7.1k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- SupélecFR486 papers
- Shandong University of Political Science and LawCN485 papers
- Dalle Molle Institute for Artificial Intelligence ResearchCH65 papers
- New York UniversityUS52 papers
- Università della Svizzera italianaCH21 papers
- Google (United States)US16 papers
- Princeton UniversityUS15 papers
- Courant Institute of Mathematical SciencesUS13 papers
- Politecnico di TorinoIT12 papers
- Meta (Israel)IL11 papers
- Massachusetts Institute of TechnologyUS10 papers
- ETH ZurichCH9 papers
19 papers · 1 filter
Cyber Security aboard Micro Aerial Vehicles: An OpenTitan-based Visual Communication Use Case
Maicol Ciani, Stefano Bonato, Rafail Psiakis +6
Autonomous Micro Aerial Vehicles (MAVs), with a form factor of 10cm in diameter, are an emerging technology thanks to the broad applicability enabled by their onboard intelligence.…
CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale
Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi +2
The privacy concerns of providing deep learning inference as a service have underscored the need for private inference (PI) protocols that protect users' data and the service provi…
Combating Informational Denial-of-Service (IDoS) Attacks: Modeling and Mitigation of Attentional Human Vulnerability
Linan Huang, Quanyan Zhu
This work proposes a new class of proactive attacks called the Informational Denial-of-Service (IDoS) attacks that exploit the attentional human vulnerability. By generating a larg…
Coin Flipping of \emph{Any} Constant Bias Implies One-Way Functions
Itay Berman, Iftach Haitner, Aris Tentes
We show that the existence of a coin-flipping protocol safe against \emph{any} non-trivial constant bias (\eg ) implies the existence of one-way functions. This improves upon…
Exploring the Effect of Resolution on the Usability of Locimetric Authentication
Antonios Saravanos, Dongnanzi Zheng, Stavros Zervoudakis +1
Locimetric authentication is a form of graphical authentication in which users validate their identity by selecting predetermined points on a predetermined image. Its primary advan…
Explainability Matters: Backdoor Attacks on Medical Imaging
Munachiso Nwadike, Takumi Miyawaki, Esha Sarkar +2
Deep neural networks have been shown to be vulnerable to backdoor attacks, which could be easily introduced to the training set prior to model training. Recent work has focused on…
MAD-VAE: Manifold Awareness Defense Variational Autoencoder
Frederick Morlock, Dingsu Wang
Although deep generative models such as Defense-GAN and Defense-VAE have made significant progress in terms of adversarial defenses of image classification neural networks, several…
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning
Xi Chen, David Simchi-Levi, Yining Wang
The prevalence of e-commerce has made detailed customers' personal information readily accessible to retailers, and this information has been widely used in pricing decisions. When…
Privacy-Preserving Multi-Operator Contact Tracing for Early Detection of Covid19 Contagions
Davide Andreoletti, Omran Ayoub, Silvia Giordano +2
The outbreak of coronavirus disease 2019 (covid-19) is imposing a severe worldwide lock-down. Contact tracing based on smartphones' applications (apps) has emerged as a possible so…
The Tools and Tactics Used in Intimate Partner Surveillance: An Analysis of Online Infidelity Forums
Emily Tseng, Rosanna Bellini, Nora McDonald +5
Abusers increasingly use spyware apps, account compromise, and social engineering to surveil their intimate partners, causing substantial harms that can culminate in violence. This…
Stabilizing Congestion in Decentralized Record-Keepers
Assimakis Kattis, Fabian Trottner
We argue that recent developments in proof-of-work consensus mechanisms can be used in accordance with advancements in formal verification techniques to build a distributed payment…
Security of Cloud FPGAs: A Survey
Chenglu Jin, Vasudev Gohil, Ramesh Karri +1
Integrating Field Programmable Gate Arrays (FPGAs) with cloud computing instances is a rapidly emerging trend on commercial cloud computing platforms such as Amazon Web Services (A…
Differentially Private Collaborative Intrusion Detection Systems For VANETs
Tao Zhang, Quanyan Zhu
Vehicular ad hoc network (VANET) is an enabling technology in modern transportation systems for providing safety and valuable information, and yet vulnerable to a number of attacks…
Security of Distributed Machine Learning: A Game-Theoretic Approach to Design Secure DSVM
Rui Zhang, Quanyan Zhu
Distributed machine learning algorithms play a significant role in processing massive data sets over large networks. However, the increasing reliance on machine learning on informa…
Deep Learning Based Android Malware Detection Framework
Soumya Sourav, Devashish Khulbe, Naman Kapoor
With the development in the field of smartphones and ever growing base of Internet, various softwares are left prone to many malicious activities like pharming, phishing, ransomwar…
RIoTS: Risk Analysis of IoT Supply Chain Threats
Timothy Kieras, Muhammad Junaid Farooq, Quanyan Zhu
Securing the supply chain of information and communications technology (ICT) has recently emerged as a critical concern for national security and integrity. With the proliferation…
FlipIn: A Game-Theoretic Cyber Insurance Framework for Incentive-Compatible Cyber Risk Management of Internet of Things
Rui Zhang, Quanyan Zhu
Internet of Things (IoT) is highly vulnerable to emerging Advanced Persistent Threats (APTs) that are often operated by well-resourced adversaries. Achieving perfect security for I…
An Interposer-Based Root of Trust: Seize the Opportunity for Secure System-Level Integration of Untrusted Chiplets
Mohammed Nabeel, Mohammed Ashraf, Satwik Patnaik +3
Leveraging 2.5D interposer technology, we advocate the integration of untrusted commodity components/chiplets with physically separate, entrusted logic components. Such organizatio…
Stopping time signatures for some algorithms in cryptography
Percy Deift, Stephen D. Miller, Thomas Trogdon
We consider the normalized distribution of the overall running times of some cryptographic algorithms, and what information they reveal about the algorithms. Recent work of Deift,…