An investigation in detection and mitigation of smishing using machine learning techniques
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Human-Computer Interaction,Media Technology,Communication,Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s13278-023-01142-4.pdf
Reference51 articles.
1. Adewole KS, Anuar NB, Kamsin A, Sangaiah AK (2019) SMSAD: a framework for spam message and spam account detection. Multimed Tools Appl 78:3925–3960
2. Akande ON, Gbenle O, Abikoye OC, Jimoh RG, Akande HB, Balogun AO, Fatokun A (2022) SMSPROTECT: an automatic smishing detection mobile application. ICT Express
3. Aldabbas H, Amin R (2021) A novel mechanism to handle address spoofing attacks in SDN based IoT. Cluster Comput 24(4):3011–3026
4. Boukari BE, Ravi A, Msahli M (2021) ML detection for smishing frauds. In: 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC) (pp 1–2). IEEE
5. Butt UA, Amin R, Aldabbas H, Mohan S, Alouffi B and Ahmadian, A (2022) Cloud-based email phishing attack using machine and DL algorithm. Complex Intell Syst. pp1–28
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