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The Intelligent Decision Support System for Cybercrime Investigation based on Knowledge Graph and Explainable Artificial Intelligence
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지식 그래프와 설명가능 인공지능 기반 사이버 범죄 수사를 위한 지능형 의사결정 지원 시스템

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Type
Academic journal
Author
Heeyoung Chung (가천대학교) Myung-Mook Han (가천대학교)
Journal
Korean Institute of Intelligent Systems Journal of Korean Institute of Intelligent Systems Vol.33 No.4 KCI Accredited Journals
Published
2023.8
Pages
293 - 301 (9page)
DOI
10.5391/JKIIS.2023.33.4.293

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The Intelligent Decision Support System for Cybercrime Investigation based on Knowledge Graph and Explainable Artificial Intelligence
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Abstract· Keywords

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In the face of the increasing cybercrime in the digital space, investigators encounter significant obstacles when it comes to collecting evidence due to the vast amount of information, activities in the dark web and other concealed activities. With the growing necessity to support law enforcement officers in making informed decisions and obtaining critical evidence, there is a demand for an intelligent decision support system which is tailored for cybercrime investigations. Therefore, the aim of this research is to propose a framework for building a knowledge graph and implementing explainable artificial intelligence, XAI based on both open web and dark web data. In addition, as part of this research, a series of experiments were conducted on the core technology of the proposed framework, which revolves around the use of a knowledge graph. The knowledge graph was constructed based on the extracted features and served as a foundation for generating association rules using the Apriori algorithm. These rules focused on identifying relationships with a confidence level of 0.5 or greater between law enforcement agencies and a key player in dark web activities. Through graph-based inference, intuitive data on the activities of this key player is provided as valuable information for the investigators.
#지식 그래프 #추론 #다크웹 #설명가능 인공지능 #의사결정 지원 시스템 #Knowledge Graph #Inference #Dark Web #Explainable AI #Decision Support System

Contents

요약
Abstract
1. 서론
2. 관련 연구
3. 제안 프레임워크
4. 실험
5. 결론 및 향후 연구
References

References (15)

Add References
Korean National Police Agency, “Cybercrime Trends in 2023,” Avaiable: https://www.police.go.kr/viewer/skin/doc.html?fn=0f1256d9-b61b-49ee-b825-a0122d33bb2b.pdf&rs=/viewer/202306, 2023, [Accessed: June 11, 2023] google schola Z. Spalevic and M. Ilic, “The use of dark web for the purpose of illegal activity spreading,” Ekonomika, vol. 63, no. 1, pp. 73-82, 2017. google schola S. Costantini, G. Gasperis, and R. Olivieri, “Digital forensics and investigations meet artificial intelligence,” Annals of Mathematics and Artificial Intelligence, vol. 86, pp. 193-229, 2019. google schola Q. Wang, Z. Mao, B. Wang, and L. Guo, “Knowledge graph embedding: A survey of approaches and applications,” IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 12, pp. 2724-2743, 2017. google schola M. Nickel, K. Murphy, V. Tresep, and E. Gabrilovich, “A review of relational machine learning for knowledge graphs,” Proceedings of the IEEE, vol. 104, no. 1, pp. 11-33, Jan., 2016. google schola

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