Anomalous DNS Query Detection Using Machine Learning Approaches

For organizations that use the Internet, their employees will visit thousands of websites every day. However, there is a chance that the destination website is not safe to visit. Such websites may be fraudulent, phishing, or even data-stealing related. On the other hand, determining if the target website link is suspicious or not could help to prevent potential harm. Using a filtered list is the most straightforward way. The problem is, as the database for malicious websites is growing, hackers’ minds are also developing, which requiring a more profound way to deal with such a problem.

Network and Data Security Access Control

Imagine a refrigerator automatically orders the eggs from the online store to deliver at its location and make the payment on behalf of the owner. In today’s world, the network infrastructures are not limited to traditional datacenters or company’s premises. IoT (Internet of Things) and BYOD (Bring Your Own Device) are growing rapidly in our life. Network and Data Security Access Control plays a vital role to protect our data from being stolen intentionally or unintentionally.

Automation & Orchestration for Improved Security Communication

Speed is incredibly important when addressing issues with computer security. The longer the time between the attack’s start and resolution, the more assets that attackers can steal from a company. There are various security platforms that can alert a company to a cyber-attack. This research project aims to combine knowledge from all these platforms together at faster speeds than a human would be able to do. The cooperation between security platforms will allow ISA Cybersecurity Inc. to detect and respond to cyber-attacks faster than previously possible.

Building and Evaluating a Consolidated SIEM (Security Information and Event Management) Threat Identification

Businesses are collecting more and more data, but they do not have the manpower to properly analyse it. This project will implement a proof of concept for a system that uses machine learning to improve the detection of cyber threats. The machine learning algorithm will receive information from many different data sources, detect where there is suspicious activity, and alert a cyber analyst. By adding a machine learning algorithm to the arsenal of cyber analysts, the analysts will be able to cut down on the time it takes to react to the threats.

Creating a comparison and alert methodology for managing the CCTX feed

Most collaborations and government departments share their threat data feed in Data Exchange. Inescapably, nowadays with increasing threat data, it is a challenge to extract a large amount of threat data and unify the format more quickly. And as more and more companies join in sharing, the redundancy of this duplicate data will increase dramatically. This project proposes machine learning algorithms for automatic format conversion to extract threat information from the traffic data, and convert them into STIX format and detect whether these structured feeds already exist in CCTX.

Real-time Automated Security Report Generation

In today’s world, organizations protect themselves and their customer’s data through the implementation of complex cybersecurity solutions composed of many different nodes, each generating constant streams of data. Building reports from this data through the calculation of various metrics can provide much needed visibility into the state of the environment. However, building such reports can be a tedious and time-consuming process.

Effects of reducing the omega-6 to omega-3 fatty acid ratio in milk replacer on intestinal health in neonatal calves

Dairy calves are generally fed whole milk or milk replacer during the first weeks of life. Compared with whole milk, milk replacer containing vegetable oils has a higher polyunsaturated fat content. More specifically, it is high in omega-6 and low in omega-3 fatty acids, making the omega-6 to omega-3 fatty acid ratio ten times higher in milk replacer compared with whole milk.

Tech pioneer traces roots through partnership

A recipient of the World Economic Forum 2015 Technology Pioneer Award, Vancouver-based quantum computing company 1QBit is a leader among the most promising technology companies. The company works closely with Fortune 500 clients and leading hardware providers to solve problems in the areas of optimization, simulation, and machine learning. 

Determining Canadian Healthcare Providers' Intentions to Receive the COVID-19 Vaccine and Improving Current Health Communication Strategies

Some healthcare providers have concerns, misconceptions, and reluctance to receive the COVID-19 vaccine, which puts them at risk of occupational and public exposure to the virus. This is called vaccine hesitancy, which is defined as the delay or refusal of vaccines in the presence of vaccination services. Widespread vaccination is an effective public health measure in reducing health burdens and nationwide economic restrictions associated with the disease.

Promoting economic development and vitality of rural communities in Ontario - Year two

Many rural regions do not have a sufficient labour force providing the skills that rural businesses need. Many job vacancies go unfilled or are filled by less than ideal candidates. This research looks at strategies to attract and retain the workers that Ontario rural communities need to generate economic development and vitality. By engaging local actors, the researcher will analyze the various dimensions influencing attraction and retention of an appropriate labour force such as affordable and attainable housing, transportation, access to health services, education/training services.

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