Failure-Oblivious Computing and Boundless Memory Blocks

Memory errors are a common cause of incorrect software execution and security vulnerabilities. We have developed two new techniques that help software continue to execute successfully through memory errors: failure-oblivious computing and boundless memory blocks. The foundation of both techniques is a compiler that generates code that checks accesses via pointers to detect out of bounds accesses. Instead of terminating or throwing an exception, the generated code takes another action that keeps the program executing without memory corruption. Failure-oblivious code simply discards invalid writes and manufactures values to return for invalid reads, enabling the program to continue its normal execution path. Code that implements boundless memory blocks stores invalid writes away in a hash table to return as the values for corresponding out of bounds reads. he net effect is to (conceptually) give each allocated memory block unbounded size and to eliminate out of bounds accesses as a programming error. We have implemented both techniques and acquired several widely used open source servers (Apache, Sendmail, Pine, Mutt, and Midnight Commander).With standard compilers, all of these servers are vulnerable to buffer overflow attacks as documented at security tracking web sites. Both failure-oblivious computing and boundless memory blocks eliminate these security vulnerabilities (as well as other memory errors). Our results show that our compiler enables the servers to execute successfully through buffer overflow attacks to continue to correctly service user requests without security vulnerabilities.Singapore-MIT Alliance (SMA

Survival Techniques for Computer Programs

Programs developed with standard techniques often fail when they encounter any of a variety of internal errors. We present a set of techniques that prevent programs from failing and instead enable them to continue to execute even after they encounter otherwise fatal internal errors. Our results indicate that even though the techniques may take the program outside of its anticipated execution envelope, the continued execution often enables the program to provide acceptable results to their users. These techniques may therefore play an important role in making software systems more resilient and reliable in the face or errors.Singapore-MIT Alliance (SMA

Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

Binary-level Function Profiling for Intrusion Detection and Smart Error Virtualization

Most current approaches to self-healing software (SHS) suffer from semantic incorrectness of the response mechanism. To support SHS, we propose Smart Error Virtualization (SEV), which treats functions as transactions but provides a way to guide the program state and remediation to be a more correct value than previous work. We perform runtime binary-level profiling on unmodified applications to learn both good return values and error return values (produced when the program encounters ``bad'' input). The goal is to ``learn from mistakes'' by converting malicious input to the program's notion of ``bad'' input. We introduce two implementations of this system that support three major uses: function profiling for regression testing, function profiling for host-based anomaly detection (environment-specialized fault detection), and function profiling for automatic attack remediation via SEV. Our systems do not require access to the source code of the application to enact a fix. Finally, this paper is, in part, a critical examination of error virtualization in order to shed light on how to approach semantic correctness

SECMACE: Scalable and Robust Identity and Credential Management Infrastructure in Vehicular Communication Systems

Several years of academic and industrial research efforts have converged to a common understanding on fundamental security building blocks for the upcoming Vehicular Communication (VC) systems. There is a growing consensus towards deploying a special-purpose identity and credential management infrastructure, i.e., a Vehicular Public-Key Infrastructure (VPKI), enabling pseudonymous authentication, with standardization efforts towards that direction. In spite of the progress made by standardization bodies (IEEE 1609.2 and ETSI) and harmonization efforts (Car2Car Communication Consortium (C2C-CC)), significant questions remain unanswered towards deploying a VPKI. Deep understanding of the VPKI, a central building block of secure and privacy-preserving VC systems, is still lacking. This paper contributes to the closing of this gap. We present SECMACE, a VPKI system, which is compatible with the IEEE 1609.2 and ETSI standards specifications. We provide a detailed description of our state-of-the-art VPKI that improves upon existing proposals in terms of security and privacy protection, and efficiency. SECMACE facilitates multi-domain operations in the VC systems and enhances user privacy, notably preventing linking pseudonyms based on timing information and offering increased protection even against honest-but-curious VPKI entities. We propose multiple policies for the vehicle-VPKI interactions, based on which and two large-scale mobility trace datasets, we evaluate the full-blown implementation of SECMACE. With very little attention on the VPKI performance thus far, our results reveal that modest computing resources can support a large area of vehicles with very low delays and the most promising policy in terms of privacy protection can be supported with moderate overhead.Comment: 14 pages, 9 figures, 10 tables, IEEE Transactions on Intelligent Transportation System