scispace - formally typeset
T

Tommaso Frassetto

Researcher at Technische Universität Darmstadt

Publications -  26
Citations -  1306

Tommaso Frassetto is an academic researcher from Technische Universität Darmstadt. The author has contributed to research in topics: Cryptography & Guard (information security). The author has an hindex of 15, co-authored 23 publications receiving 875 citations.

Papers
More filters
Proceedings ArticleDOI

IoT Sentinel Demo: Automated Device-Type Identification for Security Enforcement in IoT

TL;DR: IoT Sentinel is presented, a system capable of automatically identifying the types of devices being connected to an IoT network and enabling enforcement of rules for constraining the communications of vulnerable devices so as to minimize damage resulting from their compromise.
Proceedings ArticleDOI

Nautilus: Fishing for Deep Bugs with Grammars

TL;DR: NAUTILUS is proposed, a method to efficiently fuzz programs that require highly-structured inputs by combining the use of grammars with theUse of code coverage feedback, which significantly outperforms state-of-the-art approaches like AFL by an order of magnitude and grammar fuzzers by more than a factor of two when measuring code coverage.
Proceedings Article

The guard's dilemma: efficient code-reuse attacks against intel SGX

TL;DR: Novel exploitation techniques against SGX are presented that do not require any enclave crashes and work in the presence of existing SGX randomization approaches such as SGX-Shield and can be applied to any enclave developed with the standard Intel SGX SDK on either Linux or Windows.
Proceedings ArticleDOI

DR.SGX: Hardening SGX Enclaves against Cache Attacks with Data Location Randomization

TL;DR: This paper designs and implements a compiler-based tool called DR.SGX that instruments enclave code such that data locations are permuted at the granularity of cache lines, and realizes the permutation with the CPU's cryptographic hardware-acceleration units providing secure randomization.
Proceedings ArticleDOI

VoiceGuard: Secure and Private Speech Processing

TL;DR: This work proposes an architecture, dubbed VoiceGuard, that efficiently protects the speech processing task inside a trusted execution environment (TEE) and preserves the privacy of users while at the same time it does not require the service provider to reveal model parameters.