A Review of Mobile Surveillanceware: Capabilities, Countermeasures, and Research Challenges

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Udgivet i:Electronics vol. 14, no. 14 (2025), p. 2763-2792
Hovedforfatter: Anglano Cosimo
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MDPI AG
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100 1 |a Anglano Cosimo 
245 1 |a A Review of Mobile Surveillanceware: Capabilities, Countermeasures, and Research Challenges 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Mobile smartphones are prime targets for sophisticated surveillanceware, designed to covertly monitor specific individuals. While mobile operating systems implement various protection mechanisms, their defenses are frequently bypassed due to risky user behaviors or underlying software flaws, leading to persistent successful attacks. This paper addresses the critical research problem of how targeted mobile spyware can be effectively counteracted, particularly given its pervasive and evolving threat amplified by sophisticated evasion techniques. To contribute to this understanding, we comprehensively review mobile surveillanceware variants, namely stalkerware and mercenary spyware. We also critically review mobile OS protection mechanisms, and we detail how surveillanceware bypasses or exploits them. Our analysis reveals that, despite continuous efforts by mobile operating system and device manufacturers, both Android and iOS platforms struggle to protect devices and users, particularly against sophisticated mercenary spyware attacks, remaining vulnerable to these threats. Finally, we systematically review state-of-the-art countermeasures, identify their shortcomings, and highlight unresolved research challenges and concrete directions for future investigation for enhanced prevention and detection. Crucially, this future research must increasingly leverage artificial intelligence, including deep learning and large language models, to effectively keep pace with and overcome the sophisticated tactics employed by modern spyware. 
653 |a Operating systems 
653 |a Smartphones 
653 |a Large language models 
653 |a Exploitation 
653 |a National security 
653 |a State-of-the-art reviews 
653 |a Intelligence gathering 
653 |a Data collection 
653 |a Surveillance 
653 |a Artificial intelligence 
653 |a Machine learning 
653 |a Espionage 
653 |a Access control 
653 |a Mobile operating systems 
653 |a Consent 
773 0 |t Electronics  |g vol. 14, no. 14 (2025), p. 2763-2792 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
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