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Latest coverage for Machine Learning

Explore the intersection of machine learning and information security, covering the latest trends, threats, and innovations in cyber defense.

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Machine Learning is a branch of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed. It involves computer algorithms that can analyze patterns and make decisions with minimal human intervention.

In the context of information security, machine learning plays a critical role in detecting and responding to emerging threats. It helps to identify anomalous behavior, such as unusual network traffic or unfamiliar access patterns, which could indicate a security breach. Additionally, machine learning algorithms are used to automate the analysis of large volumes of security-related data, improving the accuracy and efficiency of threat detection systems. By continuously learning from new data, these systems can adapt to the ever-evolving cybersecurity landscape, providing enhanced protection against sophisticated attacks.

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Showing 20 most recent headlines of 108 Filtered view

Artificial intelligence (AI) is making its way into security operations quickly, but many practitioners are still struggling to turn early experimentation into consistent operational value. This is because SOCs are adopting AI without an intentional approach to operational integration. Some teams treat it as a shortcut for broken processes. Others attempt to apply machine learning to problems

Bank Info Security 5 months, 4 weeks ago

US, Allies Warn AI in OT May Undermine System Safety

AI in OT May Trigger Cascading Infrastructure FailuresThe U.S. cyber defense agency warned that machine learning and large language model deployments can introduce new attack surfaces across critical infrastructure sectors in a document setting out principles for safely integrating AI into operational technology.

Bank Info Security 6 months, 3 weeks ago

AI in Genomics: Balancing Innovation and Patient Privacy

Ethicist Harry Farmer on Data Privacy, Predictive Analytics and Fairness IssuesArtificial intelligence, particularly machine learning, is transforming genomics by enabling powerful predictions about health and human traits from DNA data. But this convergence of technologies raises major red flags related to data privacy and security, said senior researcher Harry Farmer.

How to avoid your business being felled by an AI-powered ransomware attack that costs less than a laptop. Passwork KNP Logistics Group, a British transport company from Northamptonshire that’s been around longer than the mass-produced lightbulb, collapsed after a devastating security breach that left more than 700 employees jobless. The 158-year-old firm fell victim to a ransomware attack.…

XML-Based Messaging Tech Extends Fraud Detection Into Wider Bank Use CasesACI's signals network intelligence harnesses neural networks and federated machine learning to spot fraud in real time without banks sharing data. Beyond fraud detection, its insights can drive business growth from other business units, and ACI aims to accelerate adoption by making it open source.

Bank Info Security 9 months, 4 weeks ago

Delta Air Lines Taps AI to Rewrite Rules of Ticket Pricing

AI Helps Delta Shift 20% of Ticket Pricing to Real-Time Automation by 2025Delta Air Lines is revolutionizing ticket pricing with AI, aiming to automate 20% of fares by 2025. Partnering with Fetcherr, the airline uses real-time data and machine learning for personalized pricing, raising revenue potential and privacy concerns.

WeTransfer added the magic words "machine learning" to its ToS and users reacted predictably Analysis WeTransfer this week denied claims it uses files uploaded to its ubiquitous cloud storage service to train AI, and rolled back changes it had introduced to its Terms of Service after they deeply upset users. The topic? Granting licensing permissions for an as-yet-unreleased LLM product.…

Bank Info Security 11 months, 4 weeks ago

AI in Healthcare: Top Privacy, Cyber, Regulatory Concerns

Emerging artificial intelligence and machine learning technologies being applied in the health and wellness space that are not necessarily covered by HIPAA but instead fall under a variety of tough new state privacy laws that are being enacted, said attorney Lily Li of Metaverse Law.

Emerging artificial intelligence and machine learning technologies being applied in the health and wellness space that are not necessarily covered by HIPAA but instead fall under a variety of tough new state privacy laws that are being enacted, said attorney Lily Li of Metaverse Law.

Machine Learning, Generative AI Bolster Continuous User AuthenticationFinancial institutions can use AI-fueled behavioral biometrics for real-time identity assurance. By continuously profiling how users interact with devices, firms can shift from one-time authentication to real-time identity assurance, turning every click, pause and keystroke into a frontline defense.

Politecnico di Milano's Zanero on Evolving Malware Detection and Hardware SecurityMachine learning excels at identifying repetitive patterns and anomalies, but human insight remains vital for understanding the broader context of cyberattacks - especially in cyber-physical ecosystems, said Stefano Zanero, professor at Politecnico di Milano.

The Hacker News 1 year, 1 month ago

Artificial Intelligence – What's all the fuss?

Talking about AI: Definitions Artificial Intelligence (AI) — AI refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence, such as decision-making and problem-solving. AI is the broadest concept in this field, encompassing various technologies and methodologies, including Machine Learning (ML) and Deep Learning

Bank Info Security 1 year, 2 months ago

Fighting Financial Fraud With Adversarial AI Defenses

Experts Weigh the Advantages and Risks of Generative Adversarial NetworksWith traditional rule-based fraud detection systems and even conventional machine learning models struggling to identify these highly deceptive fraud patterns, financial institutions are exploring generative adversarial networks to enhance fraud detection.

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