Smartphone-Based Sensing Network for Emergency Detection: A Privacy-Preserving Framework for Trustworthy Digital Governance
Source abstract
Abstract
Smartphones are ubiquitous and continuously carried high-performance devices equipped with speech recognition capabilities that enable the analysis of surrounding conversations. When leveraged for public purposes, networks of smartphones can function as a large-scale sensing infrastructure capable of detecting and reporting early signs of serious crimes or terrorist activities. This paper proposes the concept of “Smartphone as Societal Safety Guard” as an approach to substantially enhancing public safety through relatively low additional cost and the combination of existing technologies (first pillar). At the same time, this concept entails serious risks of privacy infringement, as exemplified by the potential introduction of always-on eavesdropping through operating system updates. The originality of this study lies in redefining smartphones not merely as personal tools but as public safety infrastructure within democratic societies, and in systematizing the conditions for their social acceptability from the perspective of institutional design. This research presents a reference architecture and a regulatory framework, and organizes six key challenges that must be addressed to reconcile public safety with privacy protection: external attacks, mitigation of privacy information, false positives, expansion of the scope of application, discriminatory use, and misuse by authorized insiders. In particular, misuse by authorized insiders is positioned as the core challenge. As a necessary condition for acceptance in democratic societies (second pillar), this paper proposes a privacy-protective infrastructure centered on the Verifiable Record of AI Output (VRAIO). By combining on-device two-stage urgency classification with the review and recording of AI outputs by independent third-party entities, the proposed framework aims to provide a mechanism that can ensure, as a design requirement, that information unrelated to emergencies is not released outside the device. In summary, this paper presents a design framework for reconciling enhanced public safety with the protection of privacy.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Privacy, Security, and Data Protection · Mobile Crowdsensing and Crowdsourcing · Advanced Malware Detection Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Science and Technology, Gunma University, Kiryu 376-8515, Japan
Funding
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research
References (76)
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