DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE–BASED CYBERSECURITY SYSTEM FOR THE AUTOMATIC DETECTION OF FAKE FINANCIAL RECEIPTS, PHISHING URLS, AND MALICIOUS APK FILES
DOI:
https://doi.org/10.5281/zenodo.17994108Keywords:
cyberattack, social environment, psychological factors, financial information, fake payment, mobile applicationAbstract
It is through phishing attacks, fake payment documents and malicious mobile applications that a large part
of financial fraud around the world is happening. As a result of such attacks, users ' bank card information, personal
information and financial resources are being stolen. Especially young people and users who are actively using the
internet are more susceptible to this type of attack. Therefore, the issue of ensuring financial information security is one
of the most important tasks of today
References
Ian Goodfellow, Yoshua Bengio, Aaron Courville. Deep Learning. – Cambridge: MIT Press, 2016. – 775 p.
Christopher M. Bishop. Pattern Recognition and Machine Learning. – New York: Springer, 2006. – 738 p.
Ting-Fang Yen, Michael K. Reiter. Traffic Aggregation for Malware Detection. // IEEE Transactions on Dependable and
Secure Computing. – 2010. – Vol. 7. – No. 2. – P. 131–145.
Maikantis P., Medvedev A., Jansen J. Phishing URL Detection Using Machine Learning Techniques. // International
Journal of Cyber Security and Digital Forensics. – 2018. – Vol. 7. – No. 2. – P. 109–121.
Shafiq M.Z., Tabish S.M., Mirza F., Farooq M. Android Malware Detection Using Static Analysis and Machine Learning.
// International Conference on Emerging Technologies. – IEEE, 2019. – P. 1–6.
Andrei G. Chuvakin, Kevin Schmidt, Chris Phillips. Logging and Log Management: The Authoritative Guide to
Understanding the Concepts Surrounding Logging and Log Management. – Waltham: Syngress, 2013. – 384 p.
Enrico De Cristofaro, Giovanni Vigna. Automated Detection of Phishing Attacks Using Natural Language Processing.
// ACM Conference on Computer and Communications Security. – 2017. – P. 241–252.
Arp D., Spreitzenbarth M., Hubner M., Gascon H., Rieck K. Drebin: Effective and Explainable Detection of Android
Malware in Your Pocket. // NDSS Symposium. – 2014. – P. 1–15.
Nidal K. Kheir, Nael Salman. OCR-Based Fraud Detection in Financial Documents Using Deep Learning. // Journal of
Information Security and Applications. – 2020. – Vol. 55. – Article 102627.
Stuart Russell, Peter Norvig. Artificial Intelligence: A Modern Approach. – 4th ed. – London: Pearson, 2021. – 1136 p.
