Machine learning supports malware detection and threat analysis, but attackers can also exploit biased data, model weaknesses, or poisoned training.
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Machine learning is a way to build software that learns patterns from data and uses them to classify, predict, or make decisions, rather than relying solely on hand-written rules. Models may support malware and phishing detection, user- or entity-behavior analysis, vulnerability prioritization, and automated security triage. Their outputs are probabilistic, so unusual activity can be missed or incorrectly flagged; changing normal behavior can also cause model drift and reduce accuracy.
Security teams must protect both the model and its training data. An attacker may manipulate training examples (data poisoning), craft inputs designed to evade detection (adversarial examples), or extract sensitive information from a model or its data. Controls include trusted data provenance, access restrictions, testing against realistic evasive inputs, monitoring for drift, and human review of high-impact decisions. Where models process personal, proprietary, or security telemetry, collection, retention, and reuse require appropriate privacy and governance controls.
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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.
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.
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.
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.
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.
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.
State privacy laws, such as Washington State's My Health My Data Act, could throw a curve ball in the use of certain consumer information for artificial intelligence and machine learning endeavors, said regulatory attorney Adam Greene of the law firm Davis Wright Tremaine.
Javelin's Jennifer Pitt on AI-Powered Detection of Authorized Payment FraudMachine learning helps banks detect APP fraud by analyzing large transaction datasets faster. These AI models operate in near real-time and can distinguish legitimate transactions from fraudulent ones by spotting anomalies, said Jennifer Pitt, senior analyst at Javelin Strategy & Research.
New Export Rules Limit AI Chip Access Globally, Sparking Industry CriticismU.S. export controls slated for publication Monday aim to block foreign adversaries from accessing American advanced computing chips and blueprints for machine learning models. Nvidia and industry leaders have criticized the policy, warning it may harm innovation.
ActZero Purchase Adds Artificial Intelligence, Open Platform and Process MaturityWith its acquisition of ActZero, WatchGuard gains advanced machine learning capabilities and expertise to improve its MDR service. ActZero's mature processes and open platform enable seamless integration of WatchGuard products as well as third-party tools like Microsoft Defender.
iPhone Maker Introduced Feature Without Explicit ConsentApple's artificial intelligence-led photo analyzer is raising privacy concerns months after the company appears to have enabled the feature by default. It uses a combination of on-device machine learning and encrypted cloud-based processing.
ML, NLP Tools Collect More Personal Information Than Required, UK Regulator SaysArtificial intelligence tools currently used by organizations in the United Kingdom to screen job applicants pose privacy risks and are susceptible to biasness and accuracy issues, the U.K. Information Commissioner's Office found. The ICO focused on machine learning and natural language processing.
Featurespace's AI Expertise Will Enhance Visa's Fraud, Risk and Payments TechnologyVisa has signed a definitive agreement to acquire AI-driven fraud prevention leader Featurespace. This acquisition will reinforce Visa's fraud detection capabilities, integrating advanced machine learning technology to strengthen financial crime prevention and protect global transactions.
How to Navigate the New Challenges and OpportunitiesAI has enabled supply chains to become more proactive and predictive. Through machine learning algorithms, natural language processing and advanced analytics, organizations can now forecast demand with greater accuracy, anticipate potential disruptions and optimize inventory management in real time.
Training AI With Synthetic Data Can Lead to Model CollapseUsing facts to train artificial intelligence models is getting tougher, as companies run out of real-world data. AI-generated synthetic data is touted as a viable replacement, but experts say this may exacerbate hallucinations, which are already a big pain point of machine learning models.
Also: Dangers of Malicious Code Embedded in ML Models; Is Ransomware in Decline?AI's influence on social engineering and election security has become a focal point at Black Hat. ISMG editors discuss how advanced technologies are making it easier to manipulate people and compromise security systems and offer key insights on machine learning vulnerabilities.