Verification System
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Giulia Macario ◽  
Giuseppe Pupillo ◽  
Gianni Bernardi ◽  
Pietro Bolli ◽  
Paola Di Ninni ◽  

2022 ◽  
Vol 9 (1) ◽  
pp. 99-109
Jindal et al. ◽  

A signature is a handwritten representation that is commonly used to validate and recognize the writer individually. An automated verification system is mandatory to verify the identity. The signature essentially displays a variety of dynamics and the static characteristics differ with time and place. Many scientists have already found different algorithms to boost the signature verification system function extraction point. The paper is aimed at multiplying two different ways to solve the problem in digital, manual, or some other means of verifying signatures. The various characteristics of the signature were found through the most adequately implemented methods of machine learning (support vector and decision tree). In addition, the characteristics were listed after measuring the effects. An experiment was performed in various language databases. More precision was obtained from the feature.

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Shubham Joshi ◽  
Shalini Stalin ◽  
Prashant Kumar Shukla ◽  
Piyush Kumar Shukla ◽  
Ruby Bhatt ◽  

The Internet of Things (IoT) is a new revolution defined by heterogeneous devices made up of intelligent, omnipresent items that are all hooked up to The internet. These devices are frequently implemented in different areas to offer innovative programs in various industrial applications, including intelligent urban, medicine, and societies. Such Internet of Things (IoT) equipment generates a large volume of private and safety information. Because IoT systems are resource-constrained in terms of operation, memory, and communication capability, safeguarding accessibility to them is a difficult task. In the blockchain concept, the majority, or even all network nodes, check the validity and accuracy of exchanged data before accepting and recording it, whether this data is related to financial transactions, measurements of a sensor, or an authentication message. In evaluating the validity of exchanged data, nodes must reach a consensus in order to perform a special action, in which case the opportunity to enter and record transactions and unreliable interactions with the system is significantly reduced. Recently, in order to share and access management of IoT devices’ information with a distributed attitude, a new authentication protocol based on blockchain has been proposed, and it is claimed that this protocol satisfies user privacy while preserving security. Today’s identification and authentication techniques have substantial shortcomings due to rapidly growing prevalence and implementation. As a result, the protection of such gadgets is critical to guarantee the program’s efficacy and safety. A decentralized authentication and access control method for lightweight IoT systems are proposed in this work and a blockchain-based system that enables identification and secures messaging with IoT nodes. The technique is built on fog information systems and the idea of a blockchain system; when contrasted to something like a blockchain-based verification system, the testing findings show that the suggested mechanism outperforms it. The authentication and verification system undergoes using the blockchain technique. Our method takes advantage of blockchain’s inherent advantages while also associated with development authentication systems. Our suggested blockchain-based approach, structure, and layout, in particular, provide for transparency, consistency, and provenance while also providing tamper-proof records. The article describes the general systems architectural style and the analysis and execution of a real scenario as just a prototype system. The authentication included give as protected prototype that can transmit data with secured protocol and achieves minimum error rate.

2021 ◽  
Vol 22 (4) ◽  
Mohammad Saleem ◽  
Bence Kovari

In this paper, we propose an enhanced jk-nearest neighbor (jk-NN) classifier for online signature verification. After studying the algorithm's main parameters, we use four separate databases to present and evaluate each algorithm parameter. The results show that the proposed method can increase the verification accuracy by 0.73-10% compared to a traditional one class k-NN classifier. The algorithm has achieved reasonable accuracy for different databases, a 3.93% error rate when using the SVC2004 database, 2.6% for MCYT-100 database, 1.75% for the SigComp'11 database, and 6% for the SigComp'15 database.The proposed algorithm uses specifically chosen parameters and a procedure to pick the optimal value for K using only the signer's reference signatures, to build a practical verification system for real-life scenarios where only these signatures are available. By applying the proposed algorithm, the average error achieved was 8% for SVC2004, 3.26% for MCYT-100, 13% for SigComp'15, and 2.22% for SigComp'11.

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