Cyber Attack Detection with Encrypted Network Connection Analysis

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dc.authorscopusid57201743399
dc.authorscopusid57203142239
dc.authorscopusid6504413319
dc.authorscopusid57447588400
dc.authorscopusid56469924100
dc.contributor.authorGonen, Serkan
dc.contributor.authorKaracayilmaz, Gokce
dc.contributor.authorArtuner, Harun
dc.contributor.authorBariskan, Mehmet Ali
dc.contributor.authorYilmaz, Ercan Nurcan
dc.date.accessioned2024-09-11T19:58:24Z
dc.date.available2024-09-11T19:58:24Z
dc.date.issued2024
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description12th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2023 -- 26 May 2023 through 28 May 2023 -- Istanbul -- 302369en_US
dc.description.abstractThe evolution of science and technology has led to increasingly complex cyber security threats, with advanced evasion techniques and encrypted communication channels making attacks harder to detect. While encryption has improved privacy and confidentiality for users, it has also provided a new avenue for attackers to exploit. Traditional intrusion detection systems, which transitioned from signature-based to behavior-based approaches, have struggled to keep up with these challenges. To address this issue, researchers have turned to continuous system monitoring and network traffic packet analysis. However, this method can be resource-intensive and time-consuming, particularly when analyzing encrypted packets. In this study, the JA3 fingerprint infrastructure was examined as a potential solution for quickly detecting attacks conducted over encrypted sessions while minimizing system downtime and damage. The results demonstrated that the JA3 infrastructure effectively detected attacks carried out via encrypted channels. Although Windows 10 and Kali 2020.4 operating systems were used as the victim and attacker systems respectively, the methodology can be applied to other operating systems and network hardware by following the outlined steps. This research is expected to make a significant contribution to the field of encryption-based attack prevention. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.en_US
dc.identifier.doi10.1007/978-981-99-6062-0_57
dc.identifier.endpage629en_US
dc.identifier.isbn978-981996061-3en_US
dc.identifier.issn2195-4356en_US
dc.identifier.scopus2-s2.0-85174570436en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage622en_US
dc.identifier.urihttps://doi.org/10.1007/978-981-99-6062-0_57
dc.identifier.urihttps://hdl.handle.net/11363/8463
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes in Mechanical Engineeringen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectContinious Monitoring; Cryptography; Cyber Security; Finger Print; JA3; Network; TLSen_US
dc.titleCyber Attack Detection with Encrypted Network Connection Analysisen_US
dc.typeConference Objecten_US

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