Secure Data Transmission Using GS3 in an Armed Surveillance System
Nowadays, the evolution and growth of machine learning (ML) algorithms and the Internet of Things (IoT) are enabling new applications. Smart weapons and people detection systems are examples. Firstly, this work takes advantage of an efficient, scalable, and distributed system, named SmartFog, which...
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MDPI AG
2025-06-01
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| Online Access: | https://www.mdpi.com/2078-2489/16/7/527 |
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| author | Francisco Alcaraz-Velasco José M. Palomares Fernando León-García Joaquín Olivares |
| author_facet | Francisco Alcaraz-Velasco José M. Palomares Fernando León-García Joaquín Olivares |
| author_sort | Francisco Alcaraz-Velasco |
| collection | DOAJ |
| description | Nowadays, the evolution and growth of machine learning (ML) algorithms and the Internet of Things (IoT) are enabling new applications. Smart weapons and people detection systems are examples. Firstly, this work takes advantage of an efficient, scalable, and distributed system, named SmartFog, which identifies people with weapons by leveraging edge, fog, and cloud computing paradigms. Nevertheless, security vulnerabilities during data transmission are not addressed. Thus, this work bridges this gap by proposing a secure data transmission system integrating a lightweight security scheme named GS3. Therefore, the main novelty is the evaluation of the GS3 proposal in a real environment. In the first fog sublayer, GS3 leads to a 14% increase in execution time with respect to no secure data transmission, but AES results in a 34.5% longer execution time. GS3 achieves a 70% reduction in decipher time and a 55% reduction in cipher time compared to the AES algorithm. Furthermore, an energy consumption analysis shows that GS3 consumes 31% less power than AES. The security analysis confirms that GS3 detects tampering, replaying, forwarding, and forgery attacks. Moreover, GS3 has a key space of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>2</mn><mn>544</mn></msup></semantics></math></inline-formula> permutations, slightly larger than those of Chacha20 and Salsa20, with a faster solution than these methods. In addition, GS3 exhibits strength against differential cryptoanalysis. This mechanism is a compelling choice for energy-constrained environments and for securing event data transmissions with a short validity period. Moreover, GS3 maintains full architectural transparency with the underlying armed detection system. |
| format | Article |
| id | doaj-art-506b80b418734d539ed10612ffbc0a48 |
| institution | DOAJ |
| issn | 2078-2489 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-506b80b418734d539ed10612ffbc0a482025-08-20T03:07:55ZengMDPI AGInformation2078-24892025-06-0116752710.3390/info16070527Secure Data Transmission Using GS3 in an Armed Surveillance SystemFrancisco Alcaraz-Velasco0José M. Palomares1Fernando León-García2Joaquín Olivares3Department of Electronic and Computer Engineering, Universidad de Córdoba, 14071 Córdoba, SpainDepartment of Electronic and Computer Engineering, Universidad de Córdoba, 14071 Córdoba, SpainDepartment of Electronic and Computer Engineering, Universidad de Córdoba, 14071 Córdoba, SpainDepartment of Electronic and Computer Engineering, Universidad de Córdoba, 14071 Córdoba, SpainNowadays, the evolution and growth of machine learning (ML) algorithms and the Internet of Things (IoT) are enabling new applications. Smart weapons and people detection systems are examples. Firstly, this work takes advantage of an efficient, scalable, and distributed system, named SmartFog, which identifies people with weapons by leveraging edge, fog, and cloud computing paradigms. Nevertheless, security vulnerabilities during data transmission are not addressed. Thus, this work bridges this gap by proposing a secure data transmission system integrating a lightweight security scheme named GS3. Therefore, the main novelty is the evaluation of the GS3 proposal in a real environment. In the first fog sublayer, GS3 leads to a 14% increase in execution time with respect to no secure data transmission, but AES results in a 34.5% longer execution time. GS3 achieves a 70% reduction in decipher time and a 55% reduction in cipher time compared to the AES algorithm. Furthermore, an energy consumption analysis shows that GS3 consumes 31% less power than AES. The security analysis confirms that GS3 detects tampering, replaying, forwarding, and forgery attacks. Moreover, GS3 has a key space of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>2</mn><mn>544</mn></msup></semantics></math></inline-formula> permutations, slightly larger than those of Chacha20 and Salsa20, with a faster solution than these methods. In addition, GS3 exhibits strength against differential cryptoanalysis. This mechanism is a compelling choice for energy-constrained environments and for securing event data transmissions with a short validity period. Moreover, GS3 maintains full architectural transparency with the underlying armed detection system.https://www.mdpi.com/2078-2489/16/7/527fog computingsecurityInternet of Thingslightweight cipherYOLOarmed people detection |
| spellingShingle | Francisco Alcaraz-Velasco José M. Palomares Fernando León-García Joaquín Olivares Secure Data Transmission Using GS3 in an Armed Surveillance System Information fog computing security Internet of Things lightweight cipher YOLO armed people detection |
| title | Secure Data Transmission Using GS3 in an Armed Surveillance System |
| title_full | Secure Data Transmission Using GS3 in an Armed Surveillance System |
| title_fullStr | Secure Data Transmission Using GS3 in an Armed Surveillance System |
| title_full_unstemmed | Secure Data Transmission Using GS3 in an Armed Surveillance System |
| title_short | Secure Data Transmission Using GS3 in an Armed Surveillance System |
| title_sort | secure data transmission using gs3 in an armed surveillance system |
| topic | fog computing security Internet of Things lightweight cipher YOLO armed people detection |
| url | https://www.mdpi.com/2078-2489/16/7/527 |
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