In practical applications closer to the operational layer and industrial control environments, OPSWAT proposes a zero-trust file strategy centered on Content Reversal and Reconstruction (CDR). This strategy removes hidden threats at the source, reconstructs trustworthy content, and ensures that files are free from malicious payloads before entering the network. Yu-Hua Chou, OPSWAT’s North Asia technical consultant, points out that in the past, enterprises often failed to detect attacks lurking in PDFs, Office files, or compressed files due to antivirus software omissions, special formatting, or delayed updates. CDR technology can parse files into neutral elements, filter dangerous objects, and then reconstruct them into clean files, achieving real-time protection without signature-based dependencies.
OPSWAT also emphasizes the application of one-way gateways and Kiosk self-service exchange stations to separate IT/OT data flows, preventing data leakage and malicious intrusion. This provides hardware-level isolation protection, particularly for nuclear power, manufacturing, transportation, and semiconductor industries. Combined with the integration of SBOM (Software Bill of Materials), COO (Country of Origin) and multi-source scanning engines, it constructs a comprehensive platform suitable for critical infrastructure. Zhou Yuhua emphasized that only by starting with the native security of files and devices can we block complex attack paths such as phishing emails, USB penetration, and supply chain vulnerabilities, and implement the zero-trust protection spirit of “not trusting any content until verification.”
From Trend Micro’s perspective, generative AI is not only a source of security challenges, but also an opportunity to restructure governance systems. Li Jiuhuang, Vice President of Product Management at Trend Micro, pointed out that the Trend Vision One platform deeply embeds AI protection mechanisms into data control, access permissions, model evaluation, and usage behavior. Through Data Security Posture Management (DSPM), container scanning, API risk analysis, and Deepfake detection modules, it establishes a complete AI governance map for enterprises. The platform’s AI Simulation module can further assist enterprises in simulating model behavior, predicting potential risks and attack paths, and generating audit reports and compliance recommendations, which is of critical value to organizations that need to comply with regulations such as GDPR and ISO 42001.
In this wave of generative AI, data is the lifeline, and governance is the line of defense. Faced with the gradual erosion of digital trust and the ever-expanding blurred boundaries of AI, enterprises that fail to deploy AI-native cybersecurity and governance mechanisms early on risk control and market competitiveness may lose their leading position in the next wave of evolution. Multi-layered integration, from architecture, platform, operations, and archives to the model itself, is the direction revealed by major cybersecurity companies. The symbiotic evolution of AI and cybersecurity will be the inevitable path for enterprises to achieve intelligent operations and sustainable security.
