[Blog] Cybersecurity Solutions for the AI and Quantum Era

The rise of AI systems and advancing quantum computing capabilities are fundamentally reshaping the security landscape for modern organizations. While these technologies bring unprecedented capabilities, they also introduce complex security vulnerabilities that traditional cyber defense approaches struggle to address. Organizations must now position themselves to meet rising security needs, while maintaining the flexibility to address current and future threats.

Recent regulatory guidelines underscore this urgency. The National Institute of Standards and Technology’s (NIST) standardization of post-quantum cryptography (PQC) algorithms signal a fundamental shift. Meanwhile, the NSA’s Commercial National Security Algorithm Suite 2.0 requirements mandate PQC implementation by 2025 for web signing and servers, followed by 2026 requirements for telecom equipment firmware. These evolving requirements arrive at a crucial moment as AI systems become more deeply embedded in operations and quantum computing threatens to break current cryptographic protections.

To address these forces and commemorate Cybersecurity Awareness Month, Lattice security experts hosted a LinkedIn Live panel discussion on emerging security challenges in the age of AI and quantum computing. The panel also highlighted why Lattice’s Field Programmable Gate Array (FPGA) technology will be critical to cyber resiliency during the AI and quantum era.

The Importance of Data Provenance

As AI systems become more prevalent, establishing and maintaining data provenance becomes essential for ensuring the integrity and reliability of AI-driven decisions. Data provenance represents the complete lineage of data from its origin through every transformation and movement – indicating where data came from, who accessed it, how it has been modified, and whether it can be trusted.

Organizations must implement provenance systems that track data from its point of origin through various transformations, creating an unbroken chain of trust. This means documenting not just the data itself, but also metadata about time, location, device information, and any transformations or analyses performed.

For AI systems, it creates a verifiable record of training data sources and modifications, enabling organizations to validate AI model outputs and identify potential security compromises.

It is important to remember that AI systems are only as reliable as their underlying data. Three key vulnerabilities highlight the critical need for data provenance.

• Malicious training, demonstrated in autonomous vehicle systems, enables attackers to deliberately mislead AI systems and put users at risk. This same vulnerability could affect AI systems managing critical operations or automated processes.
• Data poisoning allows bad actors to corrupt training datasets, leading to incorrect or biased AI responses that could impact everything from network optimization to quality control.
• Data drift causes changes in data collection patterns, such as shifting from minute-to-minute to hourly sampling, that severely impact AI model accuracy. This could lead to missed maintenance warnings or suboptimal resource allocation decisions, potentially compromising both efficiency and security.

Mitigating these threats lies in implementing comprehensive data provenance systems that cryptographically bind metadata to data at the first point of digitization. FPGAs excel in this role as the first point of digitization in systems, sitting next to sensors and other data collection points. Embedding FPGAs within data processing streams allows organizations to facilitate safe and secure data management, enabling effective identification and tracking throughout the AI system development lifecycle. Organizations can strengthen data security by leveraging FPGAs’ built-in security features, including encryption and authentication mechanisms, to safeguard and securely tag data during processing.

Navigating Quantum-Based Threats

The quantum computing threat isn't just a distant concern. While viable quantum computers may not arrive until around 2030, organizations are facing a rising frequency of "harvest now, decrypt later" (HNDL) attacks today. In these attacks, threat actors harvest encrypted data for when quantum computers will be able to break current asymmetric cryptography defenses. This threat particularly impacts long-term sensitive data like proprietary algorithms, customer information such as social security numbers, medical records, bank information, and process data that maintain their value over time. In turn, organizations must be positioned to meet CNSA 2.0 compliance by effectively migrating to PQC.

However, the transition to PQC presents its own challenges. Developers need crypto-agile solutions that can adapt as vulnerabilities are discovered and new algorithms emerge. FPGA technology enables this agility through field-upgradeable security features and the ability to implement new cryptographic algorithms as needed, providing a crucial advantage for organizations who need to maintain security over extended deployment lifecycles.

How FPGAs Enhance Security Efforts

FPGA technology offers unique advantages in meeting modern security challenges. Unlike fixed-function processors limited by microcode, FPGAs provide truly flexible, reprogrammable hardware capable of parallel processing and real-time security operations. This flexibility proves crucial for implementing platform firmware resiliency (PFR) and attestation capabilities, ensuring systems boot securely and maintain trusted operations across complex deployments.

Security-focused Lattice FPGAs such as Lattice MachXO3D™, Lattice MachXO5D™-NX, and Lattice Mach™-NX serve as Hardware Root of Trust (HRoT) anchors, controlling power sequencing and establishing security parameters before other system components activate. Their ability to run PQC while maintaining current security measures enables smooth transitions to new security paradigms, and their parallel processing capabilities allow simultaneous data collection, cryptographic operations, and security monitoring without performance compromises.

Moreover, FPGAs' reprogrammable nature enables organizations to adapt to emerging threats and evolving security standards without hardware replacements. This capability proves particularly valuable in environments where equipment often remains deployed for extended periods and must maintain security compliance throughout its operational life.

The rise of AI and quantum computing demands security solutions that are both robust and adaptable. FPGA technology, with its unique combination of flexibility, processing power, and security features, provides a foundation for addressing current threats while adapting to future challenges. As security requirements continue to evolve and new vulnerabilities emerge, organizations that implement adaptable, FPGA-based security solutions will be best positioned to protect their assets, maintain compliance, and ensure the integrity of their operations well into the AI and quantum era.

To learn more about how Lattice can help you implement PQC and future-proof your system designs, reach out to our team today.