Merging Threat Modeling with Threat Hunting for Dynamic Cybersecurity Defense

被引:0
|
作者
Nour, Boubakr [1 ]
Ujjwal, Sonika [2 ]
Karacay, Leyli [3 ]
Laaroussi, Zakaria [2 ]
Gulen, Utku [3 ]
Tomur, Emrah [4 ]
Pourzandi, Makan [1 ]
机构
[1] Ericsson Security Research, Canada
[2] Ericsson Security Research, Finland
[3] Ericsson Security Research, Turkey
[4] Izmir University of Economics, Turkey
来源
IEEE Internet of Things Magazine | 2024年 / 7卷 / 06期
关键词
D O I
10.1109/IOTM.001.2400061
中图分类号
学科分类号
摘要
As technology advances swiftly and the Internet of Things undergoes significant growth, the world is experiencing a surge in data creation. This has resulted in the rapid emergence of novel applications, bringing forth a broader range of intricate and challenging threats that pose difficulties in detection. Therefore, a comprehensive and proactive approach is needed to identify and mitigate security threats. In this article, we combine threat modeling and threat hunting using different approaches in order to provide a more holistic understanding of the security posture of the system, by leveraging the threat model capability in anticipating potential threats and the capability of the threat hunting in identifying evolving and previously unidentified threats. This integration allows for early detection and mitigation of potential threats and enables organizations to enhance their incident response readiness, implement targeted risk mitigation strategies, and fortify their overall cybersecurity posture in the face of evolving and sophisticated threats. © 2018 IEEE.
引用
收藏
页码:28 / 34
相关论文
共 50 条
  • [1] Understanding Cybersecurity Threat Trends Through Dynamic Topic Modeling
    Sleeman, Jennifer
    Finin, Tim
    Halem, Milton
    FRONTIERS IN BIG DATA, 2021, 4
  • [2] Minitrack Introduction Machine Learning and AI: Cybersecurity and Threat Hunting
    Kayhan, Varol O.
    Shivendu, Shivendu
    Agrawal, Manish
    Zeng, David
    Proceedings of the Annual Hawaii International Conference on System Sciences, 2024,
  • [3] Is Quantum Computing a Cybersecurity Threat?
    Denning, Dorothy E.
    AMERICAN SCIENTIST, 2019, 107 (02) : 83 - 85
  • [4] Empirical evaluation of a threat modeling language as a cybersecurity assessment tool
    Katsikeas, Sotirios
    Ling, Engla Rencelj
    Johnsson, Pontus
    Ekstedt, Mathias
    COMPUTERS & SECURITY, 2024, 140
  • [5] An Exploration of Disinformation as a Cybersecurity Threat
    Caramancion, Kevin Matthe
    2020 3RD INTERNATIONAL CONFERENCE ON INFORMATION AND COMPUTER TECHNOLOGIES (ICICT 2020), 2020, : 440 - 444
  • [6] Cybersecurity Confronting the Threat of Shadow IT
    Prince, Brian
    FORBES, 2014, 194 (05): : 136 - +
  • [7] DeepSecure: A computational design science approach for interpretable threat hunting in cybersecurity decision making
    Kumar, Prabhat
    Javeed, Danish
    Islam, A. K. M. Najmul
    Luo, Xin
    DECISION SUPPORT SYSTEMS, 2025, 188
  • [8] Electromagnetic Warfare and the Cybersecurity Threat
    Pinou, Damianos
    Chy, Rien
    Hayajneh, Thaier
    2017 IEEE 15TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 15TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 3RD INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS(DASC/PICOM/DATACOM/CYBERSCI, 2017, : 669 - 674
  • [9] Cyber Threat Intelligence Mining for Proactive Cybersecurity Defense: A Survey and New Perspectives
    Sun, Nan
    Ding, Ming
    Jiang, Jiaojiao
    Xu, Weikang
    Mo, Xiaoxing
    Tai, Yonghang
    Zhang, Jun
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2023, 25 (03): : 1748 - 1774
  • [10] Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence
    Gao, Peng
    Shao, Fei
    Liu, Xiaoyuan
    Xiao, Xusheng
    Qin, Zheng
    Xu, Fengyuan
    Mittal, Prateek
    Kulkarni, Sanjeev R.
    Song, Dawn
    2021 IEEE 37TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2021), 2021, : 193 - 204