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Publisher: Academy & Industry Research Collaboration Center (AIRCC)
Journal: Signal & Image Processing
Types: Article
Subjects: Privacy Preserving, Privacy Protection, Video Analy tics, UI-REF, Privacy-by-Co-Design, Filtering, Evaluation, Visual Surveillance, Holistic Privacy I mpact Assessment (H-PIA), Human Judgement and Decision Making Theory (JDM), Pleasure-Pain-Recall Theory l(PPR), Science, Q, Mathematics, QA1-939, Instruments and machines, QA71-90, Electronic computers. Computer science, QA75.5-76.95
In this paper, we present a novel Holistic Framework for Privacy Protection Level Performance Evaluation and Impact Assessment (H-PIA) to support the design and deployment of privacy-preserving filtering techniques as may be co-evolved for video surveillance through user-centred participative engagement and collectively negotiated solution seeking for privacy protection. The proposed framework is based on t he UI-REF normative ethno-methodological framework for Privacy-by-Co-Design which is based on collective-interpretivist and socio-psycho-cognitively rooted Human Judgment and Decision Making (JDM)theory including Pleasure-Pain-Recall (PPR)-theoretic opinion elicitation and analysis. This supports not only the socio-ethically reflective conflicts resol ution, prioritisation and traceability of privacy-preserving requirements evolving through user-centred co-design but also the integration of Key Holistic Performance Indicators (KPIs) comprising a number of objective and subjective evaluation metrics for the design and operational deployment of surveillance data/-video-analytics from a system-of-system-scale context-aware accountability engineering perspective. For the objective tests, we have proposed five crucial criteria to be evaluated to assess the opti mality of the balance of privacy protection and sec urity assurance as may be negotiated with end-users throu gh co-design of a privacy filtering solution. This evaluation is supported by a process of quantitativ e assessment of some of the KPIs through an automat ed objective measurement of the functional performance of the given filter. Additionally, a subjective qualitative user study has been conducted to correl ate with, and cross-validate, the results obtained from the objective assessment of the KPIs. The simulati on results have confirmed the sufficiency, necessit y and efficacy of the UI-REF-based methodologically-guide d framework for Privacy Protection evaluation to enable optimally balanced Privacy Filtering of the video frame whilst retaining the minimum of the information as negotiated per agreed process logic. Insights from this study have served the co-desi gn and deployment optimisation of privacy-preserving video filtering solutions. This UI-REF-based framework has been successfully applied to the evaluation of MediaEval 2012-2013 Privacy Filtering and as such h as served to motivates further innovation in co-design and multi-level, multi-modal impact assessment of multimedia privacy-security-balancing risk mitigati on technologies.
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