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Zac Amos
81 Results Found
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FeatureHow to Identify Data Poisoning in Industrial AI
Data poisoning reduces AI accuracy by influencing what an industrial system learns and how it responds to inputs. -
FeatureCybersecurity Strategies for Managing End-of-Life Industrial IoT Devices
Organizations that establish strong life cycle management practices position themselves to adapt as threats evolve and technology advances. -
NewsPreparing Manufacturing Cybersecurity for the ‘Silver Tsunami’
The “silver tsunami” refers to the large-scale retirement of the Baby Boomer workforce, which can be especially impactful in the manufacturing sector. -
FeatureCybersecurity Compliance vs. Security: Why You Need Both in Manufacturing
“Compliance” and “security” are connected, but they involve different strategies. -
FeatureIs It Possible to Future-Proof Industrial Cybersecurity?
Future-proofing in cybersecurity is best understood as a strategic approach rather than as a promise of permanence. -
FeatureFive Unique Challenges in Incident Response for Distributed Industrial Security Teams
Distributed industrial security teams protect systems where cyber incidents can have real-world consequences, often without being physically present. -
FeatureManaging Shadow AI and IT in Industrial Settings
The existence of shadow AI and IT poses security risks to industry by inadvertently allowing hackers unauthorized access to sensitive systems or databases. -
FeatureWhy You Need Physical Security Testing in Manufacturing
Real-world access points deserve the same level of protection as digital systems. -
FeatureProbabilistic vs. Deterministic AI in Manufacturing
Understanding the differences between probabilistic and deterministic AI will help manufacturers make more informed choices and achieve measurable results. -
FeatureOvercoming 5 Challenges in Industrial Edge Security
Understanding security challenges in industrial edge computing can help teams develop practical solutions to protect organizational data and processes.