq. (10) shows the scheduled payoff of the defender, based on the attacked target in A. An upper bound of U Â t; C ð Þ is arranged on d, only for the attacked target.…”

Section: Compact Security Game Modelmentioning

confidence: 99%

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Randomized MILP framework for Securing Virtual Machines from Malware Attacks

Mangalagowri¹,

Venkataraman²

2023

Intelligent Automation &Amp; Soft Computing

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Cloud computing involves remote server deployments with public network infrastructures that allow clients to access computational resources. Virtual Machines (VMs) are supplied on requests and launched without interactions from service providers. Intruders can target these servers and establish malicious connections on VMs for carrying out attacks on other clustered VMs. The existing system has issues with execution time and false-positive rates. Hence, the overall system performance is degraded considerably. The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server's position so that the opponent cannot track the target server beyond a certain point. Every request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server's position. Allocation of SECURITY Resources accepts a safety game in a simple format as input and finds the best coverage vector for the opponent using a Stackelberg Equilibrium (SSE) technique. A Mixed Integer Linear Programming (MILP) framework is used in the algorithm. The VM challenge is reduced by a firewall-based controlling mechanism combining behavior-based detection and signature-based virus detection. The proposed method is focused on detecting malware attacks effectively and providing better security for the VMs. Finally, the experimental results indicate that the proposed security method is efficient. It consumes minimum execution time, better false positive rate, accuracy, and memory usage than the conventional approach.

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“…Eq. (10) shows the scheduled payoff of the defender, based on the attacked target in A. An upper bound of U Â t; C ð Þ is arranged on d, only for the attacked target.…”

Section: Compact Security Game Modelmentioning

confidence: 99%

“…In cloud platforms, multiple customers may share a single physical host, making separation even more essential. The guest VM's data must be safeguarded against threats posed by other guests [10]. DoS (Denial of Service) attacks that are executed against hosts at VMs need to be controlled, as they affect entire VMs servers.…”

Section: Introductionmentioning

confidence: 99%

Randomized MILP framework for Securing Virtual Machines from Malware Attacks

Mangalagowri¹,

Venkataraman²

2023

Intelligent Automation &Amp; Soft Computing

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Enhancing Data Security in the User Layer of Mobile Cloud Computing Environment: A Novel Approach

Ogwara

Petrova

Yang

et al. 2021

Advances in Security, Networks, and Internet of Things

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This paper reviews existing Intrusion Detection Systems (IDS) that target the Mobile Cloud Computing (MCC), Cloud Computing (CC), and Mobile Device (MD) environment. The review identifies the drawbacks in existing solutions and proposes a novel approach towards enhancing the security of the User Layer (UL) in the MCC environment. The approach named MINDPRES (Mobile-Cloud Intrusion Detection and Prevention System) combines a host-based IDS and network-based IDS using Machine Learning (ML) techniques. It applies dynamic analysis of both device resources and network traffic in order to detect malicious activities at the UL in the MCCenvironment. Preliminary investigations show that our approach will enhance the security of the UL in the MCC environment. Our future work will include the development and the evaluation of the proposed model across the various mobile platforms in the MCC environment.

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Detection of Suspicious Activities at Hypervisor in Cloud Computing: A Brief Study

Anumukonda,

Yadav,

2024

Intelligent Systems Design and Applications

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A game theoretic-based distributed detection method for VM-to-hypervisor attacks in cloud environment

Cited by 10 publications

References 19 publications

Randomized MILP framework for Securing Virtual Machines from Malware Attacks

Randomized MILP framework for Securing Virtual Machines from Malware Attacks

Enhancing Data Security in the User Layer of Mobile Cloud Computing Environment: A Novel Approach

Detection of Suspicious Activities at Hypervisor in Cloud Computing: A Brief Study

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