Journal ArticleDOI
Secure Transmission of Compressed Sampling Data Using Edge Clouds
TLDR
A secure transmission framework for CS data by combining CS-based cipher and edge computing is proposed and is very useful for resource-limited IoT applications.Abstract:
Cloud capability is considered to be extended to the edge of the Internet for improving the security of data transmission. Compressive sensing (CS) has been widely studied as a built-in privacy-preserving layer to provide some cryptographic features while sampling and compressing, including data confidentiality guarantees and data integrity guarantees. Unfortunately, most existing CS-based ciphers are too lightweight or highly complex to meet the requirements of both high security of transmitting the captured data over the Internet and low energy consumption of sensing devices in the Internet of Things (IoT). In this article, a secure transmission framework for CS data by combining CS-based cipher and edge computing is proposed. From the perspective of security, the double-layer encryption mechanism and double-layer authentication mechanism are rooted in it by performing some privacy-preserving operations, including CS-based encryption, CS-based hash, information splitting, strong encryption, and feature extraction. Most significantly, the proposed framework is very useful for resource-limited IoT applications.read more
Citations
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Journal ArticleDOI
A Novel Image Steganography Method for Industrial Internet of Things Security
TL;DR: Using the HHO-IWT method for covert communication and secure data in the IIoT environment based on digital image steganography achieves higher levels of security than the state-of-the-art methods and it resists various forms of steganalysis.
Journal ArticleDOI
Low-cost and secure multi-image encryption scheme based on P-tensor product compressive sensing
Di Xiao,Minhui Zhao,Mengdi Wang +2 more
TL;DR: This paper proposes a double-layer multi-image encryption scheme with lower storage consumption and higher security based on P-tensor product CS, and makes full play to the advantages of P-Tensor product in matrix multiplication.
Journal ArticleDOI
Cryptanalzing a Novel Hyper-Chaotic Image Encryption Scheme Based on Pixel-Level Filtering and DNA-Level Diffusion
Wei Feng,Jing Zhang +1 more
TL;DR: It is found that PFDD does not have its claimed ability to resist chosen-plaintext attacks (CPAs), so under the conditions of CPAs, the entire encryption process of PFDD is cryptanalyzed, and successfully crack it by the proposed attack algorithm.
Journal ArticleDOI
Generating visually secure encrypted images by partial block pairing-substitution and semi-tensor product compressed sensing
TL;DR: This paper proposes a novel visually secure image encryption scheme by combining semi-tensor product compressed sensing and partial block pairing-substitution technique, which demonstrates the high quality of the cipher images and the high security of the proposed scheme.
Journal ArticleDOI
Cryptanalysis and Improvement of the Image Encryption Scheme Based on Feistel Network and Dynamic DNA Encoding
TL;DR: In this paper, a newly reported image encryption scheme based on Feistel network and dynamic Deoxyribonucleic acid (DNA) encoding is deeply and comprehensively investigated, and several necessary improvements to this encryption scheme and proposed the corresponding chosen-plaintext attack algorithm.
References
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Book
Compressed sensing
TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
Journal ArticleDOI
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
TL;DR: In this paper, the authors considered the model problem of reconstructing an object from incomplete frequency samples and showed that with probability at least 1-O(N/sup -M/), f can be reconstructed exactly as the solution to the lscr/sub 1/ minimization problem.
Journal ArticleDOI
An Introduction To Compressive Sampling
TL;DR: The theory of compressive sampling, also known as compressed sensing or CS, is surveyed, a novel sensing/sampling paradigm that goes against the common wisdom in data acquisition.
Journal ArticleDOI
Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility
TL;DR: This paper defines Cloud computing and provides the architecture for creating Clouds with market-oriented resource allocation by leveraging technologies such as Virtual Machines (VMs), and provides insights on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain Service Level Agreement (SLA) oriented resource allocation.
Posted Content
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
Emmanuel J. Candès,Terence Tao +1 more
TL;DR: In this article, it was shown that if the objects of interest are sparse or compressible in the sense that the reordered entries of a signal $f \in {\cal F}$ decay like a power-law, then it is possible to reconstruct $f$ to within very high accuracy from a small number of random measurements.
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