Design a system for an approved video copyright over cloud based on biometric iris and random walk generator using watermark technique

Copyright is a tool for preventing anyone forged to copy an electronic work from another person and claim that electronic work is referred to him. Since the identity of the person is always determined by his name and biometrics, there is a concern to handle this information, to preserve the copyright. In this paper, a new idea for copyright technology is used to prove video copyright, by using blind watermarking technique, the ownership information is hidden inside video frames using linear congruential generator (LCG) for adapted the locations of vector features extracted from the name and biometric image of the owner instead of hidden the watermark in the Pseudo Noise sequences or any other feature extraction technique. When providing the watermarked vector, a statistical operation is used to increase randomization state for the amplifier factors of LCG function. LCG provides random positions where the owner's information is stored inside the video. The proposed method is not difficult to execute and can present an adaptable imperceptibility and robustness performance. The output results show the robustness of this approach based on the average PSNR of frames for the embedded in 50 frames is around 47.5 dB while the watermark remains undetectable. MSSIM values with range (0.83 to 0.99)

Tamper detection of qur'anic text watermarking scheme based on vowel letters with Kashida using exclusive-or and queueing technique

The most sensitive Arabic text available online is the digital Holy Qur’an. This sacred Islamic religious book is recited by all Muslims worldwide including the non-Arabs as part of their worship needs. It should be protected from any kind of tampering to keep its invaluable meaning intact. Different characteristics of the Arabic letters like the vowels ( أ . و . ي ), Kashida (extended letters), and other symbols in the Holy Qur’an must be secured from alterations. The cover text of the al-Qur’an and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR), Embedding Ratio (ER), and Normalized Cross-Correlation (NCC), thus the location for tamper detection gets low accuracy. Watermarking technique with enhanced attributes must therefore be designed for the Qur’an text using Arabic vowel letters with Kashida. Most of the existing detection methods that tried to achieve accurate results related to the tampered Qur’an text often show various limitations like diacritics, alif mad surah, double space, separate shapes of Arabic letters, and Kashida. The gap addressed by this research is to improve the security of Arabic text in the Holy Qur’an by using vowel letters with Kashida. The purpose of this research is to enhance Quran text watermarking scheme based on exclusive-or and reversing with queueing techniques. The methodology consists of four phases. The first phase is pre-processing followed by the embedding process phase to hide the data after the vowel letters wherein if the secret bit is ‘1’, insert the Kashida but do not insert it if the bit is ‘0’. The third phase is extraction process and the last phase is to evaluate the performance of the proposed scheme by using PSNR (for the imperceptibility), ER (for the capacity), and NCC (for the security of the watermarking). The experimental results revealed the improvement of the NCC by 1.77 %, PSNR by 9.6 %, and ER by 8.6 % compared to available current schemes. Hence, it can be concluded that the proposed scheme has the ability to detect the location of tampering accurately for attacks of insertion, deletion, and reordering

EFFICIENT DATA PROTECTION BY NOISING, MASKING, AND METERING

Protecting data secrecy is an important design goal of computing systems. Conventional techniques like access control mechanisms and cryptography are widely deployed, and yet security breaches and data leakages still occur. There are several challenges. First, sensitivity of the system data is not always easy to decide. Second, trustworthiness is not a constant property of the system components and users. Third, a system’s functional requirements can be at odds with its data protection requirements. In this dissertation, we show that efficient data protection can be achieved by noising, masking, or metering sensitive data. Specifically, three practical problems are addressed in the dissertation—storage side-channel attacks in Linux, server anonymity violations in web sessions, and data theft by malicious insiders. To mitigate storage side-channel attacks, we introduce a differentially private system, dpprocfs, which injects noise into side-channel vectors and also reestablishes invariants on the noised outputs. Our evaluations show that dpprocfs mitigates known storage side channels while preserving the utility of the proc filesystem for monitoring and diagnosis. To enforce server anonymity, we introduce a cloud service, PoPSiCl, which masks server identifiers, including DNS names and IP addresses, with personalized pseudonyms. PoPSiCl can defend against both passive and active network attackers with minimal impact to web-browsing performance. To prevent data theft from insiders, we introduce a system, Snowman, which restricts the user to access data only remotely and accurately meters the sensitive data output to the user by conducting taint analysis in a replica of the application execution without slowing the interactive user session.Doctor of Philosoph