Lyes Khoukhi - IEEE Xplore Author Profile
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Lyes Khoukhi

Also published under: L. Khoukhi

Publications
127
Citations
2,252
Publications by Year
20052025
Co-Authors:
Show All Co-Authors (81)
Image of author Lyes Khoukhi

Lyes Khoukhi

Also published under: L. Khoukhi

Affiliation

Unicaen
Ensicaen
Normandy Univ, CNRS, GREYC, Caen, FRANCE

Publication Topics

Biography

Lyes Khoukhi (Senior Member, IEEE) received the Ph.D. degree in electrical and computer engineering from the University of Sherbrooke, Sherbrooke, QC, Canada, in 2006.,From 2007 to 2008, he was a Postdoctoral Researcher with the Department of Computer Science and Operations Research, University of Montreal, Montreal, QC. He is currently a Full Professor with the École Nationale Supérieure d’ingénieurs de Caen, Normandie University, GREYC CNRS, Caen, France. His current research interests include cybersecurity, attacks detection, and performance evaluation in advanced networks, such as cloud networking, 5G/software-defined networking, Internet of Things/vehicle-to-anything, and cyber-physical systems.(Based on document published on 26 April 2022).
Publications
127
Citations
2,252
Publications by Year
20052025
Co-Authors:
Show All Co-Authors (81)
Author's Published Works

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Advanced Anomaly Detection for Maritime IoT Systems: Integrating Semi-Markov Processes for Robust Cybersecurity

Kamel Abbad;Lyes Khoukhi;Lionnel Mesnil;Alain Alliot;Inna Alliot

2025 Global Information Infrastructure and Networking Symposium (GIIS)
Year: 2025 | Conference Paper |
The rapid advancement of digital technologies in maritime operations has led to an urgent demand for specialized cybersecurity strategies, particularly to counter Distributed Denial of Service (DDoS) attacks targeting critical communication protocols like NMEA 2000. This paper presents a distinctive approach utilizing stochastic semi-Markov processes specifically designed to enhance the cybersecur...Show More

Advanced Anomaly Detection for Maritime IoT Systems: Integrating Semi-Markov Processes for Robust Cybersecurity

Kamel Abbad;Lyes Khoukhi;Lionnel Mesnil;Alain Alliot;Inna Alliot

Year: 2025 | Conference Paper |

Adapting to the Evolution: Enhancing Intrusion Detection Through Machine Learning in the QUIC Protocol Era

Adam Kadi;Lyes Khoukhi;Jouni Viinikka;Pierre-Edouard Fabre

IEEE Transactions on Network and Service Management
Year: 2025 | Early Access Article |
The advent of the QUIC protocol may herald a significant shift in the composition of online traffic in the years to come. The transport layer encryption of the QUIC protocol is one of its main evolutions, especially for metadata that was previously transmitted over TCP traffic without encryption. This new protocol has the potential to require significant alterations in future internet traffic anal...Show More

Adapting to the Evolution: Enhancing Intrusion Detection Through Machine Learning in the QUIC Protocol Era

Adam Kadi;Lyes Khoukhi;Jouni Viinikka;Pierre-Edouard Fabre

Year: 2025 | Early Access Article |

An In-Depth Comparative Study of Quantum-Classical Encoding Methods for Network Intrusion Detection

Adam Kadi;Aymene Selamnia;Zakaria Abou El Houda;Hajar Moudoud;Bouziane Brik;Lyes Khoukhi

IEEE Open Journal of the Communications Society
Year: 2025 | Volume: 6 | Journal Article |
In today’s rapidly evolving cyber landscape, the growing sophistication of attacks, including the rise of zero-day exploits, poses critical challenges for network intrusion detection. Traditional Intrusion Detection Systems (IDSs) often struggle with the complexity and high dimensionality of modern cyber threats. Quantum Machine Learning (QML) seamlessly integrates the computational power of quant...Show More

An In-Depth Comparative Study of Quantum-Classical Encoding Methods for Network Intrusion Detection

Adam Kadi;Aymene Selamnia;Zakaria Abou El Houda;Hajar Moudoud;Bouziane Brik;Lyes Khoukhi

Year: 2025 | Volume: 6 | Journal Article |

Blockchain Meets O-RAN: A Decentralized Zero-Trust Framework for Secure and Resilient O-RAN in 6G and Beyond

Zakaria Abou El Houda;Hajar Moudoud;Lyes Khoukhi

IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
Year: 2024 | Conference Paper |
Cited by: Papers (3)
O-RAN (Open Radio Access Network) is an initiative that promotes the development of open and interoperable radio access technologies. The O-RAN Alliance has undertaken specification efforts that align with O-RAN principles, incorporating the near-real-time RAN Intelligent Controller (RIC) to manage extensible applications (xApps) owned by various ORAN operators and vendors. However, this integrati...Show More

Blockchain Meets O-RAN: A Decentralized Zero-Trust Framework for Secure and Resilient O-RAN in 6G and Beyond

Zakaria Abou El Houda;Hajar Moudoud;Lyes Khoukhi

Year: 2024 | Conference Paper |

Machine Learning for QUIC Traffic Flood Detection

Adam Kadi;Lyes Khoukhi;Jouni Viinikka;Pierre-Edouard Fabre

2024 Global Information Infrastructure and Networking Symposium (GIIS)
Year: 2024 | Conference Paper |
In order to ensure dependability of connected devices, machine learning is used in the analysis of network traffic to enable faster detection of abnormal behavior and congestion. The use of machine learning techniques enhances the capacity for handling traffic and helps to maintain service quality. Additionally, the purpose of machine learning on securing networks is to detect anomalies, classify ...Show More

Machine Learning for QUIC Traffic Flood Detection

Adam Kadi;Lyes Khoukhi;Jouni Viinikka;Pierre-Edouard Fabre

Year: 2024 | Conference Paper |

Blockchain-Enabled Federated Learning for Enhanced Collaborative Intrusion Detection in Vehicular Edge Computing

Zakaria Abou El Houda;Hajar Moudoud;Bouziane Brik;Lyes Khoukhi

IEEE Transactions on Intelligent Transportation Systems
Year: 2024 | Volume: 25, Issue: 7 | Journal Article |
Cited by: Papers (10)
Intelligent Transportation Systems (ITSs) are transforming the global monitoring of road safety. These systems, including vehicular networks and transportation infrastructure, are vulnerable to several security issues, which could disrupt services and potentially cause harm to the users. It is crucial to establish robust security measures to protect against evolving attacks and ensure the safe and...Show More

Blockchain-Enabled Federated Learning for Enhanced Collaborative Intrusion Detection in Vehicular Edge Computing

Zakaria Abou El Houda;Hajar Moudoud;Bouziane Brik;Lyes Khoukhi

Year: 2024 | Volume: 25, Issue: 7 | Journal Article |

A Pattern Mining-Based False Data Injection Attack Detector for Industrial Cyber-Physical Systems

Khalil Guibene;Nadhir Messai;Marwane Ayaida;Lyes Khoukhi

IEEE Transactions on Industrial Informatics
Year: 2024 | Volume: 20, Issue: 2 | Journal Article |
Cited by: Papers (5)
The implication of cyber-physical systems into industrial processes has introduced some security breaches due to the lack of security mechanisms. This article aims to come up with a novel methodology to detect false data injection attacks on cyber-physical systems. To reach this goal, we propose an efficient anomaly-based approach for detecting false data injection attacks against industrial cyber...Show More

A Pattern Mining-Based False Data Injection Attack Detector for Industrial Cyber-Physical Systems

Khalil Guibene;Nadhir Messai;Marwane Ayaida;Lyes Khoukhi

Year: 2024 | Volume: 20, Issue: 2 | Journal Article |

Secure and Efficient Federated Learning for Robust Intrusion Detection in IoT Networks

Zakaria Abou El Houda;Hajar Moudoud;Lyes Khoukhi

GLOBECOM 2023 - 2023 IEEE Global Communications Conference
Year: 2023 | Conference Paper |
Cited by: Papers (1)
The rapid expansion of the Internet of Things (IoT) has increased the demand for robust intrusion detection systems. Federated learning (FL) has appeared as a potential solution to improve the security of IoT networks by facilitating collaboration between multiple devices in training a unified model while keeping their data secure. As the training process of FL occurs locally on individual devices...Show More

Secure and Efficient Federated Learning for Robust Intrusion Detection in IoT Networks

Zakaria Abou El Houda;Hajar Moudoud;Lyes Khoukhi

Year: 2023 | Conference Paper |

Application of Deep Learning and Markov Chains Approaches Based Zero Trust Security for Smart Power Grid Systems

Nousseiba Guergouri;Nabil Sahli;Mohamed Benmohammed;Lyes Khoukhi

2023 International Conference on Networking and Advanced Systems (ICNAS)
Year: 2023 | Conference Paper |
With the increasing interconnectivity and digitalization of critical infrastructures, such as smart grids, ensuring robust cybersecurity measures is of paramount importance. Industrial Control Systems (ICS) security plays a crucial role in safeguarding the reliable operation of smart grids. In recent years, Machine learning (ML) and deep learning (DL) has emerged as a powerful tool for detecting a...Show More

Application of Deep Learning and Markov Chains Approaches Based Zero Trust Security for Smart Power Grid Systems

Nousseiba Guergouri;Nabil Sahli;Mohamed Benmohammed;Lyes Khoukhi

Year: 2023 | Conference Paper |

Mining classification algorithms to identify flooding attacks through the HTTP/3 protocol

Adam Kadi;Lyes Khoukhi;Jouni Viinikka;Pierre-Edouard Fabre

2023 IEEE International Conference on Communications Workshops (ICC Workshops)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
The recent advancements in networking technologies have brought a substantial transformation in the manner in which we interact and communicate with one another. The highly anticipated 6G networks are poised to bring about a revolutionary change to the world with their advanced features and capabilities. However, with the rising complexity of networks and the explosive growth of IoT, the threat of...Show More

Mining classification algorithms to identify flooding attacks through the HTTP/3 protocol

Adam Kadi;Lyes Khoukhi;Jouni Viinikka;Pierre-Edouard Fabre

Year: 2023 | Conference Paper |

Securing Federated Learning through Blockchain and Explainable AI for Robust Intrusion Detection in IoT Networks

Zakaria Abou El Houda;Hajar Moudoud;Bouziane Brik;Lyes Khoukhi

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
Year: 2023 | Conference Paper |
Cited by: Papers (12)
Federated learning (FL) is a distributed machine learning technique that allows multiple devices or nodes in a network to collaboratively train a machine learning model while keeping their data local to the device. This is particularly useful in the context of the Internet of Things (IoT) systems, where devices may have limited computational resources and may not be able to transmit their data to ...Show More

Securing Federated Learning through Blockchain and Explainable AI for Robust Intrusion Detection in IoT Networks

Zakaria Abou El Houda;Hajar Moudoud;Bouziane Brik;Lyes Khoukhi

Year: 2023 | Conference Paper |

Towards a Secure and Scalable Access Control System Using Blockchain

Zakaria Abou El Houda;Jérémy Beaugeard;Quentin Sauvêtre;Lyes Khoukhi

2023 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Access control, both physical and virtual, has always been a crucial aspect in maintaining the security of corporate information systems. Recently, several solutions have been proposed to address physical and virtual access control, including the use of electronic badges that can be costly to produce and easily misplaced. Additionally, numerous, sometimes expensive, cloud-based solutions have also...Show More

Towards a Secure and Scalable Access Control System Using Blockchain

Zakaria Abou El Houda;Jérémy Beaugeard;Quentin Sauvêtre;Lyes Khoukhi

Year: 2023 | Conference Paper |

Trust Management in Vehicular Ad-Hoc Networks: Extensive Survey

Houda Amari;Zakaria Abou El Houda;Lyes Khoukhi;Lamia Hadrich Belguith

IEEE Access
Year: 2023 | Volume: 11 | Journal Article |
Cited by: Papers (11)
Over the past few decades, Intelligent Transportation System (ITS) has become a vital and extensive element of daily human life and activity. Vehicular Ad hoc Networks (VANETs) have become the most promising components of ITS, which promises to enhance transport efficiency, passenger safety, and comfort by exchanging traffic and infotainment information to intelligent vehicles. Moreover, VANETs ha...Show More

Trust Management in Vehicular Ad-Hoc Networks: Extensive Survey

Houda Amari;Zakaria Abou El Houda;Lyes Khoukhi;Lamia Hadrich Belguith

Year: 2023 | Volume: 11 | Journal Article |

A MEC-Based Architecture to Secure IoT Applications using Federated Deep Learning

Zakaria Abou El Houda;Bouziane Brik;Adlen Ksentini;Lyes Khoukhi

IEEE Internet of Things Magazine
Year: 2023 | Volume: 6, Issue: 1 | Magazine Article |
Cited by: Papers (24)
Internet of Things (IoT) is a promising paradigm that is considered as major enabler of smart cities. However, with the emergence of IoT botnets, the number of unsecured IoT devices is increasing rapidly. This can give attackers more advanced tools to carry out large scale damaging IoT attacks. Advanced Machine Learning (ML) techniques can help enhance the effectiveness of conventional intrusion d...Show More

A MEC-Based Architecture to Secure IoT Applications using Federated Deep Learning

Zakaria Abou El Houda;Bouziane Brik;Adlen Ksentini;Lyes Khoukhi

Year: 2023 | Volume: 6, Issue: 1 | Magazine Article |

MiTFed: A Privacy Preserving Collaborative Network Attack Mitigation Framework Based on Federated Learning Using SDN and Blockchain

Zakaria Abou El Houda;Abdelhakim Senhaji Hafid;Lyes Khoukhi

IEEE Transactions on Network Science and Engineering
Year: 2023 | Volume: 10, Issue: 4 | Journal Article |
Cited by: Papers (47)
Distributed denial-of-service (DDoS) attacks continue to grow at a rapid rate plaguing Internet Service Providers (ISPs) and individuals in a stealthy way. Thus, intrusion detection systems (IDSs) must evolve to cope with these increasingly sophisticated and challenging security threats. Traditional IDSs are prone to zero-day attacks since they are usually signature-based detection systems. The re...Show More

MiTFed: A Privacy Preserving Collaborative Network Attack Mitigation Framework Based on Federated Learning Using SDN and Blockchain

Zakaria Abou El Houda;Abdelhakim Senhaji Hafid;Lyes Khoukhi

Year: 2023 | Volume: 10, Issue: 4 | Journal Article |

When Collaborative Federated Learning Meets Blockchain to Preserve Privacy in Healthcare

Zakaria Abou El Houda;Abdelhakim Senhaji Hafid;Lyes Khoukhi;Bouziane Brik

IEEE Transactions on Network Science and Engineering
Year: 2023 | Volume: 10, Issue: 5 | Journal Article |
Cited by: Papers (21)
Data-driven Machine and Deep Learning (ML/DL) is an emerging approach that uses medical data to build robust and accurate ML/DL models that can improve clinical decisions in some critical tasks ($e.g.,$ cancer diagnosis). However, ML/DL-based healthcare models still suffer from poor adoption due to the lack of realistic and recent medical data. The privacy nature of these medical datasets makes it...Show More

When Collaborative Federated Learning Meets Blockchain to Preserve Privacy in Healthcare

Zakaria Abou El Houda;Abdelhakim Senhaji Hafid;Lyes Khoukhi;Bouziane Brik

Year: 2023 | Volume: 10, Issue: 5 | Journal Article |

HybCon: A Scalable SDN-Based Distributed Cloud Architecture for 5G Networks

Djabir Abdeldjalil Chekired;Mohammed Amine Togou;Lyes Khoukhi

IEEE Transactions on Cloud Computing
Year: 2023 | Volume: 11, Issue: 1 | Journal Article |
Cited by: Papers (7)
In a time where data traffic is booming, Software-defined Networking (SDN) is becoming the most plausible solution to cope with the conventional networks’ shortcomings. The separation of the control (software) and the data (hardware) planes makes of SDN a technology-enabled to a multitude of new and promising applications and use cases for 5G network technology. Yet, initial SDN deployments consid...Show More

HybCon: A Scalable SDN-Based Distributed Cloud Architecture for 5G Networks

Djabir Abdeldjalil Chekired;Mohammed Amine Togou;Lyes Khoukhi

Year: 2023 | Volume: 11, Issue: 1 | Journal Article |

False Data Injection Attack Against Cyber-Physical Systems Protected by a Watermark

Khalil Guibene;Nadhir Messai;Marwane Ayaida;Lyes Khoukhi;Atika Rivenq;Yassin El Hillali

GLOBECOM 2022 - 2022 IEEE Global Communications Conference
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Several works are aiming to develop techniques allowing detecting False Data Injection Attacks, which represents one of the most harmful attacks due to its ability to damage a Cyber Physical Systems (CPS). Among these techniques the watermarking represents one of the most used ones. This paper proposes the design of a False Data Injection Attack (FDIA) against a CPS protected by a watermark-based ...Show More

False Data Injection Attack Against Cyber-Physical Systems Protected by a Watermark

Khalil Guibene;Nadhir Messai;Marwane Ayaida;Lyes Khoukhi;Atika Rivenq;Yassin El Hillali

Year: 2022 | Conference Paper |

Data leakage prevention model for vehicular networks

Maryam Najafi;Marc Lemercier;Lyes Khoukhi

2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
Year: 2022 | Conference Paper |
The vehicle adhoc network (VANET) is a promising technology that enables numerous vehicular network applications to improve road safety, navigation, and many other purposes. Android automotive supports many applications for vehicles. Each application has a list of accesses, called permissions, required for specific interfaces or sensitive data. However, some applications request permissions unrela...Show More

Data leakage prevention model for vehicular networks

Maryam Najafi;Marc Lemercier;Lyes Khoukhi

Year: 2022 | Conference Paper |

Prediction and detection model for hierarchical Software-Defined Vehicular Network

Houda Amari;Lyes Khoukhi;Lamia Hadrich Belguith

2022 IEEE 47th Conference on Local Computer Networks (LCN)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
Vehicle Ad-hoc Network (VANET) is the main component of the intelligent transportation system. With the development of the next-generation intelligent vehicular networks, the latter aims to provide strategic and secure services and communications in roads and smart cities. Due to VANET’s unique characteristics, such as high mobility of its nodes, self-organization, distributed network, and frequen...Show More

Prediction and detection model for hierarchical Software-Defined Vehicular Network

Houda Amari;Lyes Khoukhi;Lamia Hadrich Belguith

Year: 2022 | Conference Paper |

A Low-Latency Fog-based Framework to secure IoT Applications using Collaborative Federated Learning

Zakaria Abou El Houda;Lyes Khoukhi;Bouziane Brik

2022 IEEE 47th Conference on Local Computer Networks (LCN)
Year: 2022 | Conference Paper |
Cited by: Papers (14)
Attacks against the IoT network are increasing rapidly, leading to an exponential growth in the number of unsecured IoT devices. Existing security mechanisms are facing several issues due to the lack of real-time decisions, high energy consumption, and high time delays. In this context, we propose a novel Low-Latency Fog-based Framework, called FogFed, to secure IoT applications using Fog computin...Show More

A Low-Latency Fog-based Framework to secure IoT Applications using Collaborative Federated Learning

Zakaria Abou El Houda;Lyes Khoukhi;Bouziane Brik

Year: 2022 | Conference Paper |

Ensemble Learning for Intrusion Detection in SDN-Based Zero Touch Smart Grid Systems

Zakaria Abou El Houda;Bouziane Brik;Lyes Khoukhi

2022 IEEE 47th Conference on Local Computer Networks (LCN)
Year: 2022 | Conference Paper |
Cited by: Papers (17)
Software-defined network (SDN) is widely deployed on Smart Grid (SG) systems. It consists in decoupling control and data planes, to automate the monitoring and management of the communication network, and thus enabling zero touch management of SG systems. However, SDN-based SG is prone to several security threats and varios type of new attacks. To alleviate these issues, various Machine/Deep learn...Show More

Ensemble Learning for Intrusion Detection in SDN-Based Zero Touch Smart Grid Systems

Zakaria Abou El Houda;Bouziane Brik;Lyes Khoukhi

Year: 2022 | Conference Paper |

A Hierarchical Fog Computing Framework for Network Attack Detection in SDN

Zakaria Abou El Houda;Lyes Khoukhi

ICC 2022 - IEEE International Conference on Communications
Year: 2022 | Conference Paper |
Cited by: Papers (4)
In recent years, there has been a huge demand to secure Internet of Things (IoT) applications against the new emerging threats and attacks; these attacks are becoming increasingly sophisticated and have caused tremendous damage to academic and business organizations. Intrusion detection systems (IDS) have an essential role in ensuring network security. As new types of security threats emerge, conv...Show More

A Hierarchical Fog Computing Framework for Network Attack Detection in SDN

Zakaria Abou El Houda;Lyes Khoukhi

Year: 2022 | Conference Paper |

“Why Should I Trust Your IDS?”: An Explainable Deep Learning Framework for Intrusion Detection Systems in Internet of Things Networks

Zakaria Abou El Houda;Bouziane Brik;Lyes Khoukhi

IEEE Open Journal of the Communications Society
Year: 2022 | Volume: 3 | Journal Article |
Cited by: Papers (92)
Internet of Things (IoT) is an emerging paradigm that is turning and revolutionizing worldwide cities into smart cities. However, this emergence is accompanied with several cybersecurity concerns due mainly to the data sharing and constant connectivity of IoT networks. To address this problem, multiple Intrusion Detection Systems (IDSs) have been designed as security mechanisms, which showed their...Show More

“Why Should I Trust Your IDS?”: An Explainable Deep Learning Framework for Intrusion Detection Systems in Internet of Things Networks

Zakaria Abou El Houda;Bouziane Brik;Lyes Khoukhi

Year: 2022 | Volume: 3 | Journal Article |

Cyber-Attack on P2P Energy Transaction Between Connected Electric Vehicles: A False Data Injection Detection Based Machine Learning Model

Dhaou Said;Mayssa Elloumi;Lyes Khoukhi

IEEE Access
Year: 2022 | Volume: 10 | Journal Article |
Cited by: Papers (32)
When cybersecurity is neglected, any network system loses its efficiency, reliability, and resilience. With the huge integration of the Information, Communication and Technology capabilities, the Connected Electric Vehicle (CEV) as a transportation form in cities is becoming more and more efficient and able to reply to citizen and environmental expectations which improve the quality of citizens’ l...Show More

Cyber-Attack on P2P Energy Transaction Between Connected Electric Vehicles: A False Data Injection Detection Based Machine Learning Model

Dhaou Said;Mayssa Elloumi;Lyes Khoukhi

Year: 2022 | Volume: 10 | Journal Article |

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