Journal ArticleDOI
Indistinguishability of Compressed Encryption With Circulant Matrices for Wireless Security
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This letter studies the security of a CS-based cryptosystem that encrypts a plaintext with a secret circulant matrix and transmits the ciphertext over a wireless channel and develops an upper bound on the entropy.Abstract:
The principle of compressed sensing (CS) can be applied to a cryptosystem in which the sensing matrix is employed for the secret key. In this letter, we study the security of a CS-based cryptosystem that encrypts a plaintext with a secret circulant matrix and transmits the ciphertext over a wireless channel. The relative entropy is considered as a security measure for the indistinguishability of the CS-based cryptosystem. By developing an upper bound on the entropy, the security analysis reveals that the presence of wireless channels and additive noise contributes to reducing the relative entropy of the cryptosystem. Consequently, the CS-based cryptosystem with circulant matrices can guarantee wireless security in terms of the indistinguishability, as long as the channel gains and the plaintext-to-noise power ratio of an adversary are kept to be low for a long keystream and a short ciphertext.read more
Citations
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Journal ArticleDOI
A Review of Physical Layer Security Techniques for Internet of Things: Challenges and Solutions.
TL;DR: This article presents a comprehensive review of the PLS techniques toward IoT applications, and highlights three newly-proposed PLS solutions, which match the features of IoT well and are expected to be applied in the near future.
Journal ArticleDOI
Secure Wireless Communications Based on Compressive Sensing: A Survey
TL;DR: A detailed review for the state-of-the-art of secure CS according to different types of random measurement matrices such as Gaussian matrix, circulant matrix, and other special random matrices establishes theoretical foundations for applications in secure wireless communications.
Journal ArticleDOI
Indistinguishability and Energy Sensitivity of Gaussian and Bernoulli Compressed Encryption
TL;DR: This paper confirms that G-OTS and B-OTS cryptosystems can be strictly and asymptotically indistinguishable, respectively, as long as each plaintext has constant energy, but the indistinguishability is highly sensitive to energy variation of plaintexts.
Journal ArticleDOI
Secure Communications With Asymptotically Gaussian Compressed Encryption
Wonwoo Cho,Nam Yul Yu +1 more
TL;DR: Using the distance metrics, the cryptosystem can be a promising option for secure wireless communications by guaranteeing the indistinguishability against an eavesdropper, as long as each plain text has constant energy.
Book ChapterDOI
Vehicle Communication Using Secrecy Capacity
TL;DR: The relationship between secrecy capacity and various types of parameters that determine secrecy capacity in the vehicular wireless network is examined and new vehicle communication is proposed to maintain a certain level of secrecy capacity according to various parameters.
References
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Book
Elements of information theory
Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
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
Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
Emmanuel J. Candès,Terence Tao +1 more
TL;DR: If the objects of interest are sparse in a fixed basis or compressible, then it is possible to reconstruct f to within very high accuracy from a small number of random measurements by solving a simple linear program.
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.