
TL;DR
This paper investigates Advanced Persistent Threats (APTs) as a modern cyber attack technique, analyzing their characteristics, attack lifecycle, and recent detection and defense strategies to improve mitigation approaches.
Contribution
It provides a comprehensive analysis of APTs, reviewing recent detection methods like machine learning and collaborative defense, and proposes more adaptive mitigation strategies.
Findings
Analysis of four recent research papers on APT detection
Evaluation of machine learning and network defense approaches
Identification of strengths and limitations in current methods
Abstract
The techniques used in modern attacks have become an important factor for investigation. As we advance further into the digital age, cyber attackers are employing increasingly sophisticated and highly threatening methods. These attacks target not only organizations and governments but also extend to private and corporate sectors. Modern attack techniques, such as lateral movement and ransomware, are designed to infiltrate networks and steal sensitive data. Among these techniques, Advanced Persistent Threats (APTs) represent a complex method of attack aimed at specific targets to steal high-value sensitive information or damage the infrastructure of the targeted organization. In this paper, I will investigate Advanced Persistent Threats (APTs) as a modern attack technique, focusing on both the attack life cycle and cutting-edge detection and defense strategies proposed in recent academic…
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Taxonomy
TopicsNetwork Security and Intrusion Detection · Information and Cyber Security · Cybercrime and Law Enforcement Studies
