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.
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.
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.
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.
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.
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.
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.
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.
Deep learning in medical imaging analysis has revolutionized the field in areas such as computer-aided detection and segmentation of clinical abnormalities. Several studies have been published on lung cancer screening using deep learning methodologies. Specific to lung cancer screening, algorithms have been trained to automatically detect and diagnose lesions in the lungs in low dose computed tomography (CT) by leveraging longitudinal imaging in combination with biopsy results.
The availability and reliability of public transit has been a long standing equity issue for residents living in rural communities. This issue significantly impacts those who have lower incomes, the elderly, children, and people with disabilities. Access to of consistent and secure funding has been the main factor challenging the sustainability of rural transit. This research focuses on understanding funding opportunities, challenges, and solutions for rural communities through a case-study of RIDE WELL in Wellington County, Ontario.