Related papers: Flexible In-NAND Cryptographic Processing for Secu…
Mobile computing devices have been used broadly to store, manage and process sensitive or even mission critical data. To protect confidentiality of data stored in mobile devices, major mobile operating systems use full disk encryption,…
Today, flash memory are strongly used in the embedded system domain. NAND flash memories are the building block of main secondary storage systems. Such memories present many benefits in terms of data density, I/O performance, shock…
We propose a new symmetric cryptographic scheme based on functional invariants defined over discrete oscillatory functions with hidden parameters. The scheme encodes a secret integer through a four-point algebraic identity preserved under…
We present a behavioral compact model of 3D NAND flash memory for integrated circuits and system-level applications. This model is easy to implement, computationally efficient, fast, accurate and effectively accounts for the different…
Distributed machine learning systems require strong privacy guarantees, verifiable compliance, and scalable deployment across heterogeneous and multi-cloud environments. This work introduces a cloud-native privacy-preserving architecture…
In this work, we propose a dual-port cell design to address the pass disturb in vertical NAND storage, which can pass signals through a dedicated and string-compatible pass gate. We demonstrate that: i) the pass disturb-free feature…
Ultra-fast \& low-power superconductor single-flux-quantum (SFQ)-based CNN systolic accelerators are built to enhance the CNN inference throughput. However, shift-register (SHIFT)-based scratchpad memory (SPM) arrays prevent a SFQ CNN…
Inverse design coupled with adjoint optimization is a powerful method to design on-chip nanophotonic devices with multi-wavelength and multi-mode optical functionalities. Although only two simulations are required in each iteration of this…
Modern data centers have grown beyond CPU nodes to provide domain-specific accelerators such as GPUs and FPGAs to their customers. From a security standpoint, cloud customers want to protect their data. They are willing to pay additional…
This study introduces a novel AI microcontroller optimized for cost-effective, battery-powered edge AI applications. Unlike traditional single bit/cell memory configurations, the proposed microcontroller integrates zero-standby power weight…
While there exist many isolation mechanisms that are available to cloud service providers, including virtual machines, containers, etc., the problem of side-channel increases in importance as a remaining security vulnerability, particularly…
The storage industry is moving toward emerging non-volatile memories (NVMs), including the spin-transfer torque magnetoresistive random-access memory (STT-MRAM) and the phase-change memory (PCM), owing to their high density and low-power…
Photonics is the platform of choice to build a modular, easy-to-network quantum computer operating at room temperature. However, no concrete architecture has been presented so far that exploits both the advantages of qubits encoded into…
Quantum computing is an emerging technology on the verge of reshaping industries, while simultaneously challenging existing cryptographic algorithms. FALCON, a recent standard quantum-resistant digital signature, presents a challenging…
Although serverless computing offers compelling cost and deployment simplicity advantages, a significant challenge remains in securely managing sensitive data as it flows through the network of ephemeral function executions in serverless…
Emerging Non-Volatile Memories (NVMs) are promising contenders for building future memory systems. On the other side, unlike DRAM systems, NVMs can retain data even after power loss and thus enlarge the attack surface. While data encryption…
We propose ZnG, a new GPU-SSD integrated architecture, which can maximize the memory capacity in a GPU and address performance penalties imposed by an SSD. Specifically, ZnG replaces all GPU internal DRAMs with an ultra-low-latency SSD to…
We propose NVLog, an NVM-based write-ahead log for disk file systems, designed to transparently harness the high performance of NVM within the legacy storage stack. NVLog provides on-demand byte-granularity sync absorption, reserving the…
This paper proposes an architecture that integrates neural networks (NNs) and hardware security modules using a single resistive random access memory (RRAM) crossbar. The proposed architecture enables using a single crossbar to implement…
Privacy-preserving inference of convolutional neural networks (CNNs) using homomorphic encryption has emerged as a promising approach for enabling secure machine learning in untrusted environments. In our previous work, we introduced a…