Continuous and Multiregional Monitoring of Malicious Hosts

Shota Fujii, Takayuki Sato, Sho Aoki, Yu Tsuda, Y. Okano, Tomohiro Shigemoto, N. Kawaguchi, M. Terada
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引用次数: 1

Abstract

The number of cybersecurity threats has been increasing, and these threats have become more sophisticated year after year. Malicious hosts play a large role in modern cyberattacks, e.g., as a launcher of remote-control attacks or as a receiver of stolen information. In such circumstances, continuous monitoring of malicious hosts (URL/IP addresses) is indispensable to reveal cyberattack activities, and many studies have been conducted on that. However, many of them have limitations: they help only in the short-term or they help only a few regions and/or a few organizations. Therefore, we cannot effectively monitor attacks that are active for only a short time or that change their behavior depending on where the victims are from (e.g., country/organization). In this paper, we propose Stargazer, a program that monitors malicious hosts from multiple points on a long-term basis. Multiregional monitoring sensors and inter-organizational collaboration are conducted to achieve this surveillance. In this paper, we describe an implementation of the Stargazer prototype and how monitoring was carried out using multiregional sensors starting in Dec. 2018 of 1,050 malicious hosts; 10,929,418 measurements were obtained. Case studies on (1) revived hosts, (2) hosts that only respond to specific regions, and (3) the behavior of attack preparation were created.
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恶意主机的连续和多区域监控
网络安全威胁的数量一直在增加,这些威胁变得越来越复杂。恶意主机在现代网络攻击中扮演着重要的角色,例如,作为远程控制攻击的发射器或作为被盗信息的接收器。在这种情况下,对恶意主机(URL/IP地址)的持续监控是揭示网络攻击活动的必要手段,对此已经进行了很多研究。然而,它们中的许多都有局限性:它们只在短期内提供帮助,或者只帮助少数地区和/或少数组织。因此,我们无法有效监控仅在短时间内活跃或根据受害者来自何处(例如,国家/组织)改变其行为的攻击。在本文中,我们提出了Stargazer,一个从多个点长期监视恶意主机的程序。为实现这一监测,开展了多区域监测传感器和组织间协作。在本文中,我们描述了Stargazer原型的实现,以及如何从2018年12月开始使用多区域传感器对1,050个恶意主机进行监控;共进行了10,929,418次测量。创建了以下案例研究:(1)复活的主机,(2)只响应特定区域的主机,以及(3)攻击准备行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Session details: Session 1D: Applied Cryptography and Cryptanalysis HACLxN: Verified Generic SIMD Crypto (for all your favourite platforms) Pointproofs: Aggregating Proofs for Multiple Vector Commitments Session details: Session 4D: Distributed Protocols A Performant, Misuse-Resistant API for Primality Testing
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