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Identifying and profiling key sellers in cyber carding community : AZSecure text mining system

Li, Weifeng; Chen, Hsinchun; Nunamaker, Jay F. - In: Journal of management information systems : JMIS 33 (2016) 4, pp. 1059-1086

Persistent link: https://www.econbiz.de/10011664638

Enhancing predictive analytics for anti-phishing by exploiting website genre information

Abbasi, Ahmed; Zahedi, Fatemeh Mariam; Zeng, Daniel; … - In: Journal of management information systems : JMIS 31 (2014/15) 4, pp. 109-157

Persistent link: https://www.econbiz.de/10011385715

Special issue: Enterprise risk and security management : data, text and Web mining

Chen, Hsinchun (contributor) - 2011

Persistent link: https://www.econbiz.de/10008860131

Business intelligence and analytics : from big data to big impact

Chen, Hsinchun; Chiang, Roger H. L.; Storey, Veda C. - In: Management information systems : mis quarterly 36 (2012) 4, pp. 1165-1188

Persistent link: https://www.econbiz.de/10009680767

Linking exploits from the Dark Web to known vulnerabilities for proactive cyber threat intelligence : an attention-based deep structured semantic model

Samtani, Sagar; Chai, Yidong; Chen, Hsinchun - In: MIS quarterly 46 (2022) 2, pp. 911-946

Persistent link: https://www.econbiz.de/10013286533

Cross-lingual cybersecurity analytics in the international dark web with adversarial deep representation learning

Ebrahimi, Mohammadreza; Chai, Yidong; Samtani, Sagar; … - In: MIS quarterly 46 (2022) 2, pp. 1209-1226

Persistent link: https://www.econbiz.de/10013286594

Dark web : exploring and data mining the dark side of the web

Chen, Hsinchun - 2012

The University of Arizona Artificial Intelligence Lab (AI Lab) Dark Web project is a long-term scientific research program that aims to study and understand the international terrorism (Jihadist) phenomena via a computational, data-centric approach. We aim to collect "ALL" web content generated...

Persistent link: https://www.econbiz.de/10014275341