The rapid development of technology, makes it easier for everyone to exchange information and knowledge. Exchange information via the internet is threatened with security. Security issues, especially the issue of the confidentiality of information content and its authenticity, are vital things that must protect. Peculiarly for agencies that often hold activities that provide certificates in digital form to participants. Digital certificates are digital files conventionally used as proof of participation or a sign of appreciation owned by someone. We need a security technology for certificates as a source of information known as cryptography. This study aims to validate and authenticate digital certificates with digital signatures using SHA-256, DSA, and 3DES. The use of the SHA-256 hash function is in line with the DSA method and the implementation of 3DES which uses 2 private keys so that the security of digital certificate files can be increased. The pixel changes that appear in the MSE calculation have the lowest value of 7.4510 and the highest value of 165.0561 when the file is manipulated, it answers the security of the proposed method is maintained because the only valid file is the original file.

Recently, placing vehicles in the parking area is becoming a problem. A smart parking system is proposed to solve the problem. Most smart parking systems have a centralized system, wherein that type of system is at-risk of single-point failure that can affect the whole system. To overcome the weakness of the centralized system, the most popular mechanism that researchers proposed is blockchain. If there is no mechanism implemented in the blockchain to verify the authenticity of every transaction, then the system is not secure against impersonation attacks. This study combines blockchain mechanism with Ring Learning With Errors (RLWE) based digital signature for securing the scheme against impersonation and double-spending attacks. RLWE was first proposed by Lyubashevsky et al. This scheme is a development from the previous scheme Learning with Error or LWE.

In this paper, we propose a novel watermarking-based copy deterrence scheme for identifying data leaks through authorized query users in secure image outsourcing systems. The scheme generates watermarks unique to each query user, which are embedded in the retrieved encrypted images. During unauthorized distribution, the watermark embedded in the image is extracted to determine the untrustworthy query user. Experimental results show that the proposed scheme achieves minimal information loss, faster embedding and better resistance to JPEG compression attacks compared with the state-of-the-art schemes.

Differential privacy mechanisms have been proposed to guarantee the privacy of individuals in various types of statistical information. When constructing a probabilistic mechanism to satisfy differential privacy, it is necessary to consider the impact of an arbitrary record on its statistics, i.e., sensitivity, but there are situations where sensitivity is difficult to derive. In this paper, we first summarize the situations in which it is difficult to derive sensitivity in general, and then propose a definition equivalent to the conventional definition of differential privacy to deal with them. This definition considers neighboring datasets as in the conventional definition. Therefore, known differential privacy mechanisms can be applied. Next, as an example of the difficulty in deriving sensitivity, we focus on the t-test, a basic tool in statistical analysis, and show that a concrete differential privacy mechanism can be constructed in practice. Our proposed definition can be treated in the same way as the conventional differential privacy definition, and can be applied to cases where it is difficult to derive sensitivity.