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http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/2525| Low Latency Transparent Memory Encryption Engine Based On Lightweight Cryptography For Iot Devices | |
| JESUS ISAAC SORIANO | |
| RENE ARMANDO CUMPLIDO PARRA | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| Memory Encryption Engine Ligthweight Cryptography FPGA SoC IoT | |
| This thesis presents the development of a low-latency, transparent memory encryption engine utilizing lightweight cryptography for IoT devices. The research addresses the increasing vulnerability of IoT devices to physical memory attacks, such as cold boot and snooping attacks, which threaten the security of sensitive information. Focusing on the lightweight ASCON algorithm, the project entails a thorough analysis of lightweight cryptography algorithms, hardware implementation considerations, and a review of existing memory encryption frameworks. The design and implementation are carried out using Hardware Description Languages on a Zibo z7 SoC, with subsequent behavioral simulation in Vivado 2022.2. The thesis evaluates the system’s performance and IoT-specific applications, employing tools like Petalinux and Tinymembench for Full Memory Encryption (FME) testing. The analysis of data collected across all phases demonstrates the efficiency of the proposed solution in enhancing IoT device security against physical memory attacks, while maintaining low latency and transparency, marking a significant contribution to the field of lightweight cryptography in IoT security. | |
| Instituto Nacional de Astrofísica, Óptica y Electrónica | |
| 2024-01 | |
| Tesis de maestría | |
| Inglés | |
| Estudiantes Investigadores Público en general | |
| Soriano Pineda, J. I., (2024), Low Latency Transparent Memory Encryption Engine Based On Lightweight Cryptography For Iot Devices, Tesis de Maestría, Instituto Nacional de Astrofísica, Óptica y Electrónica | |
| OTRAS ESPECIALIDADES TECNOLÓGICAS | |
| Versión aceptada | |
| acceptedVersion - Versión aceptada | |
| Aparece en las colecciones: | Maestría en Ciencias Computacionales |
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| Fichero | Tamaño | Formato | |
|---|---|---|---|
| SORIANOPJI_MCC.pdf | 2.41 MB | Adobe PDF | Visualizar/Abrir |