A Survey on Enterprise Network Security: Asset Behavioral Monitoring and Distributed Attack Detection

June 29, 2023 ยท The Cartographer ยท ๐Ÿ› IEEE Access

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Survey on Enterprise Network Security: Asset Behavioral Monitoring and Distributed Attack Detectio"

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Authors Minzhao Lyu, Hassan Habibi Gharakheili, Vijay Sivaraman arXiv ID 2306.16675 Category cs.CR: Cryptography & Security Cross-listed cs.NI Citations 22 Venue IEEE Access Last Checked 2 days ago
Abstract
Enterprise networks that host valuable assets and services are popular and frequent targets of distributed network attacks. In order to cope with the ever-increasing threats, industrial and research communities develop systems and methods to monitor the behaviors of their assets and protect them from critical attacks. In this paper, we systematically survey related research articles and industrial systems to highlight the current status of this arms race in enterprise network security. First, we discuss the taxonomy of distributed network attacks on enterprise assets, including distributed denial-of-service (DDoS) and reconnaissance attacks. Second, we review existing methods in monitoring and classifying network behavior of enterprise hosts to verify their benign activities and isolate potential anomalies. Third, state-of-the-art detection methods for distributed network attacks sourced from external attackers are elaborated, highlighting their merits and bottlenecks. Fourth, as programmable networks and machine learning (ML) techniques are increasingly becoming adopted by the community, their current applications in network security are discussed. Finally, we highlight several research gaps on enterprise network security to inspire future research.
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