{"title":"Lightweight encryption for short-range wireless biometric authentication systems in Industry 4.0","authors":"Borja Bordel, R. Alcarria, T. Robles","doi":"10.3233/ica-210673","DOIUrl":null,"url":null,"abstract":"Most recent solutions for users’ authentication in Industry 4.0 scenarios are based on unique biological characteristics that are captured from users and recognized using artificial intelligence and machine learning technologies. These biometric applications tend to be computationally heavy, so to monitor users in an unobtrusive manner, sensing and processing modules are physically separated and connected through point-to-point wireless communication technologies. However, in this approach, sensors are very resource constrained, and common cryptographic techniques to protect private users’ information while traveling in the radio channel cannot be implemented because their computational cost. Thus, new security solutions for those biometric authentication systems in their short-range wireless communications are needed. Therefore, in this paper, we propose a new cryptographic approach addressing this scenario. The proposed solution employs lightweight operations to create a secure symmetric encryption solution. This cipher includes a pseudo-random number generator based, also, on simple computationally low-cost operations in order to create the secret key. In order to preserve and provide good security properties, the key generation and the encryption processes are fed with a chaotic number sequence obtained through the numerical integration of a new four-order hyperchaotic dynamic. An experimental analysis and a performance evaluation are provided in the experimental section, showing the good behavior of the described solution.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"65 1","pages":"153-173"},"PeriodicalIF":5.8000,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integrated Computer-Aided Engineering","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.3233/ica-210673","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 5
Abstract
Most recent solutions for users’ authentication in Industry 4.0 scenarios are based on unique biological characteristics that are captured from users and recognized using artificial intelligence and machine learning technologies. These biometric applications tend to be computationally heavy, so to monitor users in an unobtrusive manner, sensing and processing modules are physically separated and connected through point-to-point wireless communication technologies. However, in this approach, sensors are very resource constrained, and common cryptographic techniques to protect private users’ information while traveling in the radio channel cannot be implemented because their computational cost. Thus, new security solutions for those biometric authentication systems in their short-range wireless communications are needed. Therefore, in this paper, we propose a new cryptographic approach addressing this scenario. The proposed solution employs lightweight operations to create a secure symmetric encryption solution. This cipher includes a pseudo-random number generator based, also, on simple computationally low-cost operations in order to create the secret key. In order to preserve and provide good security properties, the key generation and the encryption processes are fed with a chaotic number sequence obtained through the numerical integration of a new four-order hyperchaotic dynamic. An experimental analysis and a performance evaluation are provided in the experimental section, showing the good behavior of the described solution.
期刊介绍:
Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal.
The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems. The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering. It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality. Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.