16 research outputs found
Renforcement de la sécurité à travers les réseaux programmables
La conception originale d’Internet n’a pas pris en compte les aspects de sécurité du réseau; l’objectif prioritaire était de faciliter le processus de communication. Par conséquent, de nombreux protocoles de l’infrastructure Internet exposent un ensemble de vulnérabilités. Ces dernières peuvent être exploitées par les attaquants afin de mener un ensemble
d’attaques. Les attaques par déni de service distribué (Distributed Denial of Service ou DDoS) représentent une grande menace et l’une des attaques les plus dévastatrices causant des dommages collatéraux aux opérateurs de réseau ainsi qu’aux fournisseurs de services Internet.
Les réseaux programmables, dits Software-Defined Networking (SDN), ont émergé comme
un nouveau paradigme promettant de résoudre les limitations de l’architecture réseau actuelle
en découplant le plan de contrôle du plan de données. D’une part, cette séparation permet
un meilleur contrôle du réseau et apporte de nouvelles capacités pour mitiger les attaques
par déni de service distribué. D’autre part, cette séparation introduit de nouveaux défis en
matière de sécurité du plan de contrôle.
L’enjeu de cette thèse est double. D’une part, étudier et explorer l’apport de SDN
à la sécurité afin de concevoir des solutions efficaces qui vont mitiger plusieurs vecteurs
d’attaques. D’autre part, protéger SDN contre ces attaques. À travers ce travail de
recherche, nous contribuons à la mitigation des attaques par déni de service distribué sur
deux niveaux (intra-domaine et inter-domaine), et nous contribuons au renforcement de
l’aspect sécurité dans les réseaux programmables.The original design of Internet did not take into consideration security aspects of the
network; the priority was to facilitate the process of communication. Therefore, many of the
protocols that are part of the Internet infrastructure expose a set of vulnerabilities that can
be exploited by attackers to carry out a set of attacks. Distributed Denial-of-Service (DDoS)
represents a big threat and one of the most devastating and destructive attacks plaguing
network operators and Internet service providers (ISPs) in a stealthy way.
Software defined networks (SDN), an emerging technology, promise to solve the limitations
of the conventional network architecture by decoupling the control plane from the data
plane. On one hand, the separation of the control plane from the data plane allows for more
control over the network and brings new capabilities to deal with DDoS attacks. On the
other hand, this separation introduces new challenges regarding the security of the control
plane.
This thesis aims to deal with various types of attacks including DDoS attacks while
protecting the resources of the control plane. In this thesis, we contribute to the mitigation
of both intra-domain and inter-domain DDoS attacks, and to the reinforcement of security
aspects in SDN
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses
The ongoing deployment of the fifth generation (5G) wireless networks
constantly reveals limitations concerning its original concept as a key driver
of Internet of Everything (IoE) applications. These 5G challenges are behind
worldwide efforts to enable future networks, such as sixth generation (6G)
networks, to efficiently support sophisticated applications ranging from
autonomous driving capabilities to the Metaverse. Edge learning is a new and
powerful approach to training models across distributed clients while
protecting the privacy of their data. This approach is expected to be embedded
within future network infrastructures, including 6G, to solve challenging
problems such as resource management and behavior prediction. This survey
article provides a holistic review of the most recent research focused on edge
learning vulnerabilities and defenses for 6G-enabled IoT. We summarize the
existing surveys on machine learning for 6G IoT security and machine
learning-associated threats in three different learning modes: centralized,
federated, and distributed. Then, we provide an overview of enabling emerging
technologies for 6G IoT intelligence. Moreover, we provide a holistic survey of
existing research on attacks against machine learning and classify threat
models into eight categories, including backdoor attacks, adversarial examples,
combined attacks, poisoning attacks, Sybil attacks, byzantine attacks,
inference attacks, and dropping attacks. In addition, we provide a
comprehensive and detailed taxonomy and a side-by-side comparison of the
state-of-the-art defense methods against edge learning vulnerabilities.
Finally, as new attacks and defense technologies are realized, new research and
future overall prospects for 6G-enabled IoT are discussed
Security Technologies and Methods for Advanced Cyber Threat Intelligence, Detection and Mitigation
The rapid growth of the Internet interconnectivity and complexity of communication systems has led us to a significant growth of cyberattacks globally often with severe and disastrous consequences. The swift development of more innovative and effective (cyber)security solutions and approaches are vital which can detect, mitigate and prevent from these serious consequences. Cybersecurity is gaining momentum and is scaling up in very many areas. This book builds on the experience of the Cyber-Trust EU project’s methods, use cases, technology development, testing and validation and extends into a broader science, lead IT industry market and applied research with practical cases. It offers new perspectives on advanced (cyber) security innovation (eco) systems covering key different perspectives. The book provides insights on new security technologies and methods for advanced cyber threat intelligence, detection and mitigation. We cover topics such as cyber-security and AI, cyber-threat intelligence, digital forensics, moving target defense, intrusion detection systems, post-quantum security, privacy and data protection, security visualization, smart contracts security, software security, blockchain, security architectures, system and data integrity, trust management systems, distributed systems security, dynamic risk management, privacy and ethics
Security Technologies and Methods for Advanced Cyber Threat Intelligence, Detection and Mitigation
The rapid growth of the Internet interconnectivity and complexity of communication systems has led us to a significant growth of cyberattacks globally often with severe and disastrous consequences. The swift development of more innovative and effective (cyber)security solutions and approaches are vital which can detect, mitigate and prevent from these serious consequences. Cybersecurity is gaining momentum and is scaling up in very many areas. This book builds on the experience of the Cyber-Trust EU project’s methods, use cases, technology development, testing and validation and extends into a broader science, lead IT industry market and applied research with practical cases. It offers new perspectives on advanced (cyber) security innovation (eco) systems covering key different perspectives. The book provides insights on new security technologies and methods for advanced cyber threat intelligence, detection and mitigation. We cover topics such as cyber-security and AI, cyber-threat intelligence, digital forensics, moving target defense, intrusion detection systems, post-quantum security, privacy and data protection, security visualization, smart contracts security, software security, blockchain, security architectures, system and data integrity, trust management systems, distributed systems security, dynamic risk management, privacy and ethics
Cyber Security
This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security
Cyber Security
This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security
Data Hiding and Its Applications
Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others
Proceedings of the Doctoral Consortium in Computer Science (JIPII 2021)
Actas de las Jornadas de InvestigaciĂłn Predoctoral en IngenierĂa InformáticaThis volume contains the proceedings of the Primeras Jornadas de InvestigaciĂłn Predoctoral en IngenierĂa Informática - First Doctoral Consortium in Computer Science, JIPII 2021, which was held online on June 15th, 2021. The aim of JIPII 2021 was to provide a forum for PhD students to present and discuss their research under the guidance of a panel of senior researchers. The advances in their PhD theses under development in the Doctoral Program in Computer Science were presented in the Consortium. This Doctoral Program belongs to the Doctoral School of the University of Cadiz (EDUCA).
Different stages of research were covered, from the most incipient phase, such as the PhD Thesis plans (or even a Master’s Thesis), to the most advanced phases in which the defence of the PhD Thesis is imminent.
We enjoyed twenty very nice and interesting talks, organized in four sessions. We had a total of fifty participants, including speakers and attendees, with an average of thirty-two people in the morning sessions and an average of twenty people in the afternoon sessions.
Several people contributed to the success of JIPII 2021. We are grateful to the Academic Committee of the Doctoral Program in Computer Science and the School of Engineering for their support. We would like also to thank the Program Committee for their work in reviewing the papers, as well as all the students and supervisors for their interest and participation.
Finally, the proceedings have been published by the Department of Computer Science and Engineering. We hope that you find the proceedings useful, interesting, and challenging