Biblio

Filters: Author is Lu, S.  [Clear All Filters]
2021-03-09
Sibahee, M. A. A., Lu, S., Abduljabbar, Z. A., Liu, E. X., Ran, Y., Al-ashoor, A. A. J., Hussain, M. A., Hussien, Z. A..  2020.  Promising Bio-Authentication Scheme to Protect Documents for E2E S2S in IoT-Cloud. 2020 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). :1—6.

Document integrity and origin for E2E S2S in IoTcloud have recently received considerable attention because of their importance in the real-world fields. Maintaining integrity could protect decisions made based on these message/image documents. Authentication and integrity solutions have been conducted to recognise or protect any modification in the exchange of documents between E2E S2S (smart-to-smart). However, none of the proposed schemes appear to be sufficiently designed as a secure scheme to prevent known attacks or applicable to smart devices. We propose a robust scheme that aims to protect the integrity of documents for each users session by integrating HMAC-SHA-256, handwritten feature extraction using a local binary pattern, one-time random pixel sequence based on RC4 to randomly hide authentication codes using LSB. The proposed scheme can provide users with one-time bio-key, robust message anonymity and a disappearing authentication code that does not draw the attention of eavesdroppers. Thus, the scheme improves the data integrity for a users messages/image documents, phase key agreement, bio-key management and a one-time message/image document code for each users session. The concept of stego-anonymity is also introduced to provide additional security to cover a hashed value. Finally, security analysis and experimental results demonstrate and prove the invulnerability and efficiency of the proposed scheme.

2018-05-01
Al-Salhi, Y. E. A., Lu, S..  2017.  New Steganography Scheme to Conceal a Large Amount of Secret Messages Using an Improved-AMBTC Algorithm Based on Hybrid Adaptive Neural Networks. 2017 Ieee 3rd International Conference on Big Data Security on Cloud (Bigdatasecurity), Ieee International Conference on High Performance and Smart Computing (Hpsc), and Ieee International Conference on Intelligent Data and Security (Ids). :112–121.

The term steganography was used to conceal thesecret message into other media file. In this paper, a novel imagesteganography is proposed, based on adaptive neural networkswith recycling the Improved Absolute Moment Block TruncationCoding algorithm, and by employing the enhanced five edgedetection operators with an optimal target of the ANNS. Wepropose a new scheme of an image concealing using hybridadaptive neural networks based on I-AMBTC method by thehelp of two approaches, the relevant edge detection operators andimage compression methods. Despite that, many processes in ourscheme are used, but still the quality of concealed image lookinggood according to the HVS and PVD systems. The final simulationresults are discussed and compared with another related researchworks related to the image steganography system.