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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.
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Macdonald, M., Frank, R., Mei, J., Monk, B..  2015.  Identifying digital threats in a hacker web forum. 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). :926–933.

Information threatening the security of critical infrastructures are exchanged over the Internet through communication platforms, such as online discussion forums. This information can be used by malicious hackers to attack critical computer networks and data systems. Much of the literature on the hacking of critical infrastructure has focused on developing typologies of cyber-attacks, but has not examined the communication activities of the actors involved. To address this gap in the literature, the language of hackers was analyzed to identify potential threats against critical infrastructures using automated analysis tools. First, discussion posts were collected from a selected hacker forum using a customized web-crawler. Posts were analyzed using a parts of speech tagger, which helped determine a list of keywords used to query the data. Next, a sentiment analysis tool scored these keywords, which were then analyzed to determine the effectiveness of this method.