Knowledge Tree
Steve Wilson
Facts (10)
Sources
Cybersecurity Trends and Predictions 2025 From Industry Insiders itprotoday.com 6 facts
perspectiveSteve Wilson, chief product officer at Exabeam, advises that organizations must implement AI-driven security tools that continuously learn from and adapt to emerging attack patterns to counter advanced social engineering attacks.
claimSteve Wilson, chief product officer at Exabeam, observes that AI's ability to identify weaknesses faster than humans will significantly shrink the time between vulnerability discovery and exploitation.
claimSteve Wilson, chief product officer at Exabeam, advises companies to integrate generative AI copilots by ensuring interoperability with existing security infrastructure and training operators to collaborate with AI assistance.
perspectiveSteve Wilson, chief product officer at Exabeam, recommends that organizations adopt predictive AI capabilities and tools that simulate attack vectors to proactively identify and patch vulnerabilities.
claimSteve Wilson, chief product officer at Exabeam, states that training employees to recognize AI-powered threats will become essential for organizations.
claimSteve Wilson, chief product officer at Exabeam, predicts that by 2025, cyber attackers will use generative AI with improved reasoning abilities to execute realistic phishing scams, including deepfake voices and video avatars, and perform complex automated probing for vulnerabilities.
Cyber Insights 2025: Open Source and Software Supply Chain ... securityweek.com Jan 15, 2025 4 facts
claimSteve Wilson, Chief Product Officer at Exabeam, predicts that in 2025, the adoption of Software Bill of Materials (SBOMs) will expand beyond traditional software, with AI and machine learning applications driving demand for more advanced Bill of Materials frameworks.
claimSteve Wilson asserts that for government and defense organizations, managing AI supply chain complexity will require an expanded Machine Learning Bill of Materials (ML-BOM) standard that accounts for continuous updates, complex dependencies, and provenance tracking across AI and machine learning systems.
claimSteve Wilson states that Machine Learning Bill of Materials (ML-BOMs), as defined by CycloneDX, will need rapid evolution to address the intricacies of modern Large Language Model (LLM) applications.
claimSteve Wilson states that achieving interoperability across ecosystems remains critical, but automation and emerging regulatory standards will play a pivotal role in maintaining compliance and security across increasingly complex AI supply chains.