Issue Date
2021-07-27Subjects
securitymachine learning
cyberstalking
digital forensics
profiling
Subject Categories::G920 Others in Computing Sciences
Metadata
Show full item recordAbstract
The continued usage of technology has led to the rise of cyberstalking. Cyberstalking is seen as traditional method of stalking that has been altered by technology. This crime has now been modernized using technological tools and techniques. The continued increase in cyberstalking in the world today has drawn attention to the need to address this problem. Though studies on this crime have been conducted in the fields of criminology, legal, public health, sociology, and psychology, it still remains a challenge to detect, prevent, and investigate this crime. Traditional stalking methods have been used to combat it, despite the fact that this crime is committed online. Unfortunately, these methods have provided few solutions for detecting and preventing it. The prevalence of this crime, combined with technological advancement, has necessitated the development of technical strategies to mitigate it, protect victims, and assist law enforcement agencies. In this study, a content-based detection framework for cyberstalking is proposed. The framework consists of message identification, filtering, detection (content detection and profiling offender) and evidence modules. It is designed as a forensic readiness framework that can automatically detect cyberstalking, gather evidence and profile potential offenders. The framework employs machine learning, data mining techniques, digital forensics, and profiling to analyze text, image, and media contents, collect evidence, and profile offenders. This framework would not only detect cyberstalking automatically, but it would also be useful as an investigative tool for law enforcement.Citation
Asante A, Feng X (2021) 'Content-based technical solution for cyberstalking detection', 2021 3rd International Conference on Computer Communication and the Internet - Nagoya, Institute of Electrical and Electronics Engineers Inc..Additional Links
https://ieeexplore.ieee.org/document/9486770Type
Conference papers, meetings and proceedingsLanguage
enISBN
9781728176185ae974a485f413a2113503eed53cd6c53
10.1109/ICCCI51764.2021.9486770