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| Flow Analysis for a Live APT Detection - Data at Rest Analysis
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Abdullah Said AL-Aamri, Rawad Abdulghafor, Akram M Z M Khedher, Shuhaili Bt Talib
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Abstract:
Smartness of the new era, the era of technology, is set on an ad-hoc architecture, to deliver a variety of known and unknown services, where the difficulty of achieving sustainable, secure, and trustworthy data transmission is a big challenge. Even within the industrial sector, it is considered that digital content delivery is smart enough and suits the nowadays definition of the smart city. Thus, such projects and systems do need two extremities, front end application and a back-end application. Regarding the front-end part, it needs to be adequate for different situations and different user skills. And also, here, we have to be aware that if we want to be practical, software applications and system applications are to be customized [1]. Building a smart environment is a concern, and through this research, we come out with a proven prognostication in a well-designed system, combining the strength of a two-party relationship, machine learning analytics standards, and dedicated and customized hardware to our research. The physical study of AI is not getting the incremental and positive growth it should be, while looking at the digital commerce industry, it is getting strong positive growth in the scientific services. In this research, we have to define our constraints which are used to measure environmental changes in the pre-given parameters; isolated zones, flows of data, etc. Those measures are remarkable points being detected and isolated among different schemas. Thus, the success of such research is a step forward in the context of a secure environment and, more precisely, in the APT detection industry.
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