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A Case Study on Smishing: An Assessment of Threats against Mobile Devices

Published: 20 August 2023 Publication History

Abstract

Smartphones emerged as a sector of outstanding the growth and development with the advent of smart homes, cities, and everything. These gadgets have been integrated into ordinary human activity. Due to their influence and expansion, these gadgets are now more susceptible to attacks than other devices like desktops or laptops. Smartphones include text messaging capabilities, often known as SMS (Short Text Messages), which attackers use to target consumers. Smishing (SMS) is an assault using text messages to target smartphone users. The main purpose of the case study was to assess vulnerability of various attacks; this study investigates the threats against mobile devices and their many forms of attacks to prevent, lessen, and end these kinds of attacks and suggests various approaches to deal with the country's current problem about the sms attack problems.

References

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A.Parti (2022). “What is Smishing - Everything you need to know.” Available: https://www.heyhack.com/post/what-is-smishing
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M. Boodae, "Mobile Users Tluee Timcs Morc Vulncrablc to Phishing attacks" in Trusteer vol. 2012. €d, 2011
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K. Dunham, “Chapter 6 - Phishing. SMishing. and Vishing," in Mobile Malware Attacks and Defense. D. Ken. Ed., cd Boston:Syngress. 2009. pp. 125-l 96.
[4]
Mishra, S., & Soni, D. (2021). DSmishSMS-A System to Detect Smishing SMS. Neural Computing and Applications. https://doi.org/10.1007/s00521-021-06305-y
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Jain, A. K., & Gupta, B. B. (2018). Rule-Based Framework for Detection of Smishing Messages in Mobile Environment. Procedia Computer Science, 125, 617–623. https://doi.org/10.1016/j.procs.2017.12.079
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Kim, S.-R.: Phishing of the dual criminality. IT and Legal Research 4, 251–290 (2010)
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Mishra S, Soni D. SMS phishing and mitigation approaches. In:Twelfth International Conference on Contemporary Computing (IC3), Noida, India, 2019, pp. 1–5, https://doi.org/10.1109/IC3.2019.8844920.
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GunikhanSonowal K, Kuppusamy S. SmiDCA: An antismishing model with machine learning approach. Comput J.
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Mishra S, Soni D. Smishing detector: a security model to detect smishing through sms content analysis and url behavior analysis. Future Gener Comput Syst 2020;108:803–15. https://doi.org/10. 1016/j.future.2020.03.021, http://www.sciencedirect.com/science/article/pii/S0167739X19318758.
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Kaspersky. 2022. What is Smishing and How to Defend Against it. Available: https://www.kaspersky.com/resource-center/threats/what-is-smishing-and-how-to-defend-against-it

Cited By

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  • (2024)Chat or Trap? Detecting Scams in Messaging Applications with Large Language Models2024 8th Cyber Security in Networking Conference (CSNet)10.1109/CSNet64211.2024.10851753(92-99)Online publication date: 4-Dec-2024
  • (2024)Unmasking the Threat: Analyzing and Mitigating SMS Smishing AttacksProceedings of Ninth International Congress on Information and Communication Technology10.1007/978-981-97-5441-0_7(69-78)Online publication date: 18-Dec-2024

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  1. A Case Study on Smishing: An Assessment of Threats against Mobile Devices

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    cover image ACM Other conferences
    ICCTA '23: Proceedings of the 2023 9th International Conference on Computer Technology Applications
    May 2023
    270 pages
    ISBN:9781450399579
    DOI:10.1145/3605423
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 20 August 2023

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    Author Tags

    1. URLs
    2. cybercriminals
    3. malicious
    4. malware
    5. scams
    6. smishing

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    • (2024)Chat or Trap? Detecting Scams in Messaging Applications with Large Language Models2024 8th Cyber Security in Networking Conference (CSNet)10.1109/CSNet64211.2024.10851753(92-99)Online publication date: 4-Dec-2024
    • (2024)Unmasking the Threat: Analyzing and Mitigating SMS Smishing AttacksProceedings of Ninth International Congress on Information and Communication Technology10.1007/978-981-97-5441-0_7(69-78)Online publication date: 18-Dec-2024

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