Authentication Process Research Articles

Decoding the Volatile Profile of White Romanian Fetească Wines

The wine’s volatilome, most of the time, defines not only its aroma, but also, its major attributes. In the case of wines, the authentication process has become imperative, in light of increased production of alcoholic beverages; consequently, reliable analytical methods have served for it. Therefore, the goal of this research was to establish the global volatile profile of traditional Romanian white wines from Fetească varieties (Fetească albă, Fetească regală) in order to identify its unique characteristics by means of a headspace solid-phase microextraction coupled with gas chromatography analysis (HS-SPME/GC-MS) and e-Nose devoted techniques. Statistics was also employed aimed at differentiating the analyzed wine by varietal groups. Consequently, 23 volatile compounds were detected and quantified in 39 Fetească white wine samples originating from various production areas (Muntenia, Oltenia, Transylvania, Banat and Dobrogea), then further classified according to their odor thresholds in five aromatic classes (floral, fruity, sweet, lactic (cheesy) and other). In addition, statistics (Principal Component Analysis (PCA), Hieratical Clustering Analysis (HCA)) were used aiming to differentiate the analyzed varietal groups. The outcomes have pointed out the existence of distinct clusters connected with ethyl esters or alcohol composition and production year, depending on each examined variety.

Development of Face Recognition System Using Support Vector Machine Algorithm

This research paper describes a face recognition system constructed with the Support Vector Machine (SVM) method. The technique implements the Convolutional Neural Network (CNN) approach for extracting features, which improves the accuracy of recognising faces. The method confirms an efficient and accurate facial recognition procedure by utilising SVM's ability to detect complex patterns within retrieved characteristics. The article explores how the system is implemented and optimised performance, with a focus on obtaining performance in real time. The experimental findings demonstrate the practical application of the SVM-based facial recognition system, emphasising its numerous potential applications in security, the authentication process, as well as interaction between humans and computers. The implementation of CNN for extracting features provides refinement to the system, proving its flexibility to complex face characteristics and confirming its feasibility in actual applications. The results indicate that the suggested system is an effective facial recognition technique. Furthermore, the system is computationally efficient, taking just a few seconds to evaluate an individual face for extracting features and recognition. The system for identifying faces uses modern approaches to enhance both speed and precision, making it a potential option for a variety of applications. Its capacity to swiftly and correctly detect faces in real-time circumstances is a substantial development in facial identification technologies. The system's capability has been comprehensively evaluated, and it satisfies the essential criteria for practical implementation in real-world situations, making it an important addition to the continued development of secure and efficient face recognition systems.

Tools for studying of facial identification and authentication

One of the most common and popular among biometric techniques is biometry of face. Currently, a large number of information systems have been created using these techniques. Thus, there is a problem of studying the methods of machine face recognition during the training of relevant specialists. The aim of the work is to develop a software tools for studying the mechanism of biometric face authentication. Face is static biometry methodic. For implementation in the developed tools the method of comparison on key points was chosen. The main stages of comparing faces are: finding a face in a photo, formation of key points, normalization, formation of segments, formation of relations, comparison of ratios. A high-level cross-platform programming language C++ with the use of additional libraries was chosen to develop the software of the tools. An open face database was used to work with the tools. The tools have a demonstration nature. During its use, you can explore and study all the components of the process of biometric identifi-cation and authentication of the user by face: demonstration of the process of finding of key points on the face, forming of distances between points, calculating of their ratios and their comparison; comparison of etalon and candidate photos during the procedure of identification and authentication and response. Examples of the main processing stages of the complex and the corresponding screen forms (windows) are given. The com-position of the tools and software are developed in the work, the main examples and stages of its work are given. It is shown that the tools can be used in the educational process, for example in laboratory or practical classes.

A Recognition-Based Graphical Password System for Enhanced User Authentication

Abstract: Password-based authentication is a popular way for ensuring computer application security and privacy. Nonetheless, the "weakest link" in the authentication process is believed to be user-chosen weak passwords and hazardous input techniques. People generally utilize mnemonic or brief passphrases instead of random alphanumeric characters. Because internet and mobile applications are widely available, users can access them from any location, at any time, using any device. While this simplicity is generally appreciated, it also increases the likelihood that credentials will be compromised through Visual Hacking. The assault tactics can include employing external recording equipment or watching the victim personally in order to obtain their login information. In response to this issue, our team created a graphical password-based authentication mechanism to combat the threat of Visual Hacking. The system's security mechanism is three-tiered, featuring password verification as well as colour and pattern matching features. This means that even with numerous camera-based hacking attempts, potential attackers would have a tough time determining or limiting the password. In addition, we created and tested a system prototype to determine its usability. According to our trial results, our system can survive Visual Hacking better than previous authentication systems while maintaining a high level of security and usability.

A COMPARATIVE PHARMACOGNOSTIC EVALUATION OF THE LEAVES OF TULSI (OCIMUM BASALICUM) AND (OCIMUM SANCTUM)

The pharmacognostic evaluation of Ocimum basilicum (Sweet Basil) and Ocimum sanctum (Holy Basil) involved detailed macroscopic and microscopic analyses of their leaves. Ocimum basilicum leaves typically measure 4-8 cm in length, displaying an elliptic ovate shape, whereas Ocimum sanctum leaves are relatively smaller, measuring about 2-2.5 cm in length and exhibiting an ovate shape. Microscopic examination further distinguished between the two species: O. sanctum displayed a square-shaped epidermis characterized by parenchymatous cells and sclerenchyma patches, whereas O. basilicum showcased a dorsiventral mesophyll structure with stomata and glandular trichomes. These distinctive features contribute significantly to the standardization, authentication, and quality control processes essential for ensuring the efficacy and safety of herbal medicine formulations containing Ocimum basilicum and Ocimum sanctum.

Enhance the Security of ATM Machine Access with Face and Fingerprint Recognition

Abstract: The project introduces an innovative approach to enhance the security and accessibility of Automated Teller Machines (ATMs). In this era where financial transactions are increasingly digital and essential, safeguarding ATM access is of paramount importance. This project leverages the power of biometric authentication, combining fingerprint and face recognition technologies to create a robust and reliable access control system. The proposed system allows ATM users to authenticate their identity with a seamless and secure process. Fingerprint recognition provides a high-precision, individualized identification method, while face recognition adds an additional layer of security, ensuring the users identity matches the stored biometric data. This dual-biometric approach significantly reduces the risk of unauthorized access and fraudulent activities at ATMs. Beyond enhancing security, the project contributes to user convenience by streamlining the authentication process, eliminating the need for traditional ATM cards or PINs. Users can access their accounts swiftly and securely, thereby improving the overall ATM experience. Furthermore, the project’s incorporation of state-of-the-art biometric technologies underscores its potential to set a standard for secure ATM access not only in the financial sector but also in various other domains where access control is critical.

The Bureaucratic Route of the Real Estate Sale Contracts

This article comes to answer one of the most common questions we have from clients in the notarial practice: "What documents are required?". Although there are no two contracts alike, just as there are no two people alike, we can say that there is a general framework that is adapted to each situation. We will present what are the stages and the bureaucratic process that the seller and buyer go through in a real estate contract, but also what documents are required and what each of them is used for. The article is structured according to three moments in the authentication process: the procedures prior to authentication, those concurrent with authentication, and those after authentication. Of course, it is up to the notary the instruments the procedure if he considers that, in addition to those presented, other documents are needed to clarify the situation of a building. We will see that, although this bureaucratic route may seem cumbersome and sometimes even boring, it is important for the safety of the non-contentious civil circuit.

Innovative supply chain network design with two-step authentication and environmentally-friendly blockchain technology

AbstractBlockchain Technology (BT) has the potential to revolutionize supply chain management by providing transparency, but it also poses significant environmental and security challenges. BT consumes energy and emits carbon gases, affecting its adoption in Supply Chains (SCs). The substantial energy demand of blockchain networks contributes to carbon emissions and sustainability risks. Moreover, for secure and reliable transactions, mutual authentication needs to be established to address security concerns raised by SC managers. This paper proposes a tri-objective optimization model for the simultaneous design of the SC-BT network, considering a two-step authentication process. The model considers transparency caused by BT members, emissions of BT, and costs related to BT and SC design. It also takes into account uncertainty conditions for participating BT members in the SC and the range of transparency, cost, and emission targets. To solve the model, a Branch and Efficiency (B&E) algorithm equipped with BT-related criteria is developed. The algorithm is implemented in a three-level SC and produces cost-effective and environmentally friendly outcomes. However, the adoption of BT in the SC can be costly and harmful to the environment under uncertain conditions. It is worth mentioning that implementing the proposed algorithm from our article in a three-level SC case study can result in a significant cost reduction of over 16% and an emission reduction of over 13%. The iterative nature of this algorithm plays a vital role in achieving these positive outcomes.

A secure authentication and collaborative data-sharing model based on a blockchain network in the cloud

ABSTRACT In cloud computing, various organisations store their confidential information in private or public cloud platforms. The data sharing through the various cloud platforms increases the risk of security. To attain data sharing while sustaining data confidentiality, a secure sharing platform and collaboration model is needed. Hence, this paper introduces the novel secure authentication and collaborative data sharing (SecAuth_CDS) scheme for sharing data on blockchain. The entities involved in the SecAuth_CDS are third parties, data owners, smart contracts and blockchain networks. The security of the authentication process can be boosted by applying various security operations, such as Exclusive OR (EXOR), hashing, encryption and so on. The proposed method assures that the sharing is secure and trustworthy by blockchain. The experimental result reveals that the SecAuth_CDS performed effectively in terms of revenue, memory usage and computation cost with the values of 27, 62.20 MB and 0.003 sec.

Four-Dimensional Physical Unclonable Functions and Cryptographic Applications Based on Time-Varying Chaotic Phosphorescent Patterns.

Physical unclonable functions (PUFs) have attracted interest in demonstrating authentication and cryptographic processes for Internet of Things (IoT) devices. We demonstrated four-dimensional PUFs (4D PUFs) to realize time-varying chaotic phosphorescent randomness on MoS2 atomic seeds. By forming hybrid states involving more than one emitter with distinct lifetimes in 4D PUFs, irregular lifetime distribution throughout patterns functions as a time-varying disorder that is impossible to replicate. Moreover, we established a bit extraction process incorporating multiple 64 bit-stream challenges and experimentally obtained physical features of 4D PUFs, producing countless random 896 bit-stream responses. Furthermore, the weak and strong PUF models were conceptualized and demonstrated based on 4D PUFs, exhibiting superior cryptological performances, including randomness, uniqueness, degree of freedom, and independent bit ratio. Finally, the data encryption and decryption in pictures were performed by a single 4D PUF. Therefore, 4D PUFs could enhance the counterfeiting deterrent of existing optical PUFs and be used as an anticounterfeiting security strategy for advanced authentication and cryptographic processes of IoT devices.

Advancing Electoral Processes: A Novel E-Voting Model Integrating Iris Scans, Raspberry Pi, and Blockchain Technology

The amalgamation of an e-voting system with blockchain technology represents a significant advancement in the electoral process, streamlining voting procedures. However, concerns persist regarding the security and auditability of the system. While blockchain provides robust security and transparency to safeguard the integrity of votes, it faces potential resistance from tech-agnostic users. In response to these challenges, a novel e-voting model is proposed, leveraging iris scans through Raspberry Pi technology, offering a promising avenue for enhanced security and user acceptance. Moreover, this biometric approach introduces a seamless and user-friendly authentication process, potentially mitigating the resistance faced by tech-agnostic voters in adopting advanced e-voting technologies. The integration of iris scans through Raspberry Pi into the e-voting system, coupled with blockchain technology, presents a comprehensive and forward-thinking solution to the challenges posed by security, auditability, and user acceptance. This multifaceted approach not only addresses existing concerns but also sets the stage for a more inclusive and secure electoral process in the digital age.

Comprehensive Security for IoT Devices with Kubernetes and Raspberry Pi Cluster

Environmental monitoring systems have gained prominence across diverse applications, necessitating the integration of cutting-edge technologies. This article comprehensively explores such a system, emphasizing the integration of a Raspberry Pi cluster with the BME680 environmental sensor within a Kubernetes framework. This study encompasses the technical aspects of hardware configuration and places a significant focus on security benchmarks and robustness validation. The environmental monitoring infrastructure discussed in this article delves into the intricacies of the Raspberry Pi cluster’s hardware setup, including considerations for scalability and redundancy. This research addresses critical security gaps in contemporary environmental monitoring systems, particularly vulnerabilities linked to IoT deployments. Amidst increasing threats, this study introduces a robust framework that integrates advanced security tools—HashiCorp (San Francisco, CA, USA) Vault v1.16 for dynamic secret management and OpenID Connect for authentication processes—to enhance applications and system integrity and resilience within the Kubernetes environment. The approach involves a multi-layered security architecture that fortifies the storage and management of credentials and ensures authenticated and authorized interactions within IoT networks. Furthermore, our research incorporates a series of security benchmark tests, including vulnerability scanning, penetration testing, and access control assessments. Additionally, this article addresses crucial aspects related to data management and analysis, detailing the methodologies employed for storing, processing, and deriving insights from the collected environmental data. It further explores the integration of the monitoring system with existing infrastructure and systems, facilitating seamless data sharing and interoperability and offering valuable insights into the system’s ability to withstand potential threats and vulnerabilities. The integration of Raspberry Pi clusters with BME680 environmental sensors within a Kubernetes-managed framework significantly enhances the scalability and security of IoT systems. This study quantifies the improvements, demonstrating at least a 30% enhancement in system responsiveness and a minimum 40% reduction in vulnerability exposures, as verified by extensive security benchmarks, including penetration testing. These advancements facilitate robust, scalable IoT deployments, with potential applications extending beyond environmental monitoring to include industrial and urban settings. The incorporation of dynamic secret management with HashiCorp Vault and secure authentication with OpenID Connect provides a blueprint for developing resilient IoT architectures capable of supporting high-security and high-availability applications. In conclusion, this article contributes to the expanding body of knowledge in IoT and environmental monitoring and establishes a strong foundation for future work. These outcomes suggest promising directions for further research in secure IoT applications and present practical implications for the deployment of secure and scalable IoT solutions in critical infrastructures.

An Analysis and Improvement Scheme for the Weakness of Kerberos V5 Authentication

The security protocol of network system can ensure the reliability of network communication. Kerberos protocol is a kind of security verification mechanism based on shared key, which has been adopted for a long time on the Internet. This text introduces the authentication process of Kerberos v5 protocol. To the defect that the authentication server don’t authenticate the user’s identity but it hold safe in building on the basis whether the user can correctly decrypt the ciphertext message in the protocol, we put forward a scheme that adding in the Challenge/Response mechanism to improve its security in Symmetric Cipher Mechanism. Passing the improved scheme’s analysis we can perceive the method that adding in Challenge/Response identity authentication technology will greatly resist Offline Password Conjecture Attack.

Machine Learning-based Intrusion Detection System Through WPA3 Protocol in Smart Contract System

Nowadays, the Internet has become one of the basic human needs of professionals. With the massive number of devices, reliability, and security will be crucial in the coming ages. Routers are common to provide us with the internet. These routers can be operated in different modes. Some routers use the Wifi Security Protocol (WPA) or WPA2, and the Wifi Alliance introduced WPA3 on 25 June 2018. There are a lot of papers regarding Smart Contract (SC)–based IDS as well as Machine Learning-based IDS. Very few discuss combining SC and ML-based IDS for different authentication processes. In this paper, we will discuss how combining SC and ML plays a vital role in authentication. Also, we play the role of embedded IDS system so that existing vulnerabilities of the WPA2 and WPA3 can be reduced to 99.62%.

“Look, it’s my first Wikipedia article!” The attitude of university students to an authentic process genre writing task

“Look, it’s my first Wikipedia article!” The attitude of university students to an authentic process genre writing task

ORICERT – FRAUDULENT DEGREE AND MARKSHEET DETECTION

Identifying fake degrees and marksheets is becoming more and more important intoday's educational environment, since thespread of fake credentials jeopardizes employer confidence, academic integrity, and social standards. An overview of the most recent developments in marksheet and fraudulent degree detection techniques—including both established techniques and cutting-edge technologies—is provided Conventional techniques for identifying forged credentials frequently entail manual verification procedures, such as physical document inspection, institution verification,and cross- referencing with official databases. Although these techniques are still fundamental, they are prone to human error and frequently ineffective whenmanaging high numbers of credentials. Recent years have seen a boom intechnology advancements meant to improve the scalability and accuracy of fraudulent credential detection in response to these difficulties. For example, machine learning algorithms have demonstrated potential in automating the authentication process through the analysis of anomalies and patterns found in digital documents. Using natural language processing (NLP) techniques, textual data from academic transcripts and diplomas may be extracted and analysed to help find discrepancies or anomalies. Additionally, blockchain technology has become a disruptive force in credential verification by providing decentralized, immutable ledgers for academic accomplishments. Employers and educational institutions may reduce the danger of credential fraud by establishing safe, unchangeable archives of student Records by utilizing blockchain-based credentialing systems. Notwithstanding these developments, there are still issues with fraudulent credential detection, such as the necessity for international collaboration in the fight against cross-border credential fraud and the adaptation of fraudsters to changing detection techniques. Furthermore, the ethical implications related to algorithmic bias and data privacy emphasize how crucial it is to implement and supervise detection systems responsibly. KEYWORD: Degree Marksheet Verification Record.

An Optimized Effective Authentication Process for E-Health Application

Because of the availability of more than an actor and a wireless component in an e-health application, providing more security and safety to users of this type of applications is expected. Moreover, ensuring protection of data user available or shared within different services from any security attack becomes an important requirement. In this paper, we are interested essentially in the authentication process, and we propose an improved Landmarkbased algorithm as a tool to extract, firstly, key features from analysed faces, and hence to accelerate the authentication operation. The suggested approach beats other state-of-the-art works in terms of accuracy and speed-up attaining time execution constraint, according to experimental evaluations.

SecQRMark:Fake Product Detection using Blockchain

In response to the global challenge of counterfeit products, this paper presents an advanced anti-counterfeit system leveraging blockchain technology. The system utilizes Ethereum, Solidity, and Ganache to establish an immutable and transparent ledger, enabling real-time tracking of products from manufacturer to consumer. Manufacturers register their products on the blockchain, generating unique QR codes with Copy Sensitive digital images for secure identification. Consumers employ an Android application to scan these QR codes, decrypting the encrypted text to access vital information about product authenticity. This system not only empowers consumers with instantaneous verification but also provides businesses with a robust defense mechanism against counterfeit threats, safeguarding their reputation and revenue. The integration of innovative technologies revolutionizes the authentication process, instilling trust in consumers and bolstering brand integrity. Our solution stands as a pioneering force in the battle against counterfeit production, offering a scalable and efficient method for detecting fake products using blockchain technology. Key Words: Block chain, smart contracts, QR(Quick Response) code, anti- counterfeit.

Candidate Authentication using OCR Techniques

This paper explores the application of Optical Character Recognition (OCR) techniques for authenticating candidates based on identity documents. As advancements in technology continue to redefine various industries, the integration of OCR into candidate authentication processes offers a streamlined and efficient solution. The aim is to design a system which gets the image of the identity proof and the details are being retrieved using the character segmentation which is done by a feature extraction optical character recognition algorithm (OCR). The authentication process encompasses document validation and implementation of security measures to safeguard against fraud.By combining YOLO object detection, Optical Character Recognition (OCR) and fuzzy matching technique ,this approach aims to enhance the accuracy and reliability of candidate authentication. This underscores the importance of a comprehensive authentication framework, incorporating both technological and procedural elements, to establish a robust and secure candidate authentication process in diverse contexts. Keywords: ID Verification,Optical Character Recognition (OCR), Text Extraction, YOLO,Object Detection,Image Segmentation, EasyOCR , Fuzzy Matching.

Modeling the fracture process of wheat straw using a discrete element approach

The cracking and breaking of wheat straw under the action of external force are rarely studied, they affect the precision of its simulation using the discrete element method. The process of straw change due to cracking and breaking consists of two stages: ring collapsing and breaking. In order to restore the real process of straw change, this study develops a discrete element model based on the Hertz-Mindlin bonding V2 contact model. The bond parameters were calibrated using the test of compression, shear, and three-point bending. An orthogonal experiment was conducted to determine the optimal parameter combination. The obtained results showed that the proposed straw model accurately simulated the cracking, breaking, and flow characteristic. The relative errors of compression strength, shear strength, and deflection were 9.48, 8.74, and 11.51%, respectively. The relative error of the angle of repose (AOR) was only 1.67%, which indicates that the mechanical properties and flow characteristic of the model are consistent with those of real straw. This study holds significant importance in accurately replicating the authentic straw treatment process in the field.