Banca de DEFESA: DAVI CARVALHO MORENO DE ALMEIDA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : DAVI CARVALHO MORENO DE ALMEIDA
DATE: 28/07/2023
TIME: 15:00
LOCAL: Sessão por videoconferência. Google Meet/Sala: https://meet.google.com/jmx-mjzu-fdd
TITLE:

TECHNIQUES FOR GENERATING PSEUDO-RANDOM NUMBERS AND PHYSICAL LAYER AUTHENTICATION USING CHAOTIC SEQUENCES.


KEY WORDS:

Pores. Pseudorandom Number Generators, Physical Layer Authentication, Information Security, Arnold Map, q-Analogs, Chaotic Sequences.


PAGES: 66
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUMMARY:

With the advancement of communication technologies and the increase in transmitted data volume, information security has become a fundamental concern in various sectors. This dissertation addresses the challenges associated with two areas of information security: the development of reliable Pseudorandom Number Generators (PRNGs) and the generation of tags for Physical Layer Authentication (PLA) systems. The dissertation presents three algorithms developed to contribute to these specific fields. The first algorithm presented is a PRNG based on the Arnold Map applied to integer rings of the type Z2m, while the second algorithm is a PRNG based on q-Analogs over finite fields. Both are compared with existing algorithms in the literature, using metrics of statistical analysis and hardware implementation. Additionally, a new tag generation algorithm for PLA systems is proposed, based on discretized chaotic sequences, and a comparison is made with existing methods in the literature using information theory-based metrics. The dissertation also analyzes the information that a malicious user has about the secret key used in the PLA system when intercepting multiple legitimate message and tag pairs, considering the proposed tag generation algorithm.


COMMITTEE MEMBERS:
Presidente - 1851787 - DANIEL PEDRO BEZERRA CHAVES
Externo à Instituição - JOAO VICTOR DE CARVALHO EVANGELISTA
Interno - 1130403 - RICARDO MENEZES CAMPELLO DE SOUZA
Notícia cadastrada em: 06/07/2023 10:30
SIGAA | Superintendência de Tecnologia da Informação (STI-UFPE) - (81) 2126-7777 | Copyright © 2006-2024 - UFRN - sigaa11.ufpe.br.sigaa11