Artificial intelligence systems are increasingly trusted to detect cyber threats, guide operational decisions, and interpret complex digital environments. Yet a deeper vulnerability is emerging one that does not attack what AI systems do, but what they believe. Modern AI systems continuously construct internal models of reality from the data they ingest stuff like logs, telemetry streams, behavioral signals, threat intelligence feeds, and external knowledge sources. These signals shape how machines interpret events, evaluate risks, and determine what actions to take. If those signals are manipulated, the system’s understanding of reality can quietly drift. Nothing appears broken. Dashboards look normal. Alerts still trigger. Confidence scores remain high. But beneath the surface, the machine’s beliefs have already changed. Epistemic Corruption Attacks explores how adversaries can manipulate the informational environment surrounding AI systems to influence their reasoning. Instead of attacking algorithms directly, attackers can reshape the signals that machines rely on to understand the world. Because the most dangerous failure in an AI system is not when it stops working. It is when it continues working with complete confidence while being completely wrong.
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Paperback. Etat : new. Paperback. Artificial intelligence systems are increasingly trusted to detect cyber threats, guide operational decisions, and interpret complex digital environments. Yet a deeper vulnerability is emerging one that does not attack what AI systems do, but what they believe. Modern AI systems continuously construct internal models of reality from the data they ingest stuff like logs, telemetry streams, behavioral signals, threat intelligence feeds, and external knowledge sources. These signals shape how machines interpret events, evaluate risks, and determine what actions to take. If those signals are manipulated, the system's understanding of reality can quietly drift. Nothing appears broken. Dashboards look normal. Alerts still trigger. Confidence scores remain high. But beneath the surface, the machine's beliefs have already changed. Epistemic Corruption Attacks explores how adversaries can manipulate the informational environment surrounding AI systems to influence their reasoning. Instead of attacking algorithms directly, attackers can reshape the signals that machines rely on to understand the world. Because the most dangerous failure in an AI system is not when it stops working. It is when it continues working with complete confidence while being completely wrong. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9789999339544
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Taschenbuch. Etat : Neu. Epistemic Corruption Attacks | Poisoning What AI Security Systems Know Rather Than What They Do | Pranav Bhatnagar | Taschenbuch | Englisch | 2026 | Eliva Press | EAN 9789999339544 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 135116558
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial intelligence systems are increasingly trusted to detect cyber threats, guide operational decisions, and interpret complex digital environments. Yet a deeper vulnerability is emerging one that does not attack what AI systems do, but what they believe. Modern AI systems continuously construct internal models of reality from the data they ingest stuff like logs, telemetry streams, behavioral signals, threat intelligence feeds, and external knowledge sources. These signals shape how machines interpret events, evaluate risks, and determine what actions to take.If those signals are manipulated, the system's understanding of reality can quietly drift.Nothing appears broken.Dashboards look normal.Alerts still trigger.Confidence scores remain high.But beneath the surface, the machine's beliefs have already changed.Epistemic Corruption Attacks explores how adversaries can manipulate the informational environment surrounding AI systems to influence their reasoning. Instead of attacking algorithms directly, attackers can reshape the signals that machines rely on to understand the world.Because the most dangerous failure in an AI system is not when it stops working.It is when it continues working with complete confidence while being completely wrong. N° de réf. du vendeur 9789999339544
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