Noura Limam

• PhD
• University of Waterloo

The fifth generation of cellular technology (5G) delivers faster speeds, lower latency, and improved network service alongside support for a large number of users and a diverse range of verticals. This brings increased complexity to network control and management, making closed-loop automation essential. In response, the 3rd Generation Partnership...

The IEEE Communications Magazine Series on Network Soft-warization and Management represents a timely source of in-depth, cutting-edge articles on state-of-the-art technologies and solutions related to two fields that are highly relevant for today's Communication Networks and their evolution. On the one hand, Network Softwarization advocates for ar...

The IEEE Communications Magazine Series on Network Softwarization and Management represents a timely source of in-depth, cutting-edge articles on state-of-the-art technologies and solutions related to two fields that are highly relevant for today's Communication Networks and their evolution. On the one hand, Network Softwarization advocates for arc...

The IEEE Communications Magazine Series on Network Softwarization and Management represents a timely source of in-depth, cutting-edge articles on state-of-the-art technologies and solutions related to two fields that are highly relevant for today's Communication Networks and their evolution. On one hand, Network Softwarization advocates for archite...

Data-driven algorithms play a pivotal role in the automated orchestration and management of network slices in 5G and beyond networks, however, their efficacy hinges on the timely and accurate monitoring of the network and its components. To support 5G slicing, monitoring must be comprehensive and encompass network slices end-to-end (E2E). Yet, seve...

This document represents the proceedings of the 19th International Conference on Network and Service Management that was held on-line on October 30 - November, 02, 2023, under the theme "Network and Service Management in the Era of Generative AI and Digital Twins". CNSM 2023 was dedicated to a number of topics in the area of Network Operations and...

The IEEE Communications Magazine Series on Network Softwarization and Management represents a timely source of in-depth, cutting-edge articles on state-of-the-art technologies and solutions related to two fields that are highly relevant for today's Communication Networks and their evolution. On one hand, Network Softwarization advocates for archite...

Deep learning (DL) has been successfully applied to encrypted network traffic classification in experimental settings. However, in production use, it has been shown that a DL classifier's performance inevitably decays over time. Re-training the model on newer datasets has been shown to only partially improve its performance. Manually re-tuning the...

The IEEE Communications Magazine Series on Network Softwarization and Management represents a timely source of in-depth, cutting-edge articles on state-of-the-art technologies and solutions related to two fields that are highly relevant for today's communication networks and their evolution. On one hand, network softwarization advocates for archite...

Deep learning (DL) has been successfully applied to encrypted network traffic classification in experimental settings. However, in production use, it has been shown that a DL classifier’s performance inevitably decays over time. Re-training the model on newer datasets has been shown to only partially improve its performance. Manually re-tuning the...

The IEEE Communications Magazine Series on Network Softwarization and Management represents a timely source of in-depth, cutting-edge articles on state-of-the-art technologies and solutions related to two fields that are highly relevant for today's communication networks and their evolution. On one hand, network softwarization advocates for archite...

Traffic classification is essential in network management for a wide range of operations. Recently, it has become increasingly challenging with the widespread adoption of encryption in the Internet, for example, as a de facto in HTTP/2 and QUIC protocols. In the current state of encrypted traffic classification using deep learning (DL), we identify...

This document represents the Proceedings of the 8th IEEE Conference on Network Softwarization (NetSoft 2022), that took place on 27 June - 1 July 2022 in Milan, Italy. The conference was organized around the theme "Network Softwarization Coming of Age: New Challenges and Opportunities". This theme recognizes the fact that Network Softwarization has...

The IEEE Communications Magazine Series on Network Softwarization and Management represents a timely source of in-depth, cutting-edge articles on state-of-the-art technologies and solutions related to two fields that are highly relevant for today's communication networks and their evolution. On one hand, network softwarization advocates for archite...

This document represents the Proceedings of the 18th IEEE/IFIP Network Operations and Management Symposium (NOMS 2022), that took place on April 25-29, 2022 in Budapest, Hungary. As a lot of new and challenging research and developments have been ongoing worldwide, the theme of the conference was "Network and Service Management in the Era of Cloudi...

Traffic classification is essential in network management for operations ranging from capacity planning, performance monitoring, volumetry, and resource provisioning, to anomaly detection and security. Recently, it has become increasingly challenging with the widespread adoption of encryption in the Internet, e.g., as a de-facto in HTTP/2 and QUIC...

Deep learning models have shown to achieve high performance in encrypted traffic classification. However, when it comes to production use, multiple factors challenge the performance of these models. The emergence of new network traffic protocols, especially at the application-layer, as well as updates to previous protocols affect the patterns in in...

The broad scope of the IEEE Communications Magazine Series on Network Softwarization and Management covers two aspects of communication networks that have become highly relevant nowadays. On one hand, network softwarization advocates for architectures where software and programmability aspects in the implementation of network functions, protocols,...

Software-defined networking creates new opportunities for automated network security management by providing a global network view and a standard interface for configuring network policies. Previously, we proposed a general framework, called ATMoS, for autonomous threat mitigation using reinforcement learning (RL) in software-defined networks. Usin...

Virtualization is instigating a paradigm shift in the networking industry, to keep up with emerging application's quality of service requirements, massive growth in traffic volume, and to reduce capital and operational expenditures. Network virtualization coupled with function virtualization enables network providers to offer on-demand virtualized...

Welcome to the fourth installment of the IEEE Communications Magazine Series on Network Softwarization and Management. We are very excited to introduce this issue and write this first editorial as a new team of Series Editors. We start by expressing our sincere gratitude and appreciation to the past Series Editors, professors Alex Galis, Kohei Shio...

W elcome to the fourth installment of the IEEE Communications Magazine Series on Network Soft-warization and Management. We are very excited to introduce this issue and write this first editorial as a new team of Series Editors. We start by expressing our sincere gratitude and appreciation to the past Series Editors, professors Alex Galis, Kohei Sh...

Traffic classification is essential in network management for operations ranging from capacity planning, performance monitoring, volumetry, and resource provisioning, to anomaly detection and security. Recently, it has become increasingly challenging with the widespread adoption of encryption in the Internet, e.g., as a de-facto in HTTP/2 and QUIC...

Network infiltrations due to advanced persistent threats (APTs) have significantly grown in recent years. Their primary objective is to gain unauthorized access to network assets, compromise system and data. APTs are stealthy and remain dormant for an extended period of time, which makes their detection challenging. In this paper, we leverage machi...

Detecting cyber threats has been an on-going research endeavor. In this era, Advanced Persistent Threats (APTs) can incur significant costs for organizations and businesses. The ultimate goal of cybersecurity is to thwart attackers from achieving their malicious intent, whether it is credential stealing, infrastructure takeover, or program sabotage...

Artificial Intelligence (AI) and Machine Learning (ML) approaches have emerged in the networking domain with great expectation. They can be broadly divided into AI/ML techniques for network engineering and management, network designs for AI/ML applications, and system concepts. AI/ML techniques for networking and management improve the way we addre...

Machine Learning has revolutionized many fields of computer science. Reinforcement Learning (RL), in particular, stands out as a solution to sequential decision making problems. With the growing complexity of computer networks in the face of new emerging technologies, such as the Internet of Things and the growing complexity of threat vectors, ther...

Bot detection using machine learning (ML), with network flow-level features, has been extensively studied in the literature. However, existing flow-based approaches typically incur a high computational overhead and do not completely capture the network communication patterns, which can expose additional aspects of malicious hosts. Recently, bot det...

Detecting cyber threats has been an on-going research endeavor. In this era, advanced persistent threats (APTs) can incur significant cost for organizations and businesses. The ultimate goal of cyber security is to thwart attackers from achieving their malicious intent, whether it is credential stealing, infrastructure takeover, or program sabotage...

Recently, network infiltrations due to advanced persistent threats (APTs) have grown significantly, resulting in considerable losses to businesses and organizations. APTs are stealthy attacks with the primary objective of gaining unauthorized access to network assets. They often remain dormant for an extended period of time, which makes their detec...

Bot detection using machine learning (ML), with network flow-level features, has been extensively studied in the literature. However, existing flow-based approaches typically incur a high computational overhead and do not completely capture the network communication patterns, which can expose additional aspects of malicious hosts. Recently, bot det...

Bot detection using machine learning (ML), with network flow-level features, has been extensively studied in the literature. However, existing flow-based approaches typically incur a high computational overhead and do not completely capture the network communication patterns, which can expose additional aspects of malicious hosts. Recently, bot det...

Network Functions Virtualization (NFV), considered a key enabler of Network "softwarization", promises to reduce the capital and operational expenditure for network operators by moving packet processing from purpose-built hardware to software running on commodity servers. However, the state-of-the-art in NFV is merely replacing monolithic hardware...

Presents key events and topics in the global communications industry.

This short article reports on the 4th IEEE International Conference on Network Softwarization, held on June 25-29, 2018 in Montreal, Canada. It has been published in the Global Communications Newsletter of IEEE Communications Magazine.

The book gathers contributions presented at the 4th IEEE International Conference on Network Softwarization, Montreal, Canada. NetSoft 2018 aimed to shed light on the key technology components and systems underlying SDN-NFV, clouds-edges and emerging network service infrastructures for the efficient handling of heterogeneous resources across networ...

This short foreword introduces the technical program of the 4th IEEE International Conference on Network Softwarization (NetSoft 2018).

Machine Learning (ML) has been enjoying an unprecedented surge in applications that solve problems and enable automation in diverse domains. Primarily, this is due to the explosion in the availability of data, significant improvements in ML techniques, and advancement in computing capabilities. Undoubtedly, ML has been applied to various mundane an...

Over the last decade, a significant amount of effort has been invested on architecting agile and adaptive management solutions in support of autonomic, self-managing networks. Auto-nomic networking calls for automated decisions for management actions. This can be realized through a set of pre-defined network management policies engineered from huma...

We consider the problem of optimizing the sensing strategy of a monitoring system in the presence of faulty sensors. We develop ORSg, an efficient data-driven algorithm for computing sampling strategies that nearly maximize the submodular utility of sensing with only a fraction of active and fault-prone sensors. Our approach combines techniques fro...

The 6th International Conference on Network and Service Management (CNSM 2010) was held on October 25–29, 2010 in Niagara Falls, Canada. CNSM is a premier annual conference, sponsored by IEEE Communications Society and IFIP Working Group on Network and Distributed Systems Management, in the general area of network, systems, and service management....

The integration of external software in project development is challenging and risky, notably because the execution quality of the software and the trustworthiness of the software provider may be unknown at integration time. This is a timely problem and of increasing importance with the advent of the SaaS model of service delivery. Therefore, in ch...

The advent of service-oriented architectures has created a unique opportunity for business providers and consumers to establish more versatile and flexible interactions across the Internet by means of a new generation of services that are discoverable, composable, configurable, and reusable. In order to support such services all along their life cy...

With the increasing need for networked applications and distributed resource sharing, there is a strong incentive for an open large-scale service infrastructure operating over multi- domain and multi-technology networks. Service discovery, as an essential support function of such an infrastructure, is a crucial current research challenge. Although...

Emerging service-oriented architectures are push- ing towards on-demand and "on the fly" application and business process composition. In order to support service composition, the underlying infrastructure must provide a facility for on-demand discovery of services and service components. Discovery be- comes challenging when services span different...

Emerging service-oriented architectures are pushing towards on-demand and “on the fly” composition of applications and business processes. In order to support service composition, the underlying infrastructure must provide a facility for on-demand discovery of services and service components. Discovery becomes challenging when services span heterog...

The increasing availability of high-performance network resources creates a rich breeding ground for widely-distributed applications that span multiple network domains or administrative domains. Such applications provide services that can be accessed by remote users. Discovery and management of these systems require the ability to name the provided...

Wireless local-area networks (WLANs) based on the IEEE 802.11 technology have been widely adopted for private use over the past few years. However, several issues remain concerns for large-scale deployment in corporate environments. Enforcing security and quality-of-service (QoS) has become a fundamental challenge to managing IEEE 802.11-based ente...

With the increasing need for networked applications and distributed resource sharing, there is a strong incentive for an open large-scale service infrastructure operating over multi-domain and multi-technology networks. Service discovery, as an essential support function of such an infrastructure, is a crucial research challenge today. Cross-domain...

This presentation will outline our groundwork in designing a naming scheme for a cross-domain, Internet- scale service discovery framework. We will present a critical look at a sample of existing approaches in naming of services and resources and we will compare them against each other based on what we identify as relevant criteria. Finally, we wil...