A New Proposal on the Advanced Persistent Threat: A Survey

Author:

Quintero-Bonilla SantiagoORCID,Martín del Rey AngelORCID

Abstract

An advanced persistent threat (APT) can be defined as a targeted and very sophisticated cyber attack. IT administrators need tools that allow for the early detection of these attacks. Several approaches have been proposed to provide solutions to this problem based on the attack life cycle. Recently, machine learning techniques have been implemented in these approaches to improve the problem of detection. This paper aims to propose a new approach to APT detection, using machine learning techniques, and is based on the life cycle of an APT attack. The proposed model is organised into two passive stages and three active stages to adapt the mitigation techniques based on machine learning.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference73 articles.

1. Targeted Attacks Cyber Security Report 2019,2019

2. A Study on Advanced Persistent Threats;Chen,2014

3. M-Trends 2019: Fireeye Mandiant Services Special Report,2019

4. Survey of publicly available reports on advanced persistent threat actors

Cited by 50 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. HEOD: Human-assisted Ensemble Outlier Detection for cybersecurity;Computers & Security;2024-11

2. Identification of Advancing Persistent Risks;Advances in IT Standards and Standardization Research;2024-05-31

3. Understanding Customer Perception of Cyber Attacks;Advances in Hospitality, Tourism, and the Services Industry;2024-05-31

4. Detection of advanced persistent threats using hashing and graph-based learning on streaming data;Applied Intelligence;2024-04

5. Comparative Analysis of Machine Learning Classifiers for Fileless Malware Detection;2024 International Conference on Green Energy, Computing and Sustainable Technology (GECOST);2024-01-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3