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Grant: Canada Research Chairs

York University

$120,000.00

Behaviour-Centric Cybersecurity

EF 2023-24

Résumé
Dr. Lashkari’s CRC research program will define a fundamental anomaly detection model for cybersecurity based on an analysis of common behavioural patterns of benign users contrasted with those of known adversarial threats. This program will create an advanced model of detecting known and unknown threats, and zero-day attacks; the Universal Anomaly Detection (UAD) by designing and developing a Universal User Profile (UUP) and a Universal Anomaly profile (UAP). In conjunction with the development of this comprehensive fundamental model, this program will release an Understanding Cybersecurity Series (UCS) as a new platform for increasing public awareness and understanding of cybersecurity and for all users with varied levels of familiarity with the topic. This platform has two components: an academic and technical component, and a public non-technical component. The academic and technical component will target a readership primarily consisting of academic scholars, advanced educators, post-secondary students, researchers and developers, corporate decision-makers, industry professionals, government legislators and legal practitioners. The non-technical component will target the widest readership audience, including youth, seniors, laypeople, and the general public. Awareness of, and access to, these simplified materials will be facilitated via the distribution and promotion of research findings through social networks and other online communication channels. Addressing both the need for technical solutions to detect anomalous behaviour and increased public awareness to encourage better cybersecurity knowledge and practices will support our collective social responsibility for cybersecurity.
Programme
Canada Research Chairs
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
CRC-2021-00340
Name nom
Habibi LAshkari, Arash
Department département
School if Information Technology - York University
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2021
Award amount
120000
Program id
CRC
Program name en
Canada Research Chairs
Program name fr
Chaires de recherche du Canada
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
9998
Committee name en
Canada Research Chair Selection Committee
Committee name fr
Comité de sélection des Chaires de recherche du Canada
Area of application code
10000
Area of application group en
The socioeconomic objective available
Area of application group fr
L'objectif socioéconomique disponible
Area of application en
The socioeconomic objective available
Area of application fr
L'objectif socioéconomique disponible
Research subject code
10000
Research subject group en
The field of research available
Research subject group fr
The field of research available
Research subject en
Le domaine de recherche disponible
Research subject fr
Le domaine de recherche disponible
Field of research list codes
RDF1020601
Field of research list names en
Information system security
Field of research list names fr
Sécurité des systèmes d'information
Socioeconomic objective list codes
RDS10610
Socioeconomic objective list names en
Information systems, technologies and services
Socioeconomic objective list names fr
Systèmes, technologies et services d'information
Application title
Behaviour-Centric Cybersecurity
Keyword
Cybersecurity; Universal Anomaly Detection; Universal User Profile; Universal Anomaly profile; Understanding Cybersecurity Series; fundamental anomaly detection model; Cybersecurity Awareness Platform
Application summary
Dr. Lashkari’s CRC research program will define a fundamental anomaly detection model for cybersecurity based on an analysis of common behavioural patterns of benign users contrasted with those of known adversarial threats. This program will create an advanced model of detecting known and unknown threats, and zero-day attacks; the Universal Anomaly Detection (UAD) by designing and developing a Universal User Profile (UUP) and a Universal Anomaly profile (UAP). In conjunction with the development of this comprehensive fundamental model, this program will release an Understanding Cybersecurity Series (UCS) as a new platform for increasing public awareness and understanding of cybersecurity and for all users with varied levels of familiarity with the topic. This platform has two components: an academic and technical component, and a public non-technical component. The academic and technical component will target a readership primarily consisting of academic scholars, advanced educators, post-secondary students, researchers and developers, corporate decision-makers, industry professionals, government legislators and legal practitioners. The non-technical component will target the widest readership audience, including youth, seniors, laypeople, and the general public. Awareness of, and access to, these simplified materials will be facilitated via the distribution and promotion of research findings through social networks and other online communication channels. Addressing both the need for technical solutions to detect anomalous behaviour and increased public awareness to encourage better cybersecurity knowledge and practices will support our collective social responsibility for cybersecurity.