research
∙
09/19/2023
The Impact of Exposed Passwords on Honeyword Efficacy
Honeywords are decoy passwords that can be added to a credential databas...
share
research
∙
06/29/2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World
Machine-learning models are known to be vulnerable to evasion attacks th...
research
∙
04/11/2023
EESMR: Energy Efficient BFT-SMR for the masses
Modern Byzantine Fault-Tolerant State Machine Replication (BFT-SMR) solu...
research
∙
12/24/2022
Bernoulli honeywords
Decoy passwords, or “honeywords,” planted in a credential database can a...
research
∙
12/29/2021
Distance-Aware Private Set Intersection
Private set intersection (PSI) allows two mutually-untrusting parties to...
research
∙
12/28/2021
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks
Minimal adversarial perturbations added to inputs have been shown to be ...
research
∙
08/03/2021
Optimally Hiding Object Sizes with Constrained Padding
Among the most challenging traffic-analysis attacks to confound are thos...
research
∙
06/06/2021
Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games
A growing body of work in game theory extends the traditional Stackelber...
research
∙
08/07/2020
Role-Based Deception in Enterprise Networks
Historically, enterprise network reconnaissance is an active process, of...
research
∙
12/27/2019
TASE: Reducing latency of symbolic execution with transactional memory
We present the design and implementation of a tool called TASE that uses...
research
∙
12/23/2019
Detecting stuffing of a user's credentials at her own accounts
We propose a framework by which websites can coordinate to detect creden...
research
∙
12/19/2019
Optimization-Guided Binary Diversification to Mislead Neural Networks for Malware Detection
Motivated by the transformative impact of deep neural networks (DNNs) on...
research
∙
12/19/2019
n-ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers
This paper proposes a new defense called n-ML against adversarial exampl...
research
∙
10/18/2019
n-m-Variant Systems: Adversarial-Resistant Software Rejuvenation for Cloud-Based Web Applications
Web servers are a popular target for adversaries as they are publicly ac...
research
∙
05/01/2018
How to end password reuse on the web
We present a framework by which websites can coordinate to make it diffi...
research
∙
04/04/2018
SBFT: a Scalable Decentralized Trust Infrastructure for Blockchains
We present SBFT: a scalable decentralized trust infrastructure for Block...
research
∙
02/27/2018
On the Suitability of L_p-norms for Creating and Preventing Adversarial Examples
Much research effort has been devoted to better understanding adversaria...
research
∙
12/31/2017
Adversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition
In this paper we show that misclassification attacks against face-recogn...
research
∙
09/09/2016