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Research Paper | Computer Technology | India | Volume 8 Issue 11, November 2019 | Popularity: 4.7 / 10

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Strategies for Handling Cyber Threats and Ensuring Data Privacy in Distributed Memory Systems

Gnana Teja Reddy Nelavoy Rajendra

Abstract: In a world where data is increasingly important, distributed memory systems (DMS) are critical in the most advanced applications, such as cloud computing, big data analysis, and HPC. Such systems allow scalability, high performance, and resilience by distributing data and computing loads among many nodes. However, their decentralization poses great cybersecurity and data privacy threats. It, therefore, seeks to look at some of the biggest threats to distributed memory systems. DDoS attacks, data breaches, insider threats, and malware. It also gives broad ways to counter these risks and protect the data, from traditional encryption and MFA to the most innovative technologies of AI & ML. The paper focuses on a predictive model for security and a layered approach to control risks and protect data in distributed memory space.

Keywords: DMS, Cybersecurity, Data Privacy, Cloud Computing, Big Data Analytics, HPC, DDoS, Data Encryption, MFA, AI, ML, Zero - Trust Architecture, Malware, Insider Threats, Sharding, and Compliance are critical factors that define the technological environment

Edition: Volume 8 Issue 11, November 2019

Pages: 2046 - 2060

DOI: https://www.doi.org/10.21275/SR24918031411

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