Formal methods for scalable trust

Defense Software for a Contested Future At the request of the DARPA, the National Academies conducted a study to explore how to enhance the assurance and agility of large-scale, integrated software-based systems. This report recommends ways the Department of Defense can engineer and manage its software systems to reduce cyber risk and enable more rapid system evolution to meet changing mission needs. Report is here: https://lnkd.in/eDrUdrUu Neat section on use and rapid maturing of formal methods to help with software assurance. Examples given: - CompCert: formally verified compiler for the C. An automated test tool that found hundreds of bugs in mainstream compilers like gcc and clang/LLVM found no bugs in CompCert's verified components after years of testing. - seL4: A high-assurance, open-source microkernel that serves as a trustworthy foundation for security-critical systems. It was successfully used in a Defense Advanced Research Projects Agency (DARPA) program to build a quadcopter drone that could resist red-team attacks. - NATS iFACTS: A large-scale air traffic control system in the United Kingdom, comprising 250,000 lines of code, that was formally proven to be free of runtime exceptions and to have functional correctness. It is written in SPARK, a subset of the Ada programming language designed for high-assurance systems. - Project Everest: A collaboration that produced formally verified, high-performance implementations of components of the HTTPS ecosystem, such as the TLS protocol and cryptographic algorithms. This verified code is now widely deployed in Mozilla Firefox, the Linux kernel, and Microsoft's Hyper-V hypervisor, among others.

Applying formal verification in network security: Insights from a Caliptra project engineer As a formal verification engineer at LUBIS EDA, I've had the privilege of working on the Caliptra project, ensuring the reliability of cryptographic algorithms like SHA-256, SHA-512, DOE, ECC, and HMAC. 🛡️ Formal verification in network security uses mathematical methods to exhaustively prove that a system behaves as intended under all possible conditions. This is crucial for cryptographic systems, where minor errors can lead to serious security issues. Here's what we did: - Property Generation: Using LUBIS tools, we defined the expected behavior and security characteristics of each algorithm. - Abstraction Techniques: We used black-boxing, signal cutting, and constraints to manage complexity and improve proof convergence. - Divide-and-Conquer Strategy: We split the design into smaller blocks, verifying each independently to handle state space explosion effectively. Challenges included modeling complex cryptographic algorithms and managing state space explosion. Yet, formal verification provided high assurance of security and comprehensive coverage, catching bugs that traditional testing might miss. 🔍 The result?  A mathematically guaranteed security for the Root of Trust (RoT) in data center SoCs, enhancing overall system reliability. Want to discuss more about formal verification in cryptographic systems? Drop your thoughts below! 👇 #SemiconductorIndustry #Semiconductors #FormalVerification

Verified to the Core: How Enterprises Can Trust ZK Technology on Ethereum This is a major step forward for the Ethereum ecosystem - congratulations to the Nethermind Security team! For businesses exploring blockchain and zero-knowledge (ZK) technology, this work is especially important. ZK systems are being used more and more in areas such as secure identity, private transactions, and efficient data verification. But the logic behind these systems called "ZK circuits" is extremely super complex. If something goes wrong in how they're written, it could lead to security issues, data leaks, or system failures. That’s why formal verification deeply matters. It’s a rigorous way of using mathematics to prove that a system is working exactly as intended - like a digital blueprint with guaranteed accuracy. For enterprises, this means: Stronger security: You can trust that sensitive operations (like proving a user’s identity without revealing their data) are safe and error-free. Lower risk: It reduces the chance of costly bugs or vulnerabilities being exploited. Reliable infrastructure: Builds a solid foundation for scaling blockchain-based business applications. With support from the Ethereum Foundation, this initiative brings a new level of trust and safety to zero-knowledge applications - making Ethereum a more reliable and secure platform for enterprise adoption. In addition to formally verifying complex ZK circuits, our team at Nethermind also specializes in formally verifying smart contracts - the core logic behind decentralized applications. This makes us an ideal security partner for enterprises and institutions seeking deep technical assurance across the blockchain stack. In a world moving toward automation and cryptographic guarantees, enterprises that don’t adopt formal verification will fall behind - both in security and in the ability to meet future regulatory and trust standards.

Jaxon's been doing a lot of work in regulated industries like Financial Services, Healthcare, and Insurance. Places where AI's decisions have profound implications. Something we've learned while working with the Department of Defense is how to embrace 'Formal Methods' and why it matters... Predictability and Safety: In environments where errors can have serious consequences, formal methods provide a structured approach to ensure AI systems behave as intended. This involves using mathematical models to define system behavior, reducing the risk of unexpected outcomes. Regulatory Compliance: These industries are governed by strict regulations. Formal methods offer a transparent framework, making AI systems more interpretable and explainable. This is crucial not only for regulatory approval but also for building trust with stakeholders. Risk Mitigation: By preemptively identifying and addressing potential faults or areas of uncertainty, formal methods help in mitigating risks. This proactive approach is essential in fields where the cost of failure is high. For AI to be effectively and safely integrated into regulated industries, the adoption of formal methods is a necessity. #AI #Formalisms #Math