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Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues
Journal of Information Security and Applications ( IF 5.6 ) Pub Date : 2020-09-15 , DOI: 10.1016/j.jisa.2020.102582
Shahab Shamshirband , Mahdis Fathi , Anthony T. Chronopoulos , Antonio Montieri , Fabio Palumbo , Antonio Pescapè

With the increasing utilization of the Internet and its provided services, an increase in cyber-attacks to exploit the information occurs. A technology to store and maintain user's information that is mostly used for its simplicity and low-cost services is cloud computing (CC). Also, a new model of computing that is noteworthy today is mobile cloud computing (MCC) that is used to reduce the limitations of mobile devices by allowing them to offload certain computations to the remote cloud. The cloud environment may consist of critical or essential information of an organization; therefore, to prevent this environment from possible attacks a security solution is needed. An intrusion detection system (IDS) is a solution to these security issues. An IDS is a hardware or software device that can examine all inside and outside network activities and recognize doubtful patterns that may demonstrate a network attack and automatically alert the network (or system) administrator. Because of the ability of an IDS to detect known/unknown (inside/outside) attacks, it is an excellent choice for securing cloud computing. Various methods are used in an intrusion detection system to recognize attacks more accurately. Unlike survey papers presented so far, this paper aims to present a comprehensive survey of intrusion detection systems that use computational intelligence (CI) methods in a (mobile) cloud environment. We firstly provide an overview of CC and MCC paradigms and service models, also reviewing security threats in these contexts. Previous literature is critically surveyed, highlighting the advantages and limitations of previous work. Then we define a taxonomy for IDS and classify CI-based techniques into single and hybrid methods. Finally, we highlight open issues and future directions for research on this topic.



中文翻译:

移动云计算环境中的计算智能入侵检测技术:审查,分类法和公开研究问题

随着互联网及其提供的服务利用率的提高,利用信息的网络攻击也随之增加。云计算(CC)是一种用于存储和维护用户信息的技术,该技术主要用于其简单性和低成本服务。此外,今天值得注意的一种新的计算模型是移动云计算(MCC),该模型用于通过允许移动设备将某些计算卸载到远程云来减少移动设备的限制。云环境可能包含组织的关键或必要信息;因此,为防止此环境可能受到攻击,需要一种安全解决方案。入侵检测系统(IDS)是针对这些安全问题的解决方案。IDS是一种硬件或软件设备,可以检查所有内部和外部网络活动,并识别出可能显示网络攻击的可疑模式,并自动向网络(或系统)管理员发出警报。由于IDS能够检测已知/未知(内部/外部)攻击,因此它是保护云计算的绝佳选择。入侵检测系统中使用了各种方法来更准确地识别攻击。与到目前为止提供的调查报告不同,本文旨在介绍对在(移动)云环境中使用计算智能(CI)方法的入侵检测系统的全面调查。我们首先提供CC和MCC范例和服务模型的概述,并在这些情况下回顾安全威胁。对以前的文献进行了严格的调查,强调以前工作的优点和局限性。然后,我们为IDS定义分类法,并将基于CI的技术分为单一方法和混合方法。最后,我们重点介绍了有关此主题的未解决问题和未来的研究方向。

更新日期:2020-09-15
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