Counting-based secret sharing technique for multimedia applications

Gutub, Adnan; Al-Juaid, Nouf; Khan, Esam

doi:10.1007/s11042-017-5293-6

Cited by 145 publications

(80 citation statements)

References 16 publications

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“…In fact, the timing performance is found common within this authentication study similar in principle to the cryptography security analysis in previous studies of GF(p) hardware modeling [21] as well as elliptic curve GF(2) crypto processors simulations [22]. The security analysis can have different factors to build its test on such as bit-ratio differences found within secret sharing studies [23]. This work testing scope is based on the timing and PSNR assumed to provide fair comparison showing attractive open research improvement over [6].…”

Section: Results and Comparisonssupporting

confidence: 62%

Secure Mobile Computing Authentication Utilizing Hash, Cryptography and Steganography Combination

Alotaibi

Al-hendi

Al-Roithy

et al. 2019

JISCR

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In this paper, we propose a modification for security authentication systems in mobile devices. Our enhancement is designed to secure information transformation over the internet by combining hash, cryptography and steganography mechanisms. We used the combination for authentication, to secure mobile computing to transfer data in a trusted manner. The proposed work will use hash function to store the secret password to provide increased security. The hashed password is encrypted using AES encryption then hidden inside an image to be called back for authentication whenever needed. The security services provided by this combination mechanisms can assure authenticity, confidentiality, and integrity. Results and comparisons to different options of available mobile computing methods proved that our proposed technique is a promising research direction for real mobile security.

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Section: Results and Comparisonssupporting

confidence: 62%

Secure Mobile Computing Authentication Utilizing Hash, Cryptography and Steganography Combination

Alotaibi

Al-hendi

Al-Roithy

et al. 2019

JISCR

Self Cite

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“…The lack of security features affects the patient security and privacy. The proposed OLPP method might contribute in extracting the best features for the encryption of the data [48][49][50][51]. Furthermore, the application of proposed method can also be applied to the field of steganography.…”

Section: Discussionmentioning

confidence: 99%

Using orthogonal locality preserving projections to find dominant features for classifying retinal blood vessels

Relan

Ballerini

Trucco

et al. 2018

Multimed Tools Appl

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Automatically classifying retinal blood vessels appearing in fundus camera imaging into arterioles and venules can be problematic due to variations between people as well as in image quality, contrast and brightness. Using the most dominant features for retinal vessel types in each image rather than predefining the set of characteristic features prior to classification may achieve better performance. In this paper, we present a novel approach to classifying retinal vessels extracted from fundus camera images which combines an Orthogonal Locality Preserving Projections for feature extraction and a Gaussian Mixture Model with Expectation-Maximization unsupervised classifier. The classification rate with 47 features (the largest dimension tested) using OLPP on our own ORCADES dataset and the publicly available DRIVE dataset was 90.56% and 86.7% respectively.

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“…Given to the increasing demand for web applications and the continuous growth of a number of networks users involving Cloud computing, E-Government, E-Commerce, E-Business, online banking services, which all contain sensitive information, it may be vulnerable to theft or access by wrong persons or even destroyed by hackers or service providers as non-trusted agencies in many cases. Therefore, there is an urgent need for information security with its three main components: Confidentiality, Integrity, and Availability (CIA) [1].…”

Section: Introductionmentioning

confidence: 99%

“…In fact, the security techniques, i.e. cryptography and steganography, focus on the phenomena that one person is in the controlling seat who is in charge of the secrecy of information [1]. However, the question is what happens when the encrypted or hidden data are corrupted, or the secret key is lost.…”

Section: Introductionmentioning

confidence: 99%

Reliable Secret Key Generation For Counting-Based Secret Sharing

Al-Qurashi¹,

Gutub²

2018

JCSCM

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Secret sharing scheme is becoming famous for increasing the security to access sensitive information for applications and resources that have to be protected by more than one person. It divides the secret key into shares, distributed to participants such that only subsets of participants can reconstruct the secret key. This paper adopts counting-based secret sharing scheme as a promising secret sharing technique presented recently. This counting-based method works on constructing shares by changing one or two 0-bits within the secret key to one at different locations for producing needed shares. The combination of selected shares is counting the ones in parallel to recover the secret key. This paper proposed improving the reliability of this counting-based secret sharing scheme by increasing the size of the secret key to 64-bits as realistically needed by most applications. The work also improved the security of the secret key affecting its shares by adjusting the generation algorithm to involve applicable statistical randomness tests from NIST 800-22 standard where any unreliable secret key is regenerated again whenever needed. The proposal is implemented and compared with the original scheme via Java platform modeling showing interesting practical remarks providing remarkable contributions.

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Counting-based secret sharing technique for multimedia applications

Cited by 145 publications

References 16 publications

Secure Mobile Computing Authentication Utilizing Hash, Cryptography and Steganography Combination

Secure Mobile Computing Authentication Utilizing Hash, Cryptography and Steganography Combination

Using orthogonal locality preserving projections to find dominant features for classifying retinal blood vessels

Reliable Secret Key Generation For Counting-Based Secret Sharing

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