Design Science Research towards Privacy by Design in Maritime Surveillance ICT Systems

Rajamäki, Jyri

doi:10.11610/isij.4316

Cited by 1 publication

(1 citation statement)

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“…Other similar data privacy regulations to GDPR now exist in other countries. GDPR itself focuses on reversible data protection via encryption [5] as a data-protection safeguard [6], which encryption is also employed herein. For example, in [7], a chain-of-evidence is kept for forensics purposes but a blockchain is employed to store hashes of information gathered, which may add to the complexity of the method.…”

Section: Introductionmentioning

confidence: 99%

Preserving Chain-of-Evidence in Surveillance Videos for Authentication and Trust-Enabled Sharing

et al. 2020

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Surveillance video recording is a powerful method of deterring unlawful activities. A robust data protection-by-design solution can be helpful in terms of making a captured video immutable, as such recordings cannot become a piece of evidence until proven to be unaltered. Similarly, video sharing from closed-circuit television video recording or in social media interaction requires self-authentication for responsible and reliable data sharing. This article presents a computationally inexpensive method of preserving a chain-of-evidence in surveillance videos by means of hashing and steganography. The method conforms to the data protection regulations, which are increasingly adopted by governments, and is applicable to network edge storage. Encryption keys are stored in a hardware wallet independently of the video capture device itself, while evidential information is stored steganographically within video frames themselves, independently of the content. Added protection is provided by hiding information within the two least-valued of pixel bitplanes, using a newly introduced technique that randomizes the pixel storage locations on a per video frame and video-capture device basis. Overall, the proposed method has turned out to not only preserve the integrity of stored video data but also results in minimal degradation of the video data resulting from steganography. Despite the inclusion of hidden information, video frames will still be available for common image-processing tasks such as tracking and classification, as their objective video quality is almost unchanged.

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Section: Introductionmentioning

confidence: 99%