Department of National Defence, Canada

IDEaS, Aug 2019 - Feb 2020

• The project falls under the umbrella - “Understanding Cyber Intent”.
• A Context-Aware and Machine Learning Framework was presented to Predict, Detect and Differentiate Cyber-Attacks. The proposed framework includes three modules, a cognitive module for detecting known attacks against existing attack signatures, an adaptive module for generating alerts, mitigating the effects of known attacks, and context-aware use of resource-intensive ML and DL tasks, and a classification module for classifying attacks with machine-learning techniques and neural networks.
• Neural Network Distillation process was implemented to interpret the learning models to update existing attack signatures of Snort.

Arolytics Inc. [Phase II]

NSBI Voucher Grant Oct 2019 - Feb 2020

• This research project revolves around building a framework that securely stores user's credentials and streamline data generated by gas emission plants.
• Several hashing algorithms, data encryption algorithms, key exchange techniques, and 2-factor authentication was implemented.
• The application was built on flask, using Mondo DB as a database, and deployed in AWS.

Arolytics Inc. [Phase I]

NSBI Voucher Grant July 2019 - Sept 2019

• This research project involved building a solution to generate plume concertation for gas emission plants.
• The solution was developed in python and JavaScript in order to implement the Gaussian model-based plume dispersion algorithm and visualizing the concentration in a web-interactive map.

Spritely Technologies Inc.

NSBI Voucher Grant Dec 2018 - Feb 2019

• A literature survey was conducted on real time communication protocol (RTCP) to implement real time chat system and notification system.
• Developed a functioning demo on implementing third party chatting engines such as PubNub, Pusher, SendBird and ChatCamp.