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The Role of Machine Learning in Cybersecurity: Exploring Anomaly Detection, Malware Detection, and User Behaviour Analytics.
The integration of machine learning (ML) in cybersecurity has brought about a revolutionary change in the industry, providing real-time detection and response to cyber threats. By analyzing behavior patterns, ML algorithms can identify and prevent new and emerging types of malware attacks, scrutinize network traffic for any unusual activity, and improve the accuracy and efficiency…
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Second Largest Canadian Grocer Sobeys Victim of Ransomware Linked to Russian Cybercrime Gang FIN7
A look into the Black Basta ransomware cyberattack that targeted Canadian grocer Sobeys.
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Mitigating the Risk of Credential Exposure
Over 60% of security breaches in the past year have been due to leaked credentials. What steps can you take to mitigate the risk?
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Optus data breach: hacker blames company
On September 22, 2022 a security breach took place on Optus, the Australian telecommunications company compromising 9,800,000 customers. Approximately 38% of the country.
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The Cyber Kill Chain and the Diamond Model of Intrusion Analysis
A broad overview of two very important concepts of becoming a cybersecurity professional.
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Working with Network Security Data & Digital Forensics and Incident Analysis
How to handle network security data and an overview of digital forensics. Helping to understand how an attack took place.
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Endpoint Vulnerability Assessment and Management
Understanding your cybersecurity baseline allows deviance from the norm to raise red flags and alert a potential cybersecurity event.
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Tools for Monitoring Network Security
Networks are subjected to patterns of data traffic, bandwidth usage, and resource access on a daily basis. The security of a network relies on the administrator being able to differentiate normal network behaviour with abnormal and potentially malicious network behaviour.
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