Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8610
Title: Comparison of Active Vulnerability Scanning vs. Passive Vulnerability Detection
Authors: Ecik, Harun
Keywords: active vulnerability scanning
passive vulnerability detection
Network security
Active vulnerability scanning
Identification tools
Integral part
Passive vulnerability detection
Security flaws
Security programs
Security weakness
Side effect
Vulnerability analysis
Vulnerability detection
Scanning
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Ecik, H. (2021, December). Comparison of Active Vulnerability Scanning vs. Passive Vulnerability Detection. In 2021 International Conference on Information Security and Cryptology (ISCTURKEY) (pp. 87-92). IEEE.
Abstract: Vulnerability analysis is an integral part of an overall security program. Through identifying known security flaws and weaknesses, vulnerability identification tools help security practitioners to remediate the existing vulnerabilities on the networks. Thus, it is crucial that the results of such tools are complete, accurate, timely and they produce vulnerability results with minimum or no side-effects on the networks. To achieve these goals, Active Vulnerability Scanning (AVS) or Passive Vulnerability Detection (PVD) approaches can be used by network-based vulnerability scanners. In this work, we evaluate these two approaches with respect to efficiency and effectiveness. For the effectiveness analysis, we compare these two approaches empirically on a test environment and evaluate their outcomes. According to total amount of accuracy and precision, the PVD results are higher than AVS. As a result of our analysis, we conclude that PVD returns more complete and accurate results with considerably shorter scanning periods and with no side-effects on networks, compared to the AVS. © 2021 IEEE.
Description: 14th International Conference on Information Security and Cryptology, ISCTURKEY 2021 -- 2 December 2021 through 3 December 2021 -- -- 175906
URI: https://doi.org/10.1109/ISCTURKEY53027.2021.9654331
https://hdl.handle.net/20.500.11851/8610
ISBN: 9781665407762
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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