By: Gonipalli Bharath, Vel Tech University, Chennai, India, International Center for AI and Cyber Security Research and Innovations, Asia University, Taiwan, Gmail: gonipallibharath@gmail.com
Abstract:
Smishing is a form of phishing in which the wicked factor involves SMS for sending malicious links or scams. It was among the growing threats in the digital world. Smishing scams, with the use of sophisticated AI-powered tools to help in crafting more convincing and targeted smishing scams, keep cybercriminals one step ahead. The article covers the future of smishing, how AI can make such scams even more effective, and how individuals and organizations can protect themselves from this evolving threat. Also attached is a flowchart to put into perspective how phishing scams-smishing included-are carried out.
Introduction:
The growth of the usage of mobile phones created the revolution of communication and, at the same time, new opportunities developed for cybercrime. Among those insidious menaces of the digital age comes smishing-scammers who attempt to phish targeted victims using short messages. This is usually sent by somebody posing as reputable entities, such as banks, government agencies, or popular companies, in an attempt to reveal sensitive information such as passwords, credit card numbers, or even personal identification[[1]]. The next step in the evolution of smishing will be to take a turn for more AI-powered capabilities that allow scammers to auto-personalize the attacks, making them more subtle and tricky to identify. Understanding this new face of smishing and the ways of protecting ourselves is crucial in taking care of personal and financial security.
Smishing: The Role of AI
AI has completely changed the dynamics of cybersecurity for both attackers and defenders. Smishing scams powered by artificial intelligence are specifically hazardous because they can:
- Personalize Scams: By parsing through data on social media, among other virtual hangouts, AI can make tailored messages more likely to be clicked on with a malicious link or shared information.
- Smishing Attack Campaign Automation: AI supports attackers in scaling smishing attacks, allowing them to send several or even millions of text messages with very little work. Attacks can use machine learning algorithms to improve scam tactics based on responses and thereby raise the success rate of an attack.
- Spoof Messages with the Appearance of Trust: AI can be used to copy the writing of someone or something trusted, thereby giving that text message a better appearance of authenticity. This could be copying the verbiage from a bank in communication or even the SMS style of a company that the victim regularly interacts with[[2]].
How Smishing Works
Smishing follows a typical pattern:
- First SMS: Unsolicited messages are sent to the victim, and the content may claim that urgent action is required on account verification, prize collection, or security updates.
- Malicious Links: These are links which direct the victim to fake websites in order to steal information or install malware on the victim’s machine.
- Data Harvesting or Malware Infection: after the victim clicks on the link, he or she is either asked to input sensitive information or is prompted to download malware which infects a device.
fig(1)
Smishing of the Future: Trends and Predictions
Deepfake Technology: Very soon, AI might allow fraudsters to send voice messages or even video messages impersonating legitimate people, say, a bank representative, to make smishing attempts look believable.
Convergence of Voice Phishing-Vishing: AI-driven smishing attacks can also extend to vishing-voice phishing-in which AI generates a convincing voice call that deceives victims into giving away confidential information.
Cross-Platform Attacks: Smishing will perhaps start overlapping with other types of cyberattacks, like phishing through emails or social media, which further confuses the user in identifying what is real communication and what is not[[3]].
fig(2)
How to Stay Safe:
While AI-powered smishing is more dangerous, there are ways individuals can stay safe. It’s all about being cautious with unsolicited messages, especially those requesting links or personal information. Never click on links from unknown senders or messages suspicious to you, even if they appear to be from a trusted source. This being said, whenever any message or request is apparently coming from any bank or valid organization, the request needs to be checked by directly contacting the same via officially recognized contact information. The attackers would, however, be faced with very slim chances of succeeding in access in the event that multi-factor authentication has been provided on an account. Moreover, installing anti-malware and anti-phishing on your device will help in detecting and blocking attempts at smishing before they even succeed. Also, educating others, especially those who are less familiar with the threats of digital security, helps reduce the general risk of smishing attacks[[4]].
Conclusion:
Future of smishing goes hand in hand with the unrelenting development of AI, equipping cybercriminals with powerful weapons to create an increasingly convincing, scalable attack. As smishing becomes more advanced, it is awareness and vigilance that help people avoid becoming victims. We can afford better defense through verification of sources, use of security tools, and education among others against these increasing AI smishing attacks.
References:
- Bundala, Ntogwa N. “Detecting and Mitigating Cyber-Psychological Tricks and Cyber-Technical Tricks in Cyberattacks,” n.d.
- Mishra, Sandhya, and Devpriya Soni. “Smishing Detector: A Security Model to Detect Smishing through SMS Content Analysis and URL Behavior Analysis.” Future Generation Computer Systems 108 (July 1, 2020): 803–15. https://doi.org/10.1016/j.future.2020.03.021.
- Seth, Prerna, and Madhavi Damle. “A Comprehensive Study of Classification of Phishing Attacks with Its AI/I Detection.” In 2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC), 370–75, 2022. https://doi.org/10.1109/IIHC55949.2022.10060305.
- Yeboah-Boateng, Ezer Osei, and Priscilla Mateko Amanor. “Phishing, SMiShing & Vishing: An Assessment of Threats against Mobile Devices” 5, no. 4 (2014).
Sandhya Mishra and Devpriya Soni, “Smishing Detector: A Security Model to Detect Smishing through SMS Content Analysis and URL Behavior Analysis,” Future Generation Computer Systems 108 (July 1, 2020): 803–15, https://doi.org/10.1016/j.future.2020.03.021. ↑
Prerna Seth and Madhavi Damle, “A Comprehensive Study of Classification of Phishing Attacks with Its AI/I Detection,” in 2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC), 2022, 370–75, https://doi.org/10.1109/IIHC55949.2022.10060305. ↑
- Ntogwa N Bundala, “Detecting and Mitigating Cyber-Psychological Tricks and Cyber-Technical Tricks in Cyberattacks,” n.d. ↑
Ezer Osei Yeboah-Boateng and Priscilla Mateko Amanor, “Phishing, SMiShing & Vishing: An Assessment of Threats against Mobile Devices” 5, no. 4 (2014). ↑
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- A. Dahiya, B. B. Gupta (2021) How IoT is Making DDoS Attacks More Dangerous?, Insights2Techinfo, pp.1
Cite As
Bharath G. (2025) The Rise of AI Smishing: Protecting Yourself from Next-Gen Scams, Insights2Techinfo, pp.1