arXiv subjects

Hamza Omar

Publications and source records attributed to Hamza Omar.

3 recordsLinked to original sources

arXiv2020

IRONHIDE: A Secure Multicore that Efficiently Mitigates Microarchitecture State Attacks for Interactive Applications

Microprocessors enable aggressive hardware virtualization by means of which multiple processes temporally execute on the system. These security-critical and ordinary processes interact with each other to assure application progress. However, temporal sharing of hardware resources exposes the processor to various microarchitecture state attacks. State-of-the-art secure processors, such as MI6 adopt Intel's SGX enclave execution model. MI6 architects strong isolation by statically isolating shared memory state, and purging the microarchitecture state of private core, cache, and TLB resources on every enclave entry and exit. The purging overhead significantly impacts performance as the interactivity across the secure and insecure processes increases. This paper proposes IRONHIDE that implements strong isolation in the context of multicores to form spatially isolated secure and insecure clusters of cores. For an interactive application comprising of secure and insecure processes, IRONHIDE pins the secure process(es) to the secure cluster, where they execute and interact with the insecure process(es) without incurring the microarchitecture state purging overheads on every interaction event. IRONHIDE improves performance by 2.1x over the MI6 baseline for a set of user and OS interactive applications. Moreover, IRONHIDE improves performance by 20% over an SGX-like baseline, while also ensuring strong isolation guarantees against microarchitecture state attacks.

cs.CR↗

arXiv2017

Exploiting the Tradeoff between Program Accuracy and Soft-error Resiliency Overhead for Machine Learning Workloads

To protect multicores from soft-error perturbations, resiliency schemes have been developed with high coverage but high power and performance overheads. Emerging safety-critical machine learning applications are increasingly being deployed on these platforms. Moreover, these systems are exposed to harsh environments, such as unmanned aerial vehicles (UAVs) and self-driving cars. Due to the unique structure and computational behavior of such applications, research has been done on relaxing their accuracy for performance benefits. We observe that not all transient errors affect program correctness, some errors only affect program accuracy, i.e., the program completes with certain acceptable deviations from error free outcome. This paper illustrates the idea of cross-layer soft-error resilience using machine learning workloads, where program accuracy is introduced as a tradeoff to deliver resilient yet efficient execution on futuristic large-scale multicores.

cs.DC↗

arXiv2017

Connecting the Dots: Privacy Leakage via Write-Access Patterns to the Main Memory

Data-dependent access patterns of an application to an untrusted storage system are notorious for leaking sensitive information about the user's data. Previous research has shown how an adversary capable of monitoring both read and write requests issued to the memory can correlate them with the application to learn its sensitive data. However, information leakage through only the write access patterns is less obvious and not well studied in the current literature. In this work, we demonstrate an actual attack on power-side-channel resistant Montgomery's ladder based modular exponentiation algorithm commonly used in public key cryptography. We infer the complete 512-bit secret exponent in $\sim3.5$ minutes by virtue of just the write access patterns of the algorithm to the main memory. In order to learn the victim algorithm's write access patterns under realistic settings, we exploit a compromised DMA device to take frequent snapshots of the application's address space, and then run a simple differential analysis on these snapshots to find the write access sequence. The attack has been shown on an Intel Core(TM) i7-4790 3.60GHz processor based system. We further discuss a possible attack on McEliece public-key cryptosystem that also exploits the write-access patterns to learn the secret key.

cs.CR↗