Related papers: Scrooge Attack: Undervolting ARM Processors for Pr…
We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Network (CNN) accelerators mapped to Field Programmable Gate…
The RRAM-based neuromorphic computing system has amassed explosive interests for its superior data processing capability and energy efficiency than traditional architectures, and thus being widely used in many data-centric applications. The…
Recent studies have shown that sponge attacks can significantly increase the energy consumption and inference latency of deep neural networks (DNNs). However, prior work has focused primarily on computer vision and natural language…
In-process compartmentalization and access control have been actively explored to provide in-place and efficient isolation of in-process security domains. Many works have proposed compartmentalization schemes that leverage hardware…
The various benefits of multi-tenanting, such as higher device utilization and increased profit margin, intrigue the cloud field-programmable gate array (FPGA) servers to include multi-tenanting in their infrastructure. However, this…
Modern processors include high-performance cryptographic functionalities such as Intel's AES-NI and ARM's Pointer Authentication that allow programs to efficiently authenticate data held by the program. Pointer Authentication is already…
Whether stemming from malicious intent or natural occurrences, faults and errors can significantly undermine the reliability of any architecture. In response to this challenge, fault detection assumes a pivotal role in ensuring the secure…
Machine Learning (ML)-powered apps are used in pervasive devices such as phones, tablets, smartwatches and IoT devices. Recent advances in collaborative, distributed ML such as Federated Learning (FL) attempt to solve privacy concerns of…
Adversaries with physical access to a target platform can perform cold boot or DMA attacks to extract sensitive data from the RAM. In response, several main-memory encryption schemes have been proposed to prevent such attacks. Also hardware…
The energy consumption of DRAM is a critical concern in modern computing systems. Improvements in manufacturing process technology have allowed DRAM vendors to lower the DRAM supply voltage conservatively, which reduces some of the DRAM…
Deep neural network (DNN) classifiers are powerful tools that drive a broad spectrum of important applications, from image recognition to autonomous vehicles. Unfortunately, DNNs are known to be vulnerable to adversarial attacks that affect…
Remote Code Execution (RCE) exploits pose a significant threat to AI and ML systems, particularly in GPU-accelerated environments where the computational power of GPUs can be misused for malicious purposes. This paper focuses on RCE attacks…
The ubiquity and pervasiveness of modern Internet of Things (IoT) devices opens up vast possibilities for novel applications, but simultaneously also allows spying on, and collecting data from, unsuspecting users to a previously unseen…
Modern x86 processors support an AVX instruction set to boost performance. However, this extension may cause security issues. We discovered that there are vulnerable properties in implementing masked load/store instructions. Based on this,…
Machine learning models are critically susceptible to evasion attacks from adversarial examples. Generally, adversarial examples, modified inputs deceptively similar to the original input, are constructed under whitebox settings by…
The drive to create thinner, lighter, and more energy efficient devices has resulted in modern SoCs being forced to balance a delicate tradeoff between power consumption, heat dissipation, and execution speed (i.e., frequency). While…
Cloud computing is a convenient model for processing data remotely. However, users must trust their cloud provider with the confidentiality and integrity of the stored and processed data. To increase the protection of virtual machines, AMD…
In most PUF-based authentication schemes, a central server is usually engaged to verify the response of the device's PUF to challenge bit-streams. However, the server availability may be intermittent in practice. To tackle such an issue,…
Emerging applications of control, estimation, and machine learning, ranging from target tracking to decentralized model fitting, pose resource constraints that limit which of the available sensors, actuators, or data can be simultaneously…
Rowhammer attacks have emerged as a significant threat to modern DRAM-based memory systems, leveraging frequent memory accesses to induce bit flips in adjacent memory cells. This work-in-progress paper presents an adaptive, many-sided…