Confidentiality-Preserving Image Search: A Comparative Study Between Homomorphic Encryption and Distance-Preserving Randomization
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TLDR
This paper focuses on comparing these two major paradigms of techniques, namely, homomorphic encryption-based techniques and feature/index randomization- based techniques, for confidentiality-preserving image search, and develops novel and systematic metrics to quantitatively evaluate security strength in this unique type of data and applications.Abstract:
Recent years have seen increasing popularity of storing and managing personal multimedia data using online services. Preserving confidentiality of online personal data while offering efficient functionalities thus becomes an important and pressing research issue. In this paper, we study the problem of content-based search of image data archived online while preserving content confidentiality. The problem has different settings from those typically considered in the secure computation literature, as it deals with data in rank-ordered search, and has a different security-efficiency requirement. Secure computation techniques, such as homomorphic encryption, can potentially be used in this application, at a cost of high computational and communication complexity. Alternatively, efficient techniques based on randomizing visual feature and search indexes have been proposed recently to enable similarity comparison between encrypted images. This paper focuses on comparing these two major paradigms of techniques, namely, homomorphic encryption-based techniques and feature/index randomization-based techniques, for confidentiality-preserving image search. We develop novel and systematic metrics to quantitatively evaluate security strength in this unique type of data and applications. We compare these two paradigms of techniques in terms of their search performance, security strength, and computational efficiency. The insights obtained through this paper and comparison will help design practical algorithms appropriate for privacy-aware cloud multimedia systems.read more
Citations
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Security and Privacy in Cloud Computing
TL;DR: Significant research and development efforts in both industry and academia aim to improve the cloud's security and privacy.
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EPCBIR: An efficient and privacy-preserving content-based image retrieval scheme in cloud computing
TL;DR: A scheme that supports CBIR over the encrypted images without revealing the sensitive information to the cloud server is proposed and the security and efficiency of the proposed scheme are shown.
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Hash Based Encryption for Keyframes of Diagnostic Hysteroscopy
TL;DR: An image color coding method aimed at increasing the security of keyframes extracted from diagnostic hysteroscopy videos using video summarization using a 2-D logistic map, which relies on mixing and cascading the orbits of the chaotic map in order to generate the stream keys for the encryption algorithm.
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A Lightweight Privacy-Preserving CNN Feature Extraction Framework for Mobile Sensing
TL;DR: This paper proposes a novel lightweight framework for privacy-preserving CNN feature extraction for mobile sensing based on edge computing that allows us to significantly reduce the latency and the overhead of the end devices while preserving privacy.
Proceedings ArticleDOI
SEISA: Secure and efficient encrypted image search with access control
TL;DR: A lightweight secure image search scheme over encrypted data, namely SEISA is proposed, which only increases about 9% search cost and sacrifices about 3% on search accuracy, and a secure k-means outsourcing algorithm that significantly saves the data owner's cost is designed.
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