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2021-03-09
Wilkens, F., Fischer, M..  2020.  Towards Data-Driven Characterization of Brute-Force Attackers. 2020 IEEE Conference on Communications and Network Security (CNS). :1—9.

Brute-force login attempts are common for every host on the public Internet. While most of them can be discarded as low-threat attacks, targeted attack campaigns often use a dictionary-based brute-force attack to establish a foothold in the network. Therefore, it is important to characterize the attackers' behavior to prioritize defensive measures and react to new threats quickly. In this paper we present a set of metrics that can support threat hunters in characterizing brute-force login attempts. Based on connection metadata, timing information, and the attacker's dictionary these metrics can help to differentiate scans and to find common behavior across distinct IP addresses. We evaluated our novel metrics on a real-world data set of malicious login attempts collected by our honeypot Honeygrove. We highlight interesting metrics, show how clustering can be leveraged to reveal common behavior across IP addresses, and describe how selected metrics help to assess the threat level of attackers. Amongst others, we for example found strong indicators for collusion between ten otherwise unrelated IP addresses confirming that a clustering of the right metrics can help to reveal coordinated attacks.

2017-11-03
Zulkarnine, A. T., Frank, R., Monk, B., Mitchell, J., Davies, G..  2016.  Surfacing collaborated networks in dark web to find illicit and criminal content. 2016 IEEE Conference on Intelligence and Security Informatics (ISI). :109–114.
The Tor Network, a hidden part of the Internet, is becoming an ideal hosting ground for illegal activities and services, including large drug markets, financial frauds, espionage, child sexual abuse. Researchers and law enforcement rely on manual investigations, which are both time-consuming and ultimately inefficient. The first part of this paper explores illicit and criminal content identified by prominent researchers in the dark web. We previously developed a web crawler that automatically searched websites on the internet based on pre-defined keywords and followed the hyperlinks in order to create a map of the network. This crawler has demonstrated previous success in locating and extracting data on child exploitation images, videos, keywords and linkages on the public internet. However, as Tor functions differently at the TCP level, and uses socket connections, further technical challenges are faced when crawling Tor. Some of the other inherent challenges for advanced Tor crawling include scalability, content selection tradeoffs, and social obligation. We discuss these challenges and the measures taken to meet them. Our modified web crawler for Tor, termed the “Dark Crawler” has been able to access Tor while simultaneously accessing the public internet. We present initial findings regarding what extremist and terrorist contents are present in Tor and how this content is connected to each other in a mapped network that facilitates dark web crimes. Our results so far indicate the most popular websites in the dark web are acting as catalysts for dark web expansion by providing necessary knowledgebase, support and services to build Tor hidden services and onion websites.