Abstract
To further cybersecurity, there is interest in studying online cybercriminal communities to learn more about emerging cyber threats. Literature documents the existence of many online Internet Relay Chat (IRC) cybercriminal communities where cybercriminals congregate and share hacking tools, malware, and more. However, many cybercriminal community participants appear unskilled and have fleeting interests, making it difficult to detect potential long-term or key participants. This is a challenge for researchers and practitioners to quickly identify cybercriminals that may provide credible threat intelligence. Thus, we propose a computational approach to analyze cybercriminals IRC communities in order to identify potential long-term and key participants. We use the extended Cox model to scrutinize cybercriminal IRC participation for better understanding of behaviors exhibited by cybercriminals of importance. Results indicate that key cybercriminals may be quickly identifiable by assessing the scale of their interaction and networks with other participants.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 482-510 |
| Number of pages | 29 |
| Journal | Journal of Management Information Systems |
| Volume | 33 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 2 2016 |
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ASJC Scopus subject areas
- Management Information Systems
- Computer Science Applications
- Management Science and Operations Research
- Information Systems and Management
Cite this
Examining Hacker Participation Length in Cybercriminal Internet-Relay-Chat Communities. / Benjamin, Victor; Zhang, Bin; Nunamaker, Jay F.; Chen, Hsinchun.
In: Journal of Management Information Systems, Vol. 33, No. 2, 02.04.2016, p. 482-510.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Examining Hacker Participation Length in Cybercriminal Internet-Relay-Chat Communities
AU - Benjamin, Victor
AU - Zhang, Bin
AU - Nunamaker, Jay F.
AU - Chen, Hsinchun
PY - 2016/4/2
Y1 - 2016/4/2
N2 - To further cybersecurity, there is interest in studying online cybercriminal communities to learn more about emerging cyber threats. Literature documents the existence of many online Internet Relay Chat (IRC) cybercriminal communities where cybercriminals congregate and share hacking tools, malware, and more. However, many cybercriminal community participants appear unskilled and have fleeting interests, making it difficult to detect potential long-term or key participants. This is a challenge for researchers and practitioners to quickly identify cybercriminals that may provide credible threat intelligence. Thus, we propose a computational approach to analyze cybercriminals IRC communities in order to identify potential long-term and key participants. We use the extended Cox model to scrutinize cybercriminal IRC participation for better understanding of behaviors exhibited by cybercriminals of importance. Results indicate that key cybercriminals may be quickly identifiable by assessing the scale of their interaction and networks with other participants.
AB - To further cybersecurity, there is interest in studying online cybercriminal communities to learn more about emerging cyber threats. Literature documents the existence of many online Internet Relay Chat (IRC) cybercriminal communities where cybercriminals congregate and share hacking tools, malware, and more. However, many cybercriminal community participants appear unskilled and have fleeting interests, making it difficult to detect potential long-term or key participants. This is a challenge for researchers and practitioners to quickly identify cybercriminals that may provide credible threat intelligence. Thus, we propose a computational approach to analyze cybercriminals IRC communities in order to identify potential long-term and key participants. We use the extended Cox model to scrutinize cybercriminal IRC participation for better understanding of behaviors exhibited by cybercriminals of importance. Results indicate that key cybercriminals may be quickly identifiable by assessing the scale of their interaction and networks with other participants.
UR - http://www.scopus.com/inward/record.url?scp=84990909793&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84990909793&partnerID=8YFLogxK
U2 - 10.1080/07421222.2016.1205918
DO - 10.1080/07421222.2016.1205918
M3 - Article
VL - 33
SP - 482
EP - 510
JO - Journal of Management Information Systems
JF - Journal of Management Information Systems
SN - 0742-1222
IS - 2
ER -