Use of Intelligence Based Agents to Deal with Cyber Crime

Muhamad Arif Budiman, Muhammad Erza Aminanto

Abstract


The rapid development of information and communication technology has encouraged the development of cybercrime. As a type of crime that is different from conventional crime, the handling of cybercrime requires a special way. This paper aims to examine intelligence-based agents for handling cyber crimes, Indonesia, with a focus on the use of chatbots. The method used is the library research method. Data sourced from various books, journals and internet sources were then analyzed by descriptive analysis method. The results show that the current development of AI has allowed its use to carry out crime data mining. One of the ways to do this is by using a chatbot, which is a type of intelligence-based agent. The use of chatbots in the police has the possibility to be developed as a cybercrime detection and evidence collection method. This is done by developing a chatbot framework, methodology and evidence collection procedures on the dark web and digital forensic practices.


Keywords


intelligence-based agents; chatbots; crime data mining; cybercrime

Full Text:

PDF

References


Almansoori, A., Alshamsi, M., Abdallah, S., & Salloum, S. A. (2021). Analysis of Cybercrime on Social Media Platforms and Its Challenges. The International Conference on Artificial Intelligence and Computer Vision (pp. 615-625). Springer, Cham.

Arifin, M. (2020). The Efforts of Islamic Criminal Law Integration into Indonesian Law Procedures. Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 3 (2): 975-984.

Champbell-Phillips, S. (2020). Exploring Social Problems in Tobago. Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 3 (3): 1594-1598.

Chen, H., Chung, W., Qin, Y., Chau, M., Xu, J. J., Wang, G., et al. (2003). Crime data mining: an overview and case studies. In. Proceedings of the 2003 annual national conference on Digital government research (pp. 1-5). Texas: University of Arizona.

Chintia, E., Nadiah, R., Ramadhani, H. N., Haedar, Z. F., & Febriansyah, A. (2019). Kasus Kejahatan Siber yang Paling Banyak Terjadi di Indonesia dan Penanganannya. JIEET (Journal of Information Engineering and Educational Technology) 2(2), 65-69.

Fayyad, U., & Uthurusamy, R. (2002). Evolving data mining into solutions for insights. Communications of the ACM, 45(8), 28-31.

Gendi, M., & Munteanu, C. (2021). Towards a chatbot for evidence gathering on the dark web. In CUI 2021-3rd Conference on Conversational User Interfaces, 1-3.

Kuk, K., Stanojević, A., Jovanović, M., & Nedeljković, S. (2018). Intelligent e-service for detecting malicious code based agent technology. Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics, (pp. 1-6).

Laranjo, L., Dunn, A. G., Tong, H. L., Kocaballi, A. B., Chen, J., Bashir, R., et al. (2018). Conversational agents in healthcare: a systematic review. Journal of the American Medical Informatics Association, 25(9), 1248-1258.

Marufah, N., Rahmat, H. K., & Widana, I. D. (2020). Degradasi Moral sebagai Dampak Kejahatan Siber pada Generasi Millenial di Indonesia. NUSANTARA: Jurnal Ilmu Pengetahuan Sosial, 7(1), 191-201.

Mashabi, S. (2021, Sep 14). BSSN: Hingga Agustus 2021 Tercatat 888 Juta Serangan Siber. Retrieved Okt 27, 2021, from kompas.com: https://nasional.kompas.com/read/2021/09/14/10493771/bssn-hingga-agustus-2021-tercatat-888-juta-serangan-siber

Nahwan, D., Nurhayani, N., Nugroho, I. S., & Srimurni, R. R. (2021). Analisa Manajemen Strategis Program Pelatihan SDM TIK Polri dalam Menghadapi Kejahatan Siber Era 4.0. Media Nusantara, 18(2), 133-144.

Noviantini, N., Remaja, I. N., & Mariadi, N. N. (2021). Efektivitas Patroli Siber Dalam Mengungkap Kasus Ujaran Kebencian Di Wilayah Hukum Polres Buleleng. Kertha Widya, 9(1), 28-51.

Piscopo, A., Siebes, R., & Hardman, L. (2017). Predicting sense of community and participation by applying machine learning to open government data. Policy & Internet, 9(1), 55-75.

Rachmadie, D. T. (2020). Regulasi Penyimpangan Artificial Intelligence Pada Tindak Pidana Malware Berdasarkan Undang-Udang Republik Indonesia Nomor 19 Tahun 2016. Jurnal Hukum Pidana dan penanggulangan Kejahatan, 9(2), 128-156.

Radulov, N. (2019). Artificial intelligence and security Security 4.0. Security & Future, 3(1), 3-5.

Schachner, T., Keller, R., & Von Wangenheim, F. (2020). Artificial intelligence-based conversational agents for chronic conditions: systematic literature review. Journal of medical Internet research, 22(9), e20701.

Sivčević, D., Košanin, I., Nedeljković, S., Nikolić, V., Kuk, K., & Nogo, S. (2020). Possibilities of used intelligence based agents in instant messaging on e-government services. 2020 19th International Symposium INFOTEH-JAHORINA (INFOTEH) (pp. 1-5). IEEE.

Stănilă, L. (2020). Memories of the Future-Sweetie and the Impact of the New Technologies on the Criminal Justice System. EU and comparative law issues and challenges series (ECLIC), 4, 557-575.

Zed, M. (2003). Metode Penelitian Kepustakaan. Jakarta: Yayasan Obor Indonesia.

Tumanggor, F., Muazzul, and Zulyadi, R. (2019). Handling of Narcotics Child Victims in Child Special Coaching Institutions Class I Tanjung Gusta, Medan. Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 2 (4): 50-55.




DOI: https://doi.org/10.33258/birci.v5i1.4049

Article Metrics

Abstract view : 112 times
PDF - 37 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.