Grant: Discovery Grants Program - Individual
Carleton University
$42,000.00
Security Techniques for Next Generation Networks
EF 2024-25
Résumé
With the interest of protecting public safety, the Canadian Parliament completed the second reading of Bill C-26 in March 2023, which presents an Act focused mainly on cybersecurity, amending the Telecommunications Act and making consequential amendments to other Acts. The proposed research program aligns closely with such public interest where the overarching innovative element in this program is building attack-resilient Next Generation Networks (NGN).
In this proposal, the term NGN refers to the evolving communication networks that are expected to serve as critical infrastructure for society in an unprecedented way. The
COVID19 pandemic demonstrated how important the communication infrastructure is. Post pandemic, in addition to their importance in the daily lives of billions of people, NGN are also expected to be a crucial element in supporting other critical infrastructures such as power grids and transportation systems.
The proposed program adopts the vision that while the current security practices served us to get to this point, there is a pressing need for new security techniques that will work for NGN that will serve as critical (if not the most critical) infrastructures in our society. Therefore, the long-term objective of this proposed research program is: "to create new security techniques for next generation networks that will focus on dynamic defences, customized Machine Learning, and effective, scalable evaluation approaches."
This will be achieved by pursuing the following innovative and complementary themes:
-Dynamic security techniques which include detection in large networks. The program will also focus on deployable defences that rely on Federated Learning. Performance will be a key issue in deployability.
-Machine learning geared towards network traffic and events: this theme will focus on studying practical attacks and defences that are based on Machine Learning in communication networks.
-Effective, scalable network security evaluation approaches: this theme will deal with outdated and problematic datasets by trying to create new datasets in collaboration with other researchers and organizations. We will also continue our work on creating large scale network emulation environments.
This program will have an impact on research through the creation of new research techniques that other researchers can utilize to enhance research in network security. It will also help train highly qualified personnel in areas that are crucial for the Canadian Information Security industry.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2024-05333
Name nom
Matrawy, Ashraf
Department département
School of Information Technology
Organization id
23
Institution établissement
Carleton University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
42000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
803
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer communications
Area of application fr
Téléinformatique
Research subject code
2508
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Communications networks
Research subject fr
Réseaux de télécommunications
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Security Techniques for Next Generation Networks
Keywords
network defences; network security; threat model; information security; security evaluation
Application summary
With the interest of protecting public safety, the Canadian Parliament completed the second reading of Bill C-26 in March 2023, which presents an Act focused mainly on cybersecurity, amending the Telecommunications Act and making consequential amendments to other Acts. The proposed research program aligns closely with such public interest where the overarching innovative element in this program is building attack-resilient Next Generation Networks (NGN).
In this proposal, the term NGN refers to the evolving communication networks that are expected to serve as critical infrastructure for society in an unprecedented way. The
COVID19 pandemic demonstrated how important the communication infrastructure is. Post pandemic, in addition to their importance in the daily lives of billions of people, NGN are also expected to be a crucial element in supporting other critical infrastructures such as power grids and transportation systems.
The proposed program adopts the vision that while the current security practices served us to get to this point, there is a pressing need for new security techniques that will work for NGN that will serve as critical (if not the most critical) infrastructures in our society. Therefore, the long-term objective of this proposed research program is: "to create new security techniques for next generation networks that will focus on dynamic defences, customized Machine Learning, and effective, scalable evaluation approaches."
This will be achieved by pursuing the following innovative and complementary themes:
-Dynamic security techniques which include detection in large networks. The program will also focus on deployable defences that rely on Federated Learning. Performance will be a key issue in deployability.
-Machine learning geared towards network traffic and events: this theme will focus on studying practical attacks and defences that are based on Machine Learning in communication networks.
-Effective, scalable network security evaluation approaches: this theme will deal with outdated and problematic datasets by trying to create new datasets in collaboration with other researchers and organizations. We will also continue our work on creating large scale network emulation environments.
This program will have an impact on research through the creation of new research techniques that other researchers can utilize to enhance research in network security. It will also help train highly qualified personnel in areas that are crucial for the Canadian Information Security industry.