research
∙
09/13/2023
ZKROWNN: Zero Knowledge Right of Ownership for Neural Networks
Training contemporary AI models requires investment in procuring learnin...
share
research
∙
08/04/2023
SABRE: Robust Bayesian Peer-to-Peer Federated Learning
We introduce SABRE, a novel framework for robust variational Bayesian pe...
research
∙
08/01/2023
Secure and Trustworthy Computing 2.0 Vision Statement
The Secure and Trustworthy Computing (SaTC) program within the National ...
research
∙
07/17/2023
G-Scan: Graph Neural Networks for Line-Level Vulnerability Identification in Smart Contracts
Due to the immutable and decentralized nature of Ethereum (ETH) platform...
research
∙
04/04/2023
NetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression
Video compression plays a significant role in IoT devices for the effici...
research
∙
01/18/2023
Tailor: Altering Skip Connections for Resource-Efficient Inference
Deep neural networks use skip connections to improve training convergenc...
research
∙
09/26/2022
FastStamp: Accelerating Neural Steganography and Digital Watermarking of Images on FPGAs
Steganography and digital watermarking are the tasks of hiding recoverab...
research
∙
09/21/2022
Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers
Text classification has become widely used in various natural language p...
research
∙
08/08/2022
PerD: Perturbation Sensitivity-based Neural Trojan Detection Framework on NLP Applications
Deep Neural Networks (DNNs) have been shown to be susceptible to Trojan ...
research
∙
08/03/2022
Abusing Commodity DRAMs in IoT Devices to Remotely Spy on Temperature
The ubiquity and pervasiveness of modern Internet of Things (IoT) device...
research
∙
06/24/2022
zPROBE: Zero Peek Robustness Checks for Federated Learning
Privacy-preserving federated learning allows multiple users to jointly t...
research
∙
06/09/2022
ReFace: Real-time Adversarial Attacks on Face Recognition Systems
Deep neural network based face recognition models have been shown to be ...
research
∙
04/20/2022
Adversarial Scratches: Deployable Attacks to CNN Classifiers
A growing body of work has shown that deep neural networks are susceptib...
research
∙
04/12/2022
AdaTest:Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection
This paper proposes AdaTest, a novel adaptive test pattern generation fr...
research
∙
04/08/2022
An Adaptive Black-box Backdoor Detection Method for Deep Neural Networks
With the surge of Machine Learning (ML), An emerging amount of intellige...
research
∙
04/05/2022
FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes
Deepfakes and manipulated media are becoming a prominent threat due to t...
research
∙
03/18/2022
Adversarial Attacks on Deep Learning-based Video Compression and Classification Systems
Video compression plays a crucial role in enabling video streaming and c...
research
∙
02/21/2022
Backdoor Defense in Federated Learning Using Differential Testing and Outlier Detection
The goal of federated learning (FL) is to train one global model by aggr...
research
∙
11/07/2021
Machine Learning-Assisted E-jet Printing of Organic Flexible Biosensors
Electrohydrodynamic-jet (e-jet) printing technique enables the high-reso...
research
∙
11/02/2021
HASHTAG: Hash Signatures for Online Detection of Fault-Injection Attacks on Deep Neural Networks
We propose HASHTAG, the first framework that enables high-accuracy detec...
research
∙
09/07/2021
Trojan Signatures in DNN Weights
Deep neural networks have been shown to be vulnerable to backdoor, or tr...
research
∙
04/23/2021
Unsupervised Information Obfuscation for Split Inference of Neural Networks
Splitting network computations between the edge device and a server enab...
research
∙
03/23/2021
ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning
Ethereum smart contracts are automated decentralized applications on the...
research
∙
03/04/2021
WaveGuard: Understanding and Mitigating Audio Adversarial Examples
There has been a recent surge in adversarial attacks on deep learning ba...
research
∙
02/15/2021
Cross-modal Adversarial Reprogramming
With the abundance of large-scale deep learning models, it has become po...
research
∙
02/03/2021
TAD: Trigger Approximation based Black-box Trojan Detection for AI
An emerging amount of intelligent applications have been developed with ...
research
∙
01/30/2021
Expressive Neural Voice Cloning
Voice cloning is the task of learning to synthesize the voice of an unse...
research
∙
12/07/2020
A Singular Value Perspective on Model Robustness
Convolutional Neural Networks (CNNs) have made significant progress on s...
research
∙
09/04/2020
CLEANN: Accelerated Trojan Shield for Embedded Neural Networks
We propose CLEANN, the first end-to-end framework that enables online mi...
research
∙
08/10/2020
Trustworthy AI Inference Systems: An Industry Research View
In this work, we provide an industry research view for approaching the d...
research
∙
04/08/2020
GeneCAI: Genetic Evolution for Acquiring Compact AI
In the contemporary big data realm, Deep Neural Networks (DNNs) are evol...
research
∙
02/16/2020
SynFi: Automatic Synthetic Fingerprint Generation
Authentication and identification methods based on human fingerprints ar...
research
∙
02/09/2020
FastWave: Accelerating Autoregressive Convolutional Neural Networks on FPGA
Autoregressive convolutional neural networks (CNNs) have been widely exp...
research
∙
12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
research
∙
12/07/2019
Principal Component Properties of Adversarial Samples
Deep Neural Networks for image classification have been found to be vuln...
research
∙
12/05/2019
Scratch that! An Evolution-based Adversarial Attack against Neural Networks
Recent research has shown that Deep Neural Networks (DNNs) for image cla...
research
∙
11/15/2019
ASCAI: Adaptive Sampling for acquiring Compact AI
This paper introduces ASCAI, a novel adaptive sampling methodology that ...
research
∙
06/28/2019
A Neural-based Program Decompiler
Reverse engineering of binary executables is a critical problem in the c...
research
∙
05/24/2019
Decentralized Bayesian Learning over Graphs
We propose a decentralized learning algorithm over a general social netw...
research
∙
05/09/2019
Universal Adversarial Perturbations for Speech Recognition Systems
In this work, we demonstrate the existence of universal adversarial audi...
research
∙
04/09/2019
SWNet: Small-World Neural Networks and Rapid Convergence
Training large and highly accurate deep learning (DL) models is computat...
research
∙
03/31/2019
BlackMarks: Blackbox Multibit Watermarking for Deep Neural Networks
Deep Neural Networks have created a paradigm shift in our ability to com...
research
∙
02/19/2019
XONN: XNOR-based Oblivious Deep Neural Network Inference
Advancements in deep learning enable cloud servers to provide inference-...
research
∙
02/08/2019
ARM2GC: Succinct Garbled Processor for Secure Computation
We present ARM2GC, a novel secure computation framework based on Yao's G...
research
∙
01/31/2019
Peer-to-peer Federated Learning on Graphs
We consider the problem of training a machine learning model over a netw...
research
∙
01/17/2019
CodeX: Bit-Flexible Encoding for Streaming-based FPGA Acceleration of DNNs
This paper proposes CodeX, an end-to-end framework that facilitates enco...
research
∙
11/08/2018
Performance Comparison of Contemporary DNN Watermarking Techniques
DNNs shall be considered as the intellectual property (IP) of the model ...
research
∙
09/06/2018
Adversarial Reprogramming of Sequence Classification Neural Networks
Adversarial Reprogramming has demonstrated success in utilizing pre-trai...
research
∙
06/15/2018
RAPIDNN: In-Memory Deep Neural Network Acceleration Framework
Deep neural networks (DNN) have demonstrated effectiveness for various a...
research
∙
05/21/2018
