activity
20122023
most citedenpheeph: A Fault Injection Framework for Spiking and Compressed Deep Neural Networks

18 citations · 35 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CR2023

SHIELD: An Adaptive and Lightweight Defense against the Remote Power Side-Channel Attacks on Multi-tenant FPGAs

Mahya Morid Ahmadi, Faiq Khalid, Radha Vaidya +3

Dynamic partial reconfiguration enables multi-tenancy in cloud-based FPGAs, which presents security challenges for tenants, IPs, and data. Malicious users can exploit FPGAs for rem…

cs.AR2023

On the Susceptibility of QDI Circuits to Transient Faults

Raghda El Shehaby, Matthias Függer, Andreas Steininger

By design, quasi delay-insensitive (QDI) circuits exhibit higher resilience against timing variations as compared to their synchronous counterparts. Since computation in QDI circui…

cs.LG2023★ 2 cited

ISimDL: Importance Sampling-Driven Acceleration of Fault Injection Simulations for Evaluating the Robustness of Deep Learning

Alessio Colucci, Andreas Steininger, Muhammad Shafique

Deep Learning (DL) systems have proliferated in many applications, requiring specialized hardware accelerators and chips. In the nano-era, devices have become increasingly more sus…

cs.NI2022

ATLAS: An IoT Architecture and Secure Open-source Networking Stack for Anonymous Localization and Tracking Using Smartphones and Bluetooth Beacons

Bharath Srinivas Prabakaran, Felix Fasching, Juri Schreib +2

Bluetooth (BT) has revolutionized close-range communication enabling smart capabilities in everyday devices through wireless technology. One of the most important sub-domains of In…

cs.NE2022★ 18 cited

enpheeph: A Fault Injection Framework for Spiking and Compressed Deep Neural Networks

Alessio Colucci, Andreas Steininger, Muhammad Shafique

Research on Deep Neural Networks (DNNs) has focused on improving performance and accuracy for real-world deployments, leading to new models, such as Spiking Neural Networks (SNNs),…

cs.OH2020★ 1 cited

Efficient Metastability Characterization for Schmitt-Triggers

Jürgen Maier, Andreas Steininger

Despite their attractiveness as metastability filters, Schmitt-Triggers can suffer from metastability themselves. Therefore, in the selection or construction of a suitable Schmitt-…