Roman Alex F. Lustro

Work place: Information and Communication Technology Department, Isabela State University, Philippines

E-mail: romanalex.f.lustro@isu.edu.ph

Website:

Research Interests: Data Mining, Artificial Intelligence

Biography

Roman Alex F. Lustro earned his Doctor in Information Technology at the Technological Institute of the Philippines. He finished his Master in Information Technology at the University of La Salette. Likewise, obtained his Bachelor of Science in Information Technology at Isabela State University.

At present, Dr. Lustro is an assistant professor II at Isabela State University teaching capstone projects, system analysis and design, software engineering, and database management system. In addition, he is also holding an office as the program chair of the Bachelor of Science in Information Technology, responsible for administrative and academic-related matters.

He is also a researcher who has published researches in Scopus-indexed journals and a presenter in international conferences. His topics include cryptography, artificial intelligence, design pattern, and data mining.

Author Articles
Modified Key Derivation Function for Enhanced Security of Speck in Resource-Constrained Internet of Things

By Roman Alex F. Lustro

DOI: https://doi.org/10.5815/ijcnis.2021.04.02, Pub. Date: 8 Aug. 2021

Randomness is an imperative component in every cryptographic algorithm to guarantee secret keys are unpredictable and secured against all forms of attacks. Speck generated sequence is non-random, a clear sign that it falls beyond the acceptable success rate when tested in statistical analysis. Thus, this study resolves the non-randomness by integrating a novel key derivation function that uses elementary operators designed for lightweight application. This design aims not to compromise performance when implemented on software and hardware. As a result, the modified Speck successfully passed the NIST SP 800 - 22 and Dieharder v3.31.0 Statistical Test Analysis as no p-value is flagged as failed during testing. Hence, making modified Speck cryptographically secured. Nevertheless, a 1.06% decrease in the figure of merit of the modified Speck still makes it worthier in a resource-constrained Internet of Things application as contrasted to Speck because it is proven to be beyond cryptographically secured.

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