Big Data Based Security Analytics for Protecting Virtualized Infrastructures in Cloud Computing

Win, Thu Yein; Tianfield, Huaglory; Mair, Quentin

doi:10.1109/tbdata.2017.2715335

Cited by 55 publications

(26 citation statements)

References 16 publications

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“…Existing malware detection approaches usually involve two steps: first, monitoring hooks are placed at different points within the virtualized infrastructure, and then a regularly updated attack signature database is used to determine attack presence [18]. Some of the relevant work is described below.…”

Section: Existing Malware Detection Methods In Virtualizedmentioning

confidence: 99%

Secure Virtualization Environment Based on Advanced Memory Introspection

Zhang

Meng

Wang

et al. 2018

Security and Communication Networks

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Most existing virtual machine introspection (VMI) technologies analyze the status of a target virtual machine under the assumption that the operating system (OS) version and kernel structure information are known at the hypervisor level. In this paper, we propose a model of virtual machine (VM) security monitoring based on memory introspection. Using a hardware-based approach to acquire the physical memory of the host machine in real time, the security of the host machine and VM can be diagnosed. Furthermore, a novel approach for VM memory forensics based on the virtual machine control structure (VMCS) is put forward. By analyzing the memory of the host machine, the running VMs can be detected and their high-level semantic information can be reconstructed. Then, malicious activity in the VMs can be identified in a timely manner. Moreover, by mutually analyzing the memory content of the host machine and VMs, VM escape may be detected. Compared with previous memory introspection technologies, our solution can automatically reconstruct the comprehensive running state of a target VM without any prior knowledge and is strongly resistant to attacks with high reliability. We developed a prototype system called the VEDefender. Experimental results indicate that our system can handle the VMs of mainstream Linux and Windows OS versions with high efficiency and does not influence the performance of the host machine and VMs.

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Section: Existing Malware Detection Methods In Virtualizedmentioning

confidence: 99%

Secure Virtualization Environment Based on Advanced Memory Introspection

Zhang

Meng

Wang

et al. 2018

Security and Communication Networks

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“…Win 等 [336] 提出一种云环境下基于大数据技术的恶意软件和 rootkit 攻击实时检测框架, 利用 HDFS 存储从客户 VM 中采集的海量数据, 利用基于图的事件关联分析和基于 MapReduce 解析器的潜在攻击路径识别方法提取攻击特征, 进而利用基于逻辑回归和置信传播 (belief propagation) 的机器学习算法实现攻击检测.…”

Section: 基于大数据技术的服务与平台安全监管unclassified

Research progress on big data security technology

Chen¹,

Gao²,

Huilin³

et al. 2020

Sci. Sin.-Inf.

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Independence and controllability of big data security Chinese Science Bulletin 60, 427 (2015); Research progress in the complexity theory and algorithms of big-data computation SCIENTIA SINICA Informationis 46, 1255 (2016); Real-time intelligent big data processing: technology, platform, and applications SCIENCE CHINA Information Sciences 62, 082101 (2019); Research on theory and key technology of trusted computing platform security testing and evaluation SCIENCE CHINA Information Sciences 53, 434 (2010); Earth observation big data for climate change research

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“…Moreover, current methods and mechanisms for service provision vary from vendor to supplier. The IT team needs to develop a strategy for considering an important aspect of cloud computing, which can be a set of standard APIs that automate the entire service provisioning cycle from allocation to deallocation [28]- [30]. Although most users of the cloud platform want simpler approaches to copy/paste, the actual configuration of the service is too complex for the average user.…”

Section: Service Provisioningmentioning

confidence: 99%

Smart Resilient Security Framework and Solutions for Cloud-driven Digital Supply Networks

Srinivasan*,

Gupta,

Kumaran S

et al. 2019

IJITEE

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The cloud-based logistics services allow cost reduction, higher elasticity, flexibility, and maximum utilization of resources for performing high computations and data analytics. Logistics and security are complex issues with the corporate entities when these are to be used for taking critical issues. To understand these, this paper discusses a conceptualized, flexible security framework for cloud-driven digital supply chain in Agricultural. Moreover, a security enhancement layer is included at each layer of the cloud with a feasibility study on protecting user information in the logistics services ambiance. Also, the Data Residency for cloud-based logistics services is elaborated with Data Security analysis. Further, the article discusses the possible solutions to handle the security concerns of the logistic model.

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Big Data Based Security Analytics for Protecting Virtualized Infrastructures in Cloud Computing

Cited by 55 publications

References 16 publications

Secure Virtualization Environment Based on Advanced Memory Introspection

Secure Virtualization Environment Based on Advanced Memory Introspection

Research progress on big data security technology

Smart Resilient Security Framework and Solutions for Cloud-driven Digital Supply Networks

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