Non-interactive zero-knowledge proof scheme from RLWE-based key exchange

Lattice-based non-interactive zero-knowledge proof has been widely used in one-way communication and can be effectively applied to resist quantum attacks. However, lattice-based non-interactive zero-knowledge proof schemes have long faced and paid more attention to some efficiency issues, such as proof size and verification time. In this paper, we propose the non-interactive zero-knowledge proof schemes from RLWE-based key exchange by making use of the Hash function and public-key encryption. We then show how to apply the proposed schemes to achieve the fixed proof size and rapid public verification. Compared with previous approaches, our schemes can realize better effectiveness in proof size and verification time. In addition, the proposed schemes are secure from completeness, soundness, and zero-knowledge.

Exploration of Student Thinking Process in Proving Mathematical Statements

A mathematical statement is not a theorem until it has been carefully derived from previously proven axioms, definitions and theorems. The proof of a theorem is a logical argument that is given deductively and is often interpreted as a justification for statements as well as a fundamental part of the mathematical thinking process. Studying the proof can help decide if and why our answers are logical, develop the habit of arguing, and make investigating an integral part of any problem solving. However, not a few students have difficulty learning it. So it is necessary to explore the student's thought process in proving a statement through questions, answer sheets, and interviews. The ability to prove is explored through 4 (four) proof schemes, namely Scheme of Complete Proof, Scheme of Incomplete Proof, Scheme of unrelated proof, and Scheme of Proof is immature. The results obtained indicate that the ability to prove is influenced by understanding and the ability to see that new theorems are built on previous definitions, properties and theorems; and how to present proof and how students engage with proof. Suggestions in this research are to change the way proof is presented, and to change the way students are involved in proof; improve understanding through routine proving new mathematical statements; and developing course designs that can turn proving activities into routine activities.

Automatic Damaged Number Plate Recognition System In Image Processing

The use of the NPR (Number Plate Recognition) is a structure expected to assist confirm the number tags of cars. This structure is anticipated to have the real goal of the security system. This structure is based on an image planning system. This scheme helps to distinguish between the number plates of the cars, to prepare them and to use the information taken care of for further methodology such as securing, empowering the car to pass or to expel the car. NPR is an image scheduling development that utilizes the number (license) plate to acknowledge the car. The goal is to structure a gainful altered attested vehicle unmistakable proof scheme by the use of car number plateThe system is carried out along the route of security control of a particularly restricted area, such as military areas or area around the finest public working settings, such as the Parliament, the Supreme Court, etc. First, the produced system receives a image of the car. The region of the vehicle number plate is evacuated using the picture division in the picture. The optical character affirmation method is used to confirm the character. The resulting information is then used to distinguish and record the information in the database. The structure is performed and impersonated in Python, and the execution is tried on a licensed image. It is seen from the outset that the produced structure acknowledges and sees the car amount vividly.

Privacy Preserving Distributed K-Means Clustering in Malicious Model Using Verifiable Secret Sharing Scheme

In this article, the authors propose an approach for privacy preserving distributed clustering that assumes malicious model. In the literature, there do exist, numerous approaches that assume a semi honest model. However, such an assumption is, at best, reasonable in experimentations; rarely true in real world. Hence, it is essential to investigate approaches for privacy preservation using a malicious model. The authors use the Pederson's Verifiable Secret Sharing scheme ensuring the privacy using additively homomorphic secret sharing scheme. The trustworthiness of the data is assured using homomorphic commitments in Pederson's scheme. In addition, the authors propose two variants of the proposed approach - one for horizontally partitioned dataset and the other for vertically partitioned dataset. The experimental results show that the proposed approach is scalable in terms of dataset size. The authors also carry out experimentations to highlight the effectiveness of Verifiable Secret Sharing scheme against Zero Knowledge Proof scheme.

Fast Antinoise RFID-Aided Medical Care System

We propose a grouping proof scheme to help the nursing staff on their final check automatically before a medicine round. During the medicine round, even though their RFID reader is offline, our method can generate multiple proofs for each patient and help the medical caretakers follow the five-right policy to correctly administer the drugs to their patients. Besides, because our scheme enables a nurse to target specific group tags during a medicine round, it is able to generate proofs even when the illegitimate tags are on site. We prove that our generated proof is reliable because it can resist most security threats and guarantee the integrity of the proof. Besides, our proposed scheme guarantees anonymity on the RFID tags, so the patients’ sensitive information and location privacy can be protected. Last, we run a simulation to show that compared with the related methods our proposed scheme requires the least transmission time and the lowest computation loads to generate a proof.

Privacy Preserving Distributed K-Means Clustering in Malicious Model Using Verifiable Secret Sharing Scheme

In this article, the authors propose an approach for privacy preserving distributed clustering that assumes malicious model. In the literature, there do exist, numerous approaches that assume a semi honest model. However, such an assumption is, at best, reasonable in experimentations; rarely true in real world. Hence, it is essential to investigate approaches for privacy preservation using a malicious model. The authors use the Pederson's Verifiable Secret Sharing scheme ensuring the privacy using additively homomorphic secret sharing scheme. The trustworthiness of the data is assured using homomorphic commitments in Pederson's scheme. In addition, the authors propose two variants of the proposed approach - one for horizontally partitioned dataset and the other for vertically partitioned dataset. The experimental results show that the proposed approach is scalable in terms of dataset size. The authors also carry out experimentations to highlight the effectiveness of Verifiable Secret Sharing scheme against Zero Knowledge Proof scheme.