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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Moreover, it satisfies the requirements of the EPCGen2 standards.
📌 3 Key Takeaways
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Objective & Hypothesis:The need for security in lightweight devices such as radio frequency identification tags is increasing and a pseudorandom number generator (PRNG) constitutes an essential part of the authentication protocols that provide security.
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Key Findings & Data:The main aim of this research is to produce a lightweight PRNG for cryptographic applications in wireless identification and sensing platform family devices, and other related lightweight devices.
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Conclusion & Impact:Moreover, it satisfies the requirements of the EPCGen2 standards.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Pseudorandom number generation · genetic programming · wireless identification and sensing platform
Abstract
The need for security in lightweight devices such as radio frequency identification tags is increasing and a pseudorandom number generator (PRNG) constitutes an essential part of the authentication protocols that provide security. The main aim of this research is to produce a lightweight PRNG for cryptographic applications in wireless identification and sensing platform family devices, and other related lightweight devices. This PRNG is produced with genetic programming methods using entropy calculation as the fitness function, and it is tested with the NIST statistical test suite. Moreover, it satisfies the requirements of the EPCGen2 standards.
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Cite This Article
KÖSEMEN, C., DALKILIÇ, G., AYDIN, Ö. (2018). Genetic programming-based pseudorandom number generator for wireless identification and sensing platform. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 26 - Sayı: 5, 2500–2511. https://ajindex.com/articles/187342