Unveiling the pattern of PhishingAttacks using the Machine Learning approach
- Title
- Unveiling the pattern of PhishingAttacks using the Machine Learning approach
- Creator
- Sinha V.; Shanbhog M.; Upreti K.
- Description
- This study introduces a unique approach to strengthening cybersecurity by combining advanced models for real-time detection of phishing websites. A classifier is trained to discern patterns associated with legitimate and phishing URLs, leveraging a carefully organized labeled dataset. The model in this paper forms the foundation for a real-time detection system, providing users with real-time information on potential phishing threats. Integrating an adaptive decision-making algorithm improves decision-making adaptability, particularly in scenarios challenging the model's confidence. A user feedback loop ensures the continuous learning and refinement of the system, aligning it more closely with user expectations. The future scope of this research involves exploring advanced models, improving explainability, and incorporating dynamic features for enhanced detection. Adaptive policies, large-scale deployment, and ethical implications are pivotal for real-world applicability. In conclusion, this study contributes to advancing phishing detection methodologies and lays the groundwork for future innovations in cybersecurity. The collaborative efforts of academia, industry, and cybersecurity stakeholders arenecessaryfor realizing the full potential of this paper and ensuring a safer online platform for users. 2024 IEEE.
- Source
- Proceedings - 3rd International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Adaptive Learning; Models; Phishing Detection; Real-time Threat Detection; User-Centric Design
- Coverage
- Sinha V., Christ (Deemed to Be University), Department of Computer Science, NCR, Delhi, India; Shanbhog M., Christ (Deemed to Be University), Department of Computer Science, NCR, Delhi, India; Upreti K., Christ (Deemed to Be University), Department of Computer Science, NCR, Delhi, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835038943-2
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sinha V.; Shanbhog M.; Upreti K., “Unveiling the pattern of PhishingAttacks using the Machine Learning approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/19353.