Erol Gelenbe

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Verified

Erol verified their affiliation via an institutional email.

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• PhD (Polytechnic Institute NYU 1970); Docteur ès Sciences (Sorbonne University 1973); BSEE (Middle East Technical UniversityAnkara
• Professor at Polish Academy of Sciences

The Internet of Things (IoT) is transforming industries by enhancing productivity and efficiency; however, energy availability remains a significant challenge due to the limited capacity of batteries and supercapacitors powering IoT devices. The emergence of Green IoT (G-IoT) frameworks, which prioritize energy efficiency and renewable energy integ...

Despite signicant advancements in green IoT design frameworks aimed at minimizing energy consumption, extending node lifetimes, reducing carbon footprints , and enhancing sustainability, energy losses due to imperfections in energy storage systems (ESS)such as batteries, capacitors, and supercapaci-torsremain a critical challenge. These ineciencies...

The safe and swift evacuation of passengers from Maritime Vessels, requires an effective Internet of Things(IoT) as well as an information and communication technology(ICT) infrastructure. However, during emergencies, delays in IoT and ICT systems that guide evacuees, can impair the evacuation process. This paper presents explores the impact of the...

Gateway Servers for the Internet of Vehicles (IoV) must meet stringent Security and Quality of Service (QoS) requirements, including cyberattack protection, low delays and minimal packet loss, to offer secure real-time data exchange for human and vehicle safety and efficient road traffic management. Therefore, it is vital to protect these systems f...

In pervasive systems, mobile devices and other sensors access Gateways, which are Servers that communicate with the devices, provide low latency services, connect them with each other, and connect them to the Internet and backbone networks. Gateway Servers are often equipped with Attack Detection (AD) software that analyzes the incoming traffic to...

Edge computing systems must offer low latency at low cost and low power consumption for sensors and other applications, including the IoT, smart vehicles, smart homes, and 6G. Thus, substantial research has been conducted to identify optimum task allocation schemes in this context using non-linear optimization, machine learning, and market-based al...

Gateway Servers for the Internet of Vehicles (IoV) must meet stringent Security and Quality of Service (QoS) requirements, including cyberattack protection, low delays and minimal packet loss, to offer secure real-time data exchange for human and vehicle safety and efficient road traffic management. Therefore, it is vital to protect these systems f...

Smartphones are widely used as portable data collectors for wearable and healthcare sensors that can passively collect data streams related to the environment, health status, and behaviors. Recent research shows that the collected data can be used to monitor not only the physical states but also the mental health of individuals. However, extracting...

The process of quantifying trust considers the factors that affect it, which can be applied to identify malicious behavior, reduce uncertainty, and facilitate decision-making. Traditional trust evaluation methods based on statistics and reasoning, rely heavily on domain knowledge, which limits their practical applications. Graph Neural Networks (GN...

In the present paper, we investigate the impact of imperfections (non-idealities) of the energy storage system (e.g., batteries, capacitors, or supercapacitors) on the energy performance of green IoT nodes. In particular, we investigate the impact of energy leakage from the Energy Storage System (ESS) on important energy performance metrics, such a...

The widespread adoption of the Internet of Things (IoT) partly depends on the successful design and deployment of IoT nodes that can operate for several years without any service outage and the need to replace their energy storage systems (ESSs) (e.g., battery, capacitor, or supercapacitor) when all the stored energy is depleted or when the cycle l...

Vulnerability prediction is an important mechanism for secure software development, as it enables the early identification and mitigation of software vulnerabilities. Vulnerability prediction models (VPMs) are machine learning (ML) models able to detect potentially vulnerable software components based on information retrieved from their source code...

This article summarizes some of the research contributions of several EU Projects including NEMESYS, GHOST, KONFIDO, SDK4ED, SerIoT and IoTAC, primarily with a cybersecurity and Machine Learning orientation. The subjects covered include the cybersecurity of Mobile Networks and of the Internet of Things (IoT), the design of IoT Gateways and their pe...

This comprehensive review navigates the multifaceted realm of large language models, placing a significant focus on its exemplar model, ChatGPT, developed by OpenAI. As an advanced model seamlessly integrate into diverse digital interactions, the critical question of its trustworthiness and associated challenges becomes increasingly prominent. Our...

Starting with the contributions presented in this EuroCyberSecurity Workshop 2021 which was organized as part of the series of International Symposia on Computer and Information Sciences (ISCIS), with the support of the European Commission funded IoTAC Project, that was held on November 2021 in NI ice, France, this paper summarizes some of the rese...

The safe and swift evacuation of passengers from Maritime Vessels, requires an effective Internet of Things (IoT) as well as an information and communication technology (ICT) infrastructure. However, during emergencies, delays in IoT and ICT systems that guide evacuees, can impair the evacuation process. This paper presents explores the impact of t...

We analyze, further and deeper, a recently proposed technique for addressing the Massive Access Problem (MAP), an issue in telecommunications which arises when too many devices transmit packets to a gateway in quick succession. This technique, the Adaptive-Quasi-Deterministic Transmission Policy (AQDTP) is a special case of "traffic shaping" which...

The most energy-hungry parts of mobile networks are the base station sites, which consume around 60-80% of their total energy. One of the approaches for relieving this energy pressure on the electricity grid infrastructure and reducing the Operational Expenditures (OPEX) is to power base stations with renewable energy. However, the design of a gree...

Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (especially water, which is becoming a scarce resource) and environmental pollution (in the case of leakage of toxic fluids like oil and gas). Emerging technologies like the Internet of...

Developing embedded software applications is a challenging task, chiefly due to the limitations that are imposed by the hardware devices or platforms on which they operate, as well as due to the heterogeneous non-functional requirements that they need to exhibit. Modern embedded systems need to be energy efficient and dependable, whereas their main...

Cruise ships and other naval vessels include automated Internet of Things (IoT)-based evacuation systems for the passengers and crew to assist them in case of emergencies and accidents. The technical challenges of assisting passengers and crew to safety during emergencies include various aspects such as sensor failures, imperfections in the sound o...

This paper proposes a novel Self-Supervised Intrusion Detection (SSID) framework, which enables a fully online Deep Learning (DL) based Intrusion Detection System (IDS) that requires no human intervention or prior off-line learning. The proposed framework analyzes and labels incoming traffic packets based only on the decisions of the IDS itself usi...

In the software rich environment of 6G, systems will be surrounded by edge devices that support distributed software systems which are critical to operations. Such systems may also be subject to frequent updates or uploads of individual software components. Trust in such systems will therefore depend on our ability to rapidly ensure that such softw...

ChatGPT, as an advanced model that seamlessly integrates into diverse digital interactions, shows great potential to enhance the performance of consumer technology and reshape its landscape. The critical question of its trustworthiness and associated challenges becomes increasingly prominent. However, the literature still lacks a thorough review to...

The document list publications on performance modelling from 1969 to 1980 in mainstream journals and conferences.

The growing concerns about the resource sustainability and environmental impact of deploying billions or trillions of IoT devices in the various sectors of society or economy have given rise to an energy research field known as Green-IoT (G-IoT). G-IoT emphasises the need to prioritise energy efficiency and the reduction of pollution in the IoT eco...

It provides a complete chronological list of journal papers and books published between 1970-2023.

The application of classical Random Neural Networks (RNN) has been restricted to deterministic digital systems that generate probability distributions instead of the stochastic characteristics of random spiking signals. To optimize the utilization of the stochastic properties inherent in RNN, we propose a new category of supervised Random Quantum N...

This paper considers key issues surrounding energy consumption by information and communication technologies (ICT), which has been steadily growing and is now attaining approximately 10% of the worldwide electricity consumption with a significant impact on greenhouse gas emissions. The perimeter of ICT systems is discussed, and the role of the subs...

There is a growing awareness of the need to reduce carbon emissions from the operation of mobile networks. The massive deployment of ultra-dense 5G and IoT networks will significantly increase energy demand and put the electricity grid under stress while also driving up operational costs. In this paper, we model the energy performance of an off-gri...

This paper presents several novel algorithms for real-time cyberattack detection using the Auto-Associative Deep Random Neural Network. Some of these algorithms require offline learning, while others allow the algorithm to learn during its normal operation while it is also testing the flow of incoming traffic to detect possible attacks. Most of the...

The Internet of Things (IoT) is transforming almost every industry, including agriculture, food processing, health care, oil and gas, environmental protection, transportation and logistics, manufacturing, home automation, and safety. Cost-effective, small-sized batteries are often used to power IoT devices being deployed with limited energy capacit...

Major challenges of assisting passengers to safely and quickly escape from ships when an emergency occurs, include complex realistic features such as human behavior uncertainty, dynamic human traversal times, and the computation and communication delays in the systems that offer advice to users during an emergency. In this paper, we present simulat...

This paper proposes a novel Self-Supervised Intrusion Detection (SSID) framework, which enables a fully online Machine Learning (ML) based Intrusion Detection System (IDS) that requires no human intervention or prior off-line learning. The proposed framework analyzes and labels incoming traffic packets based only on the decisions of the IDS itself...

Cyberattacks are increasingly threatening networked systems, often with the emergence of new types of unknown (zero-day) attacks and the rise of vulnerable devices. While Machine Learning (ML)-based Intrusion Detection Systems (IDSs) have been shown to be extremely promising in detecting these attacks, the need to learn large amounts of labelled da...

IoT Servers that receive and process packets from IoT devices should meet the QoS needs of incoming packets, and support Attack Detection software that analyzes the incoming traffic to identify and discard packets that may be part of a Cyberattack. Since UDP Flood Attacks can overwhelm IoT Servers by creating congestion that paralyzes their operati...

The IoT's vulnerability to network attacks has motivated the design of intrusion detection schemes (IDS) using Machine Learning (ML), with a low computational cost for online detection but intensive offline learning. Such IDS can have high attack detection accuracy and are easily installed on servers that communicate with IoT devices. However, they...

This paper presents several novel algorithms for real-time cyberattack detection using the Auto-Associative Deep Random Neural Network, which were developed in the HORIZON 2020 IoTAC Project. Some of these algorithms require offline learning, while others require the algorithm to learn during its normal operation while it is also testing the flow o...

The document is a group of articles from the French newspapers and magazines Le Monde, Le Figaro, Le Novel Observateur, which describe the educational and training program known as the VFI: Volontaires pour la Formation a l'Informatique (Volunteers for education in Informatics) designed and implemented by Prof Erol Gelenbe in the period 1984-93, to...

Description of a new Graduate level Computer Engineering at the University of Paris V in 1988.

This paper proposes a method to assess the security of an n device, or IP address, IoT network by simultaneously identifying all the compromised IoT devices and IP addresses. It uses a specific Random Neural Network (RNN) architecture composed of two mutually interconnected sub-networks that complement each other in a recurrent structure, called...

A novel online Compromised Device Identification System (CDIS) is presented to identify IoT devices and/or IP addresses that are compromised by a Botnet attack, within a set of sources and destinations that transmit packets. The method uses specific metrics that are selected for this purpose and which are easily extracted from network traffic, and...

The complexity of battery-powered autonomous devices such as Internet of Things (IoT) nodes or Unmanned Aerial Vehicles (UAV) and the necessity to ensure an acceptable quality of service, reliability, and security, have significantly increased their energy demand. In this paper, we discuss using a diffusion approximation process to approximate the...

IoT networks handle incoming packets from large numbers of IoT Devices (IoTDs) to IoT Gateways. This can lead to the IoT Massive Access Problem that causes buffer overflow, large end-to-end delays and missed deadlines. This paper analyzes a novel traffic shaping method named the Quasi-Deterministic Traffic Policy (QDTP) that mitigates this problem...

Recent advances in Command and Control (C2) modelling have developed algorithmic representations of the command decision making process at both the tactical (Rapid Planning) and operational (Deliberate Planning) levels of command. In this paper, the development of methods by which indicators of enemy/group behaviour can be extracted is discussed. T...

The traffic from the large number of IoT devices connected to the IoT is a source of congestion known as the Massive Access Problem (MAP), that results in packet losses, delays and missed deadlines for real-time data. This paper reviews the literature on MAP and summarizes recent results on two approaches that have been designed to mitigate MAP. On...

With the development of communication technologies and the increasing bandwidth of optical fibres and transmission speeds in current 5G and future 6G wireless networks, there is a growing demand for solutions organising traffic in such networks, taking into account both end-to-end transmissions and the possibility of data processing by edge service...

Unmanned Aerial Vehicles (UAVs) are rapidly gaining popularity in a wide variety of applications, e.g., agriculture, health care, environmental management, supply chains, law enforcement, surveillance, and photography. Dones are often powered by batteries, making energy a critical resource that must be optimised during the mission of the drone. The...

The traffic from the large number of IoT devices connected to the IoT is a source of congestion known as the Massive Access Problem (MAP), that results in packet losses, delays and missed deadlines for real-time data. This paper reviews the literature on MAP and summarizes recent results on two approaches that have been designed to mitigate MAP. On...

Critical everyday activities handled by modern IoT Systems imply that security is of major concern both for the end-users and the industry. Securing the IoT System Architecture is commonly used to strengthen its resilience to malicious attacks. However, the security of software running on the IoT must be considered as well, since the exploitation o...

Developing modern secure and low-energy applications in a short time imposes new challenges and creates the need of designing new software tools to assist developers in all phases of application development. The design of such tools cannot be considered a trivial task, as they should be able to provide optimization of multiple quality requirements....

Classical Random Neural Networks (RNNs) have demonstrated effective applications in decision making, signal processing, and image recognition tasks. However, their implementation has been limited to deterministic digital systems that output probability distributions in lieu of stochastic behaviors of random spiking signals. We introduce the novel c...

IoT gateways aim to meet the deadlines and QoS needs of packets from as many IoT devices as possible, though this can lead to a form of congestion known as the Massive Access Problem (MAP). While much work was conducted on predictive or reactive scheduling schemes to match the arrival process of packets to the service capabilities of IoT gateways,...

In recent years, IoT devices have often been the target of Mirai Botnet attacks. This paper develops an intrusion detection method based on Auto-Associated Dense Random Neural Network with incremental online learning, targeting the detection of Mirai Botnet attacks. The proposed method is trained only on benign IoT traffic while the IoT network is...

The rapid progress in urban construction and informatization, especially the recent ubiquity of portable devices and intelligent infrastructures, has rapidly aggravated the concentration of pedestrians in built environments. These smart environments, which have been driven close to their limitation in daily operations, can be vulnerable during emer...

As we recall the major contributions of Professor Dennis Gabor that resulted in his Nobel Prize in Physics in 1971 for the invention of holography, it is interesting to put his impact on science, technology, as well as humanity, in a broader context so as to better understand his experiences, and recognize the very significant role that he played i...

Over 500 million host computers, three billion PCs and mobile devices consume over a billion kilowatts of electricity. As part of this "system" computer networks consume an increasing amount of energy, and help reduce energy expenditure from other sources through E-Work, E-Commerce and E-Learning. Traditionally, network design seeks to minimise net...

The book covers the international advances in Modelling, Analysis and Simulation of Computer Systems and Networks and of their Applications

In recent years, IoT devices have often been the target of Mi-rai Botnet attacks. This paper develops an intrusion detection method based on Auto-Associated Dense Random Neural Network with incremental online learning, targeting the detection of Mirai Botnet attacks. The proposed method is trained only on benign IoT traffic while the IoT network is...

Digital applications in healthcare, typically referred as Health Information Technologies (HIT) are transforming healthcare delivery. This increased use of electronic applications and distributed services in the context of healthcare, almost inevitably includes the use of sensitive data and therefore increases the information security risks. A seri...

A significant challenge of IoT networks is to offer Quality of Service (QoS) and meet deadline requirements when packets from a massive number of IoT devices are forwarded to an IoT gateway. Many IoT devices tend to report their data to their wired or wireless network gateways at closely correlated instants of time, leading to congestion known as t...

A significant challenge of IoT networks is to offer Quality of Service (QoS) and meet deadline requirements when packets from a massive number of IoT devices are forwarded to an IoT gateway. Many IoT devices tend to report their data to their wired or wireless network gateways at closely correlated instants of time, leading to congestion known as t...

Internet connected IoT devices have often been particularly vulnerable to Botnet attacks of the Mirai family in recent years. Thus we develop an attack detection scheme for Mirai Botnets, using the Auto-Associative Dense Random Neural Network that has recently been successful for other attacks such as the SYN attack. The resulting method is trained...

We present an approach that uses Reinforcement Learning (RL) with the Random Neural Network (RNN) acting as an adaptive critic, to route traffic in a SDN network, so as to minimize a composite Goal function that includes both packet delay and energy consumption per packet. We directly measure the traffic dependent energy consumption characeristics...

Background The increase of healthcare digitalization comes along with potential information security risks. Thus, the EU H2020 KONFIDO project aimed to provide a toolkit supporting secure cross-border health data exchange. Methods KONFIDO focused on the so-called “User Goals”, while also identifying barriers and facilitators regarding eHealth acce...

A challenge of IoT networks is to offer Quality of Service (QoS) and meet deadline requirements when packets from numerous IoT devices must be forwarded. Thus this paper introduces the Randomization of flow Generation Times (RGT) that smooths incoming IoT traffic so that QoS improves and packet loss is avoided. When the “Earliest Deadline First” (E...

Despite the acknowledged importance of quantitative security assessment in secure software development, current literature still lacks an efficient model for measuring internal software security risk. To this end, in this paper, we introduce a hierarchical security assessment model (SAM), able to assess the internal security level of software produ...

The crucial importance of science and technology and its accurate peer reviewed dissemination, has once again been demonstrated during the current pandemic. Thus the COVID-19 pandemic together with the inevitable energy transition required by climate change, lead us to consider the issue of scientific and technical communication, both for the writt...

The short latency required by IoT devices that need to access specific services have led to the development of Fog architectures that can serve as a useful intermediary between IoT systems and the Cloud. However, the massive numbers of IoT devices that are being deployed raise concerns about the power consumption of such systems as the number of Io...

Les pays de l'UE peuvent se targuer de posséder quelques-unes des plus prestigieuses universités et organismes de recherche dans le monde. Pourtant la part des innovations technologiques que produit le continent reste faible au regard du potentiel de recherches que l'UE représente. Comment redresser la barre et mieux armer les universités européenn...

It has been recently observed that Software Defined Networks (SDN) can change the paths of different connections in the network at a relatively frequent pace to improve the overall network performance, including delay and packet loss, or to respond to other needs such as security. These changes mean that a network that SDN controls will seldom oper...

Common software vulnerabilities can result in severe security breaches, financial losses, and reputation deterioration and require research effort to improve software security. The acceleration of the software production cycle, limited testing resources, and the lack of security expertise among programmers require the identification of efficient so...

Software-Defined Networks (SDN) dynamically modify the paths of Internet flows in response to the quality of service or security needs, and hence frequently modify traffic levels at network routers. Thus network routers often operate in the transient regime, rather than at steady-state, with significant impact on packet loss probabilities and delay...

Cyber-attack detection has become a basic component of all information processing systems, and once an attack is detected it may be possible to block or mitigate its effects. This paper addresses the use of a learning recurrent Random Neural Network (RNN) to build a lightweight detector for certain types of Botnet attacks on IoT systems. Its low co...

Software vulnerability prediction is an important and active area of research where new methods are needed to build accurate and efficient tools that can identify security issues. Thus we propose an approach based on mixed features that combines text mining features and the features generated using a Static Code Analyzer. We use a Random Neural Net...

Long-running software may operate on hardware platforms with limited energy resources such as batteries or photovoltaic, or on high-performance platforms that consume a large amount of energy. Since such systems may be subject to hardware failures, checkpointing is often used to assure the reliability of the application. Since checkpointing introdu...