Application of Recursive Algorithm on Shamir's Scheme Reconstruction for Cheating Detection and Identification

Information data protection is necessary to ward off and overcome various fraud attacks that may be encountered. A secret sharing scheme that implements cryptographic methods intends to maintain the security of confidential data by a group of trusted parties is the answer. In this paper, we choose the application of recursive algorithm on Shamir-based linear scheme as the primary method. In the secret reconstruction stage and since the beginning of the share distribution stage, these algorithms have been integrated by relying on a detection parameter to ensure that the secret value sought is valid. Although the obtained scheme will be much simpler because it utilizes the Vandermonde matrix structure, the security aspect of this scheme is not reduced. Indeed, it is supported by two detection parameters formulated from a recursive algorithm to detect cheating and identify the cheater(s). Therefore, this scheme is guaranteed to be unconditionally secure and has a high time efficiency (polynomial running time).

A Survey On: Cheating Detection in Exams

Cheating in exams has become a serious issue these days. Exams play an important role in every student’s life. Cheating in exams has been a common problem all over the world. Manual cheating detection methods may not be completely successful, to stop cheating during examinations. Automating this process will help in detection with use of machine learning. The proposed method helps to make this process automated. So there is no need to wholly depend on manual method. Keywords: Machine Learning, automated, cheating detection.

Towards Contactless Learning Activities during Pandemics Using Autonomous Service Robots

The COVID-19 pandemic has had a significant impact worldwide, impacting schools, undergraduate, and graduate university education. More than half a million lives have been lost due to COVID-19. Moving towards contactless learning activities has become a research area due to the rapid advancement of technology, particularly in artificial intelligence and robotics. This paper proposes an autonomous service robot for handling multiple teaching assistant duties in the educational field to move towards contactless learning activities during pandemics. We use SLAM to map and navigate the environment to proctor an exam. We also propose a human–robot voice interaction and an academic content personalization algorithm. Our results show that our robot can navigate the environment to proctor students avoiding any static or dynamic obstacles. Our cheating detection system obtained a testing accuracy of 86.85%. Our image-based exam paper scanning system can scan, extract, and process exams with high accuracy.

Blockchain-Based Secure Outsourcing of Polynomial Multiplication and Its Application in Fully Homomorphic Encryption

The efficiency of fully homomorphic encryption has always affected its practicality. With the dawn of Internet of things, the demand for computation and encryption on resource-constrained devices is increasing. Complex cryptographic computing is a major burden for those devices, while outsourcing can provide great convenience for them. In this paper, we firstly propose a generic blockchain-based framework for secure computation outsourcing and then propose an algorithm for secure outsourcing of polynomial multiplication into the blockchain. Our algorithm for polynomial multiplication can reduce the local computation cost to O n . Previous work based on Fast Fourier Transform can only achieve O n log n for the local cost. Finally, we integrate the two secure outsourcing schemes for polynomial multiplication and modular exponentiation into the fully homomorphic encryption using hidden ideal lattice and get an outsourcing scheme of fully homomorphic encryption. Through security analysis, our schemes achieve the goals of privacy protection against passive attackers and cheating detection against active attackers. Experiments also demonstrate our schemes are more efficient in comparisons with the corresponding nonoutsourcing schemes.

Applying cheating identifiable secret sharing scheme in multimedia security

In (k,n) secret sharing scheme, one secret is encrypted into n shares in such a way that only k or more shares can decrypt the secret. Secret sharing scheme can be extended into the field of multimedia that provides an efficient way to protect confidential information on multimedia. Secret image sharing is just the most important extension of secret sharing that can safely guard the secrecy of images among multiple participants. On the other hand, cheating detection is an important issue in traditional secret sharing schemes that have been discussed for many years. However, the issue of cheating detection in secret image sharing has not been discussed sufficiently. In this paper, we consider the cheating problem in the application of secret image sharing schemes and construct a (k,n) secret image sharing scheme with the ability of cheating detection and identification. Our scheme is capable of identifying cheaters when k participants involve in reconstruction. The cheating identification ability and size of shadow in the proposed scheme are improved from the previous cheating identifiable secret image sharing scheme.