Survey on Mobile Phone Threat: Detection and Prevention Techniques

Adamu Shehu¹ , Yakubu Ernest Nwuku² , Egere N. Augustine³ , Muhammad A. Bilyaminu⁴ , Muhammed Usman⁵ , Ibrahim Abdu⁶

Section:Survey Paper, Product Type: Journal-Paper
Vol.11 , Issue.5 , pp.48-53, Oct-2023

Online published on Oct 31, 2023

Copyright © Adamu Shehu, Yakubu Ernest Nwuku, Egere N. Augustine, Muhammad A. Bilyaminu, Muhammed Usman, Ibrahim Abdu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
The increasing popularity and convenience of mobile phones have made them indispensable tools for personal and corporate tasks. However, this portability also exposes sensitive data, such as credit card details, login credentials, and private contacts, to potential malware attacks, such malwares are Android GMBots, AceDeceiver IOS Malware, Marcher (ExoBot), backdoor and roots exploits, etc. As mobile phones are vulnerable to malware attacks, it is crucial to implement robust security methods such existing methods as anti-virus, NaĂŻve-Bayes, SVM, MTM base mobile security, etc. to detect and prevent potential threats. In this research, we delineate diverse methods for identifying and thwarting mobile phone attacks. We undertake a comparative assessment of their susceptibilities and put forth the most efficacious approach and framework to bolster mobile security. The study discovered Pre-Crime Cloud Service Scheme and MTM base security are been rated the best mobile security defense against malware and potential security threats. It is recommended that continuous user awareness and exploring different new mobile security techniques for the detection and prevention of potential malware attacks.

Key-Words / Index Term :
Mobile phone, threat, detection, prevention, techniques

References :
[1] Umar Ahmed, Aliyu Musa, "Assessment of Mobile Phone Use in Nigeria from Inception to Date". Scholars Bulletin, Vol-2, Iss-4, 192-197, 2016.
[2] Belal Amro, "Malware Detection Techniques for Mobile Devices," International Journal of Mobile Network Communications & Telematics, 7(4/5/6), 01–10. 2017
[3] Fang-Yie Leu, Kun-Lin Tsai,Yi-Ting Hsiao and
Chao-Tung Yang, "An Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques," IEEE Systems Journal, vol. 11, no. 2, pp. 427-438, 2017.
[4] Mercaldo, Francesco & Santone, Antonella, "Deep learning for image-based mobile malware detection", Journal of Computer Virology and Hacking Techniques. 16. 1-15, 2020.
[5] Ya-Fen Chang, Wei-Liang Tai, & Min-How Hsu, "A
Secure Mobility Network Authentication Scheme Ensuring User Anonymity" Symmetry 9, no. 12: 307. 2017.
[6] Bin Ge and Jin Xu, "Analysis of Computer Network
Security Technology and Preventive Measures under the Information Environment," 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), Harbin, China, pp. 1978-1981, 2020
[7] Waiganjo, Iyaloo. "Mobile device security issue in a mobile device world". 1st Annual Research Conference, 2019.
[8] Hezal Lope, & Rahu Lopes, "Comparative Analysis of Mobile Security Threats and Solution," International Journal of Engineering Research and Application Vol. 3, Issue 5, pp.499-502, 2013.
[9] Mitrea, Teodor & Borda, Monica, "Mobile Security Threats: A Survey on Protection and Mitigation Strategies." International Conference Knowledge-Based Organization. 26. 131-135, 2020.
[10] Blaž Markelj, Sabina Zgaga,, "Comprehension of cyber threats and their consequences in Slovenia." Computer Law & Security Review, 32(3), 513–525. 2016.
[11] Vishal Garg, Bikrampal Kaur, Tajinder Kumar; ANN based security in mobile cloud computing. AIP Conference Proceeding 2, 2760 (1): 020019, 2023
[12] Atzeni, Andrea & Diaz, Fernando & Lopez, Francisco & Marcelli, Andrea & Sánchez, Antonio & Squillero, Giovanni. "The Rise of Android Banking Trojans". IEEE Potentials. 39. 13-18, (2020).
[13] Panagiotis I. Radoglou-Grammatikis, & Panagiotis G. Sarigiannidis, "Flow anomaly-based intrusion detection system for Android mobile devices." In 2017 6th International Conference on Modern Circuits and Systems Technologies (MOCAST). Thessaloniki, Greece: IEEE (pp. 1–4) 2017.
[14] Abdullah Mohammed Rashid & Ali Taha Al-Oqaily, "Detect and Prevent the Mobile Malware." International Journal of Scientific and Research Publications, 5(5), 1–3 2015.
[15] Muthuswamy, Sujithra & Ganapathi, Padmavathi, "Mobile Device Security: A Survey on Mobile Device Threats, Vulnerabilities and their Defensive Mechanism." International Journal of Computer Applications, 56(14), 0975 – 8887, 2012.
[16] Seungyong Yoon, Yongsung Jeon and Jeongnyeo Kim, "Mobile Security Technology for Smart Devices" International Conference on Information and Communication Technology Convergence (ICTC), Jeju, Korea (South), pp. 1171-1173, 2015.
[17] Jalaluddin Khan, Haider Abbas,and Jalal Al-Muhtadi, “Survey on Mobile User`s Data Privacy Threats and Defense Mechanisms”, Procedia Computer Science, Volume 56, Pages 376-383, ISSN 1877-0509, 2015.
[18] Prabhat Bisht, Manmohan Singh Rauthan, “Machine Learning and Natural Language Processing Based Web Application Firewall for Mitigating Cyber Attacks in Cloud,” International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.3, pp.1-15, 2023
[19] Vikas Singhal, Devendra Singh, Sanjai Kumar Gupta, “Data Encryption Technique based on Enhancement of Blowfish Algorithm in Comparison of DES & DCT Methods” International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.3, pp.16-21, 2023.