Deceptive Phishing Spying and Detection in Social Networking Sites Using Data Mining and Ontology
Mohammed Mahmood Ali, Mohammad Sanaullah Qaseem, Md. Sadeq Mohiuddin Ghori, Rabia Basri, Mohammed Abbad Mohiuddin, Md. Shabaz Hussain · 2024
Deceptive phisher messages in social-networking-sites (SNS) are often the source of cybersecurity breaches, resulting in spying of privacy information (PI) leading towards cyber identity thefting. To address this issue Anti-Phisher Detection System (APDs) has been designed, utilizing Ontology-Integrated Information Extraction (OIIE) and Association-Rule Technique (ART) that pin-points which precisely predicts phishers activities and also updates the phishers database based on microblogs that attempted to disrupt security; thus, alerts the social users by intimating them to secure privacy information from phishers activities and generating a report for cybercrime department for adequate action. APDs is tested by taking certain spim from SNS and identified its prediction as Financial_domain with a precision of 66.66% depicted in Fig. 5. The result of APDs demonstrates the significant improvement over earlier systems, briefly discussed in Section IV.