Biblio
In cyberspace, a digital signature is a mathematical technique that plays a significant role, especially in validating the authenticity of digital messages, emails, or documents. Furthermore, the digital signature mechanism allows the recipient to trust the authenticity of the received message that is coming from the said sender and that the message was not altered in transit. Moreover, a digital signature provides a solution to the problems of tampering and impersonation in digital communications. In a real-life example, it is equivalent to a handwritten signature or stamp seal, but it offers more security. This paper proposes a scheme to enable users to digitally sign their communications by validating their identity through users’ mobile devices. This is done by utilizing the user’s ambient Wi-Fi-enabled devices. Moreover, the proposed scheme depends on something that a user possesses (i.e., Wi-Fi-enabled devices), and something that is in the user’s environment (i.e., ambient Wi-Fi access points) where the validation process is implemented, in a way that requires no effort from users and removes the "weak link" from the validation process. The proposed scheme was experimentally examined.
An acoustic fingerprint is a condensed and powerful digital signature of an audio signal which is used for audio sample identification. A fingerprint is the pattern of a voice or audio sample. A large number of algorithms have been developed for generating such acoustic fingerprints. These algorithms facilitate systems that perform song searching, song identification, and song duplication detection. In this study, a comprehensive and powerful survey of already developed algorithms is conducted. Four major music fingerprinting algorithms are evaluated for identifying and analyzing the potential hurdles that can affect their results. Since the background and environmental noise reduces the efficiency of music fingerprinting algorithms, behavioral analysis of fingerprinting algorithms is performed using audio samples of different languages and under different environmental conditions. The results of music fingerprint classification are more successful when deep learning techniques for classification are used. The testing of the acoustic feature modeling and music fingerprinting algorithms is performed using the standard dataset of iKala, MusicBrainz and MIR-1K.
With the development of e-Science and data intensive scientific discovery, it needs to ensure scientific data available for the long-term, with the goal that the valuable scientific data should be discovered and re-used for downstream investigations, either alone, or in combination with newly generated data. As such, the preservation of scientific data enables that not only might experiment be reproducible and verifiable, but also new questions can be raised by other scientists to promote research and innovation. In this paper, we focus on the two main problems of digital preservation that are format migration and preservation metadata. Format migration includes both format verification and object transformation. The system architecture of format migration and preservation metadata is presented, mapping rules of object transformation are analyzed, data fixity and integrity and authenticity, digital signature and so on are discussed and an example is shown in detail.
Digital signal processing (DSP) and multimedia based reusable Intellectual property (IP) cores form key components of system-on-chips used in consumer electronic devices. They represent years of valuable investment and hence need protection against prevalent threats such as IP cloning and fraudulent claim of ownership. This paper presents a novel crypto digital signature approach which incorporates multiple security modules such as encryption, hashing and encoding for protection of digital signature processing cores. The proposed approach achieves higher robustness (and reliability), in terms of lower probability of coincidence, at lower design cost than existing watermarking approaches for IP cores. The proposed approach achieves stronger proof of authorship (on average by 39.7%) as well as requires lesser storage hardware compared to a recent similar work.
This study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subjects and it achieved 94% recognition accuracy. A crypto-tool software was used to perform the randomness test on the proposed RSA and SHA256.
Public key cryptography plays a vital role in many information and communication systems for secure data transaction, authentication, identification, digital signature, and key management purpose. Elliptic curve cryptography (ECC) is a widely used public key cryptographic algorithm. In this paper, we propose a hardware-software codesign implementation of the ECC cipher. The algorithm is modelled in C language. Compute-intensive components are identified for their efficient hardware implementations. In the implementation, residue number system (RNS) with projective coordinates are utilized for performing the required arithmetic operations. To manage the hardware-software codeign in an integrated fashion Xilinx platform studio tool and Virtex-5 xc5vfx70t device based platform is utilized. An application of the implementation is demonstrated for encryption of text and its respective decryption over prime fields. The design is useful for providing an adequate level of security for IoTs.