Endpoint Detection and Response: Why Use Machine Learning?

被引：5

作者：

Sjarif, Nilam Nur Amir ^{[1
]}

Chuprat, Suriayati ^{[1
]}

Mahrin, Mohd Naz'ri ^{[1
]}

Ahmad, Noor Azurati ^{[1
]}

Ariffin, Aswami ^{[2
]}

Senan, Firham M. ^{[2
]}

Zamani, Nazri Ahmad ^{[2
]}

Saupi, Afifah ^{[2
]}

机构：

[1] Univ Teknol Malaysia, Kuala Lumpur, Malaysia

[2] CyberSecur Malaysia, Cyberjaya, Malaysia

来源：

2019 10TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC): ICT CONVERGENCE LEADING THE AUTONOMOUS FUTURE | 2019年

关键词：

Endpoint; detection; response; techniques; machine learning;

D O I：

10.1109/ictc46691.2019.8939836

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Threats towards the cyberspace have becoming more aggressive, intelligent and some attack at real-time. These urged both researchers and practitioner to secure the cyberspace at the very root point, which refer to as the endpoint. The detection and response at endpoint must be able to protect at real-time as good as the attacker. In this paper, we reviewed the techniques used in endpoint detection and response. We discovered the trend have shifted from the traditional approaches to more intelligent way. Specifically, most proposed techniques focused on machine learnings. We also zoomed into these techniques and outline the advantages of these techniques.

引用

页码：283 / 288

页数：6

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