While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution (e.g., a good trade-off between cost, accuracy, resilience and computational efficiency) that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing.

https://www.mdpi.com/1424-8220/22/21/8500/pdf?version=1667559882

Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System

Automated integration of real-time and non-real-time defense systems

With emergence of latest technology, life of individuals has greatly been improved. On the other hand, there has been vulnerabilities and loopholes in the technology that exploited the security. As, user and passwords provide safeguard to data, but physical and behavioral process require the authentication, As, passwords and user login cannot provide proper authentication process. Thus, biometrics process provides the authentication to physical and behavioral characteristics. In this paper, we introduce Secure password-driven Fingerprint Biometrics Authentication (SPFBA) method for protecting the confidential and private information stored onto the smartphone in case of lost and stolen. The SPFBA is unibiometric, but leveraging the features and integrating fingerprint biometrics authentication with password-driven method. Furthermore, false acceptance rate accuracy, false rejection rate accuracy and genuine acceptance rate accuracy are determined. To determine the effectiveness of the proposed SPFBA; Java platform and Android studio are used for implementation. Finally, SPFBA is compared with other known biometric authentication methods from accuracy perspective.

Secure Password-Driven Fingerprint Biometrics Authentication

The virtually coupled train sets (VCTS) have been proposed to improve operational capability and passenger satisfaction and ensure punctuality, thus alleviating the rapidly worsening traffic pressure. Recently, due to the lack of reliable wireless communications and accurate perceptual information, VCTS based on industrial internet of things (IIoT) are receiving growing concerns by integrating into the IIoT, AI, and edge computing. However, denial of service (DoS) attacks are feasible for IIoT-based VCTS due to the physically exposed open electromagnetic environment. They would cause severe safety and punctuality problems, such as poor real-time capability, enormous packet dropout rates, extensive train operational delays, and disturbance in the train convoy’s dynamic schedule. This paper deeply discusses the effects of DoS attacks on the performances of the IIoT-based VCTS by combing the physical layer with the cyber layer and explores the requirement of an attacker. We consider that the system is under the attack of a rational DoS attacker with limited jamming attacks, which will cause the most system state offset. In the paper, we propose a novel train status estimation approach to compensate for the losing information of the front train by the trade-off between the best gain of the DoS attacker and the punctuality of the IIoT-based VCTS. System performance includes physical dynamic indicators, train operational delay variance, and average waiting time of passengers. Taken together, these findings indicate that the established status estimation approach can effectively mitigate safety concerns and reduce train operational delays.

/pdf/a-novel-approach-for-estimating-performance-of-iiot-based-kyblb8m5.pdf

A Novel Approach for Estimating Performance of IIoT-Based Virtual Control Train Sets under DoS Attacks

Sailfish invasive weed optimization algorithm for multiple image sharing in cloud computing

Dependence of the individuals on the Internet for performing the several actions require secure data communication. Thus, the reliable data communication improves the confidentiality. As, enhanced security leads to reliable and faster communication. To improve the reliability and confidentiality, there is dire need of fully secured authentication method. There are several methods of password protections were introduced to protect the confidentiality and reliability. Most of the existing methods are based on alphanumeric approaches, but few methods provide the dual authentication process. In this paper, we introduce improved graphical password authentication using Twofish Encryption and Visual Cryptography (TEVC) method. Our proposed TEVC is unpredictably organized as predicting the correct graphical password and arranging its particles in the proper order is harder as compared to traditional alphanumeric password system. TEVC is tested by using JAVA platform. Based on the testing results, we confirm that proposed TEVC provides secure authentication. TEVC encryption algorithm detected as more prudent and possessing lower time complexity as compared to other known existing algorithms message code confirmation and fingerprint scan with password.

Two Factor Authentication using Twofish Encryption and Visual Cryptography Algorithms for Secure Data Communication

Cyber–physical systems (CPSs) have developed rapidly in recent years, contributing to an efficient integration between the cyber and physical worlds in intelligent and connected city environments. However, efficient mobility in a CPS is not well solved. Here, we present a prototype for a privacy-aware secure human-centric mobility-aware (SHM) model proposed and tested to analyze physical and human domains in IoT-based wireless sensor networks (WSNs). The proposed SHM model involves five modules: 1) sensor advertisements; 2) mobile sensor recruitment; 3) load balancing; 4) transmission guarantee; and 5) privacy with data-sharing phases. The proposed model is also validated using an accurate testing method that involves software and hardware tools and mathematical modeling to confirm secure communication. The model provides a tradeoff between energy efficiency and Quality-of-Service (QoS) requirements and compares the performance with other known models/protocols. Our testing process continued for four days, demonstrating that the SHM model provides compelling features of a secure CPS based on actual testing results. In practice, our model can be used in hospitals, as evident from validation in a real-life environment following the protocols.

A Mobility-Aware Human-Centric Cyber–Physical System for Efficient and Secure Smart Healthcare

With the emergence of advanced technology, the user authentication methods have also been improved. Authenticating the user, several secure and efficient approaches have been introduced, but the biometric authentication method is considered much safer as compared to password-driven methods. In this paper, we explore the risks, concerns, and methods by installing well-known open-source software used in Unibiometric analysis by the partners of The National Institute of Standards and Technology (NIST). Not only are the algorithms used all open source but it comes with test data and several internal open source utilities necessary to process biometric data.

Duisen Gulsezim

Papers

Two Factor Authentication using Twofish Encryption and Visual Cryptography Algorithms for Secure Data Communication

A Mobility-Aware Human-Centric Cyber–Physical System for Efficient and Secure Smart Healthcare

Successes and Failures in Exploring Biometric Algorithms in NIST Open Source Software and Data.