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All Journal International Journal of Electrical and Computer Engineering
Hector Florez
Universidad Distrital Francisco Jose de Caldas
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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Techniques for predicting dark web events focused on the delivery of illicit products and ordered crime Romil Rawat; Olukayode Ayodele Oki; Sakthidasan Sankaran; Hector Florez; Sunday Adeola Ajagbe
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5354-5365

Abstract

Malicious actors, specially trained professionals operating anonymously on the dark web (DW) platform to conduct cyber fraud, illegal drug supply, online kidnapping orders, CryptoLocker induction, contract hacking, terrorist recruitment portals on the online social network (OSN) platform, and financing are always a possibility in the hyperspace. The amount and variety of unlawful actions are increasing, which has prompted law enforcement (LE) agencies to develop efficient prevention tactics. In the current atmosphere of rapidly expanding cybercrime, conventional crime-solving methods are unable to produce results due to their slowness and inefficiency. The methods for accurately predicting crime before it happens "automated machine" to help police officers ease the burden on personnel while also assisting in preventing offense. To achieve and explain the results of a few cases in which such approaches were applied, we advise combining machine learning (ML) with computer vision (CV) strategies. This study's objective is to present dark web crime statistics and a forecasting model for generating alerts of illegal operations like drug supply, people smuggling, terrorist staffing and radicalization, and deceitful activities that are connected to gangs or organizations showing online presence using ML and CV to help law enforcement organizations identify, and accumulate proactive tactics for solving crimes.
Co-Authors Olukayode Ayodele Oki Romil Rawat Sakthidasan Sankaran Sunday Adeola Ajagbe