Cognitive and Computationally Intelligent Algorithms for the Detection of Cyber Threats

The rapid and widespread advancement of cyber-threats within the past few years has had a profound impact on virtually everyone, from ordinary people to governments to local organizations. This has caused cyber-security to be considered a global challenge, which is now requiring innovative solutions, such as incorporating human cognition based methods into the software algorithms to detect malicious activities of adversaries. This is because, the cyber-security industry is heavily dependent on the knowledge, and analysis and investigation skills of analysists in the detection of cyber-threats. The analysists have the ability to coalesce and examine in their minds large stacks and disparate sources of data, spread across small and large temporal and spatial windows, and compare their observations with previous known attacks to decide if the dataset objects under scrutiny represent an attack. TO BE CONT’D

Faculty Supervisor:

Ken Ferens

Student:

Mohammad Nurul Afsar Shaon;Kenneth Brezinski;Joshua Charles;Ainslee Heim;Andrew Sadik;Elivier Armando Reyes Davila;Siobhan Reid

Partner:

Canadian Tire

Discipline:

Engineering - computer / electrical

Sector:

Consumer goods

University:

University of Manitoba