MITIGATING WATERING HOLE ATTACKS A MULTILAYERED DEFENSE STRATEGY INTEGRATING MACHINE LEARNING AND BEHAVIORAL ANALYSIS.
One of the main threats that are occurring in the world is watering hole attacks, as they attack specific groups by exploiting respected sites. Legacy defenses, based on these known signatures and static rules have shown to be insufficient in the face of sophisticated attacks. This paper proposes a...
| Publicado en: | Scientific Culture Vol. 12; no. 5 Part 1; pp. 67 - 84 |
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| Autores principales: | , |
| Formato: | Artículo |
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University of the Aegean
2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=193975176&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 193975176 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 24080071 I6HU jtl: Scientific Culture issn: 24080071 maglogo: N pubinfo: dt: 2026 vid: 12 iid: 5 Part 1 pid: 47715 pub: University of the Aegean artinfo: ui: 193975176 10.5281/zenodo.12511006 ppf: 67 ppct: 17 formats: tig: atl: MITIGATING WATERING HOLE ATTACKS A MULTILAYERED DEFENSE STRATEGY INTEGRATING MACHINE LEARNING AND BEHAVIORAL ANALYSIS. aug: au: Ataelfadiel, Mohammed Awad Mohammed Osman, Ahmed A. F. affil: Applied College, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia su: Machine learning Anomaly detection (Computer security) Behavioral sciences Internet security Cyberterrorism sug: subj: Machine learning Anomaly detection (Computer security) Behavioral sciences Internet security Cyberterrorism keyword: Advanced Persistent Threats (APTs) Behavioral Analysis Cybersecurity Defense Strategies Machine Learning in Cybersecurity Threat Detection and Mitigation Watering Hole Attacks ab: One of the main threats that are occurring in the world is watering hole attacks, as they attack specific groups by exploiting respected sites. Legacy defenses, based on these known signatures and static rules have shown to be insufficient in the face of sophisticated attacks. This paper proposes a multi-layered defense strategy that integrates machine learning (ML) and behavioral analysis to detect and mitigate watering hole attacks. The proposed strategy involves training ML models to recognize patterns indicative of such attacks and continuously monitoring user behavior to detect anomalies. We hypothesize that this integrated approach will offer a robust and adaptive defense mechanism, enhancing the ability to detect and respond to advanced cyber threats in real-time. This paper provides a comprehensive framework for implementing this multi-layered defense strategy, contributing to the ongoing efforts to improve cybersecurity measures against watering hole attacks pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2026 holdings: @attributes: islocal: N |
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