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Federated Learning (FL) enables collaborative model training across distributed devices while safeguarding data and user privacy. However, FL remains susceptible to privacy threats that can compromise data via direct means. That said,…
We propose an architecture, called NVQLink, for connecting high-performance computing (HPC) resources to the control system of a quantum processing unit (QPU) to accelerate workloads necessary to the operation of the QPU. We aim to support…
We propose a modification to the transpiler of a quantum computer to safeguard against side-channel attacks aimed at learning information about a quantum circuit. We demonstrate that if it is feasible to shield a specific subset of gates…
The arm race between hardware security engineers and side-channel researchers has become more competitive with more sophisticated attacks and defenses in the last decade. While modern hardware features improve the system performance…
Communication among devices in multi-GPU systems plays an important role in terms of performance and scalability. In order to optimize an application, programmers need to know the type and amount of the communication happening among GPUs.…
For a distributed last-level cache (LLC) in a large multicore chip, the access time to one LLC bank can significantly differ from that to another due to the difference in physical distance. In this paper, we successfully demonstrated a new…
The great performance of machine learning algorithms and deep neural networks in several perception and control tasks is pushing the industry to adopt such technologies in safety-critical applications, as autonomous robots and self-driving…
Acoustic side-channel attacks on keyboards can bypass security measures in many systems that use keyboards as one of the input devices. These attacks aim to reveal users' sensitive information by targeting the sounds made by their keyboards…
Modern heterogeneous supercomputing systems are comprised of compute blades that offer CPUs and GPUs. On such systems, it is essential to move data efficiently between these different compute engines across a high-speed network. While…
Both AMD and Intel have presented technologies for confidential computing in cloud environments. The proposed solutions - AMD SEV (-ES, -SNP) and Intel TDX - protect Virtual Machines (VMs) against attacks from higher privileged layers…
Effective intra-node GPU communication is essential for optimizing performance in MPI-based HPC applications, especially when leveraging multiple communication paths. In this study, we propose a novel approach that integrates CUDA Graphs…
Quantum circuit cutting enables near-term quantum devices to execute workloads exceeding their qubit capacity by decomposing circuits into independently runnable fragments. While this extends computational reach, it creates a previously…
Detecting covert channels among legitimate traffic represents a severe challenge due to the high heterogeneity of networks. Therefore, we propose an effective covert channel detection method, based on the analysis of DNS network data…
New hardware primitives such as Intel SGX secure a user-level process in presence of an untrusted or compromised OS. Such "enclaved execution" systems are vulnerable to several side-channels, one of which is the page fault channel. In this…
The transient-execution attack Meltdown leaks sensitive information by transiently accessing inaccessible data during out-of-order execution. Although Meltdown is fixed in hardware for recent CPU generations, most currently-deployed CPUs…
In the last two decades, the evolving cyber-threat landscape has brought to center stage the contentious tradeoffs between the security and performance of modern microprocessors. The guarantees provided by the hardware to ensure no…
Network-on-Chip (NoC) is widely used to facilitate communication between components in sophisticated System-on-Chip (SoC) designs. Security of the on-chip communication is crucial because exploiting any vulnerability in shared NoC would be…
Edge AI inference is becoming prevalent thanks to the emergence of small yet high-performance microprocessors. This shift from cloud to edge processing brings several benefits in terms of energy savings, improved latency, and increased…
Side-channel attacks allow to extract sensitive information from cryptographic primitives by correlating the partially known computed data and the measured side-channel signal. Starting from the raw side-channel trace, the preprocessing of…
Securing deep neural networks (DNNs) from side-channel attacks is an important problem as of today, given the substantial investment of time and resources in acquiring the raw data and training complex models. All published countermeasures…