Double Helix and RAVEN: A System for Cyber Fault Tolerance and Recovery

Cyber security research has produced numerous artificial diversity techniques such as address space layout randomization, heap randomization, instruction-set randomization, and instruction location randomization. To be most effective, these techniques must be high entropy and secure from information leakage which, in practice, is often difficult to achieve. Indeed, it has been demonstrated that well-funded, determined adversaries can often circumvent these defenses. To allow use of low-entropy diversity, prevent information leakage, and provide provable security against attacks, previous research proposed using low-entropy but carefully structured artificial diversity to create variants of an application and then run these constructed variants within a fault-tolerant environment that runs each variant in parallel and cross check results to detect and mitigate faults. If the variants are carefully constructed, it is possible to prove that certain classes of attack are not possible. This paper presents an overview and status of a cyber fault tolerant system that uses a low overhead multi-variant execution environment and precise static binary analysis and efficient rewriting technology to produce structured variants which allow automated verification techniques to prove security properties of the system. Preliminary results are presented which demonstrate that the system is capable of detecting unknown faults and mitigating attacks.