Thomas Ristenpart

Associate Professor at Cornell Tech and the Department of Computer Science, Cornell University

LEARNING AND PRIVACY

Session Chair

Ghassan Karame, NEC Laboratories Europe

Xiaoning Li

Chief Security Architect, Director of Cloud Security Research at Alibaba Cloud
Building Hardware Assisted Trusted Computing Architecture on Public Cloud

HOSTING AND CONFINEMENT

Session Chair

Byoungyoung Lee, Seoul National University

David Kaplan

Security Architecture Fellow at AMD
Confidential Computing with AMD SEV-SNP

CRYPTO AND BEYOND

Session Chair

Anil Somayaji, Carleton University

Hany Farag

Engineering Manager at Google

BLITZ TALKS

Session Chair

Huibo Wang, Baidu Security

Long Live Randomization:

On Privacy-preserving Contact Tracing in Pandemic

New Techniques and Models, and Evaluation

Static Analysis Opportunities for Improving Agile and Moving Target Defenses

Systematization of MTD 1

Systematization of MTD 2

Web Privacy

Privacy policies

PETS in the wild

Secure Computation & Data Privacy

Medical Privacy

Marina Krotofil

Optimize Your Efforts: How to Tailor PhD Research to Real-World Needs – Industrial Perspective on Academic CPS/IoT Research

CPS&IoT Security

Session Chair

Charalambos Konstantinou

Real Case Studies and Demos

Session Chair

Avishai Wool

CPS&IoT Robustness

Session Chair

Sibin Mohan

Keynote: Introduction to Ant Secure Collaborative Intelligence (SCI) Lab

Keynote: Engineering Privacy-Preserving Machine Learning Protocols

Information Leakage by Model Weights on Federated Learning

Adversarial Detection on Graph Structured Data

Keynote: MC2: A Secure Collaborative Computation Platform

Keynote: Zero Knowledge Proofs for Machine Learning

CryptoSPN: Expanding PPML beyond Neural Networks

FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning

Neither Private Nor Fair: The Impact of Data Imbalance on Utility and Fairness in Differential Privacy

Secure Collaborative Training and Inference for XGBoost

HERB: Fast Privacy-Preserving Inference using Block Circulant Weight Matrices

Delphi: A Cryptographic Inference Service for Neural Networks

Bhavani Thuraisingham

UT Dallas

Raheem Beyah

Georgia Tech

Being a grad student - how to succeed and plant the seeds for your future career

Bhavani Thuraisingham (UT Dallas)

Indrakshi Ray (Colorado State University)

Yuan Tian (University of Virginia)

Celine Irvene (Georgia Tech)

Kevin Alejandro Roundy (NortonLifeLock Research Group)

A Latina in Tech

Cristina Cifuentes (Oracle Labs Australia)

Dr. R. Sekar

Stony Brook University

Information Flow: A Unified Basis for Vulnerability Mitigation, Malware Defense and Attack Scenario Reconstruction

Binary Manipulation & Disassembly

Dr. A. Loginov

GrammaTech

Concurrency & Exception Handling

Ryan Craven

ONR

Feature Isolation & Exploitation

Mark M. Tehranipoor

University of Florida
The Pursuit of Happiness: Establishing Hardware Root-of-Trust for Cyber Security

PUFS AND BEYOND

Session Chair

Stefan Katzenbeisser, University of Passau

SIDE CHANNELS: ATTACKS AND DEFENSES

Session Chair

Yuan Cao, Hohai University

Çetin Kaya Koç

UC Santa Barbara
Formidable Challenges in Hardware Implementations of Fully Homomorphic Encryption Functions for Applications in Machine Learning

FAULT ATTACKS AND CRYPTOGRAPHIC HARDWARE DESIGN

Session Chair

Tolga Arul, University of Passau

HARDWARE AND SYSTEM SECURITY

Session Chair

Marten van Dijk, CWI Amsterdam

David Oswald

University of Birmingham
Software and hardware vulnerabilities in Intel SGX

Regular Papers Session #1

Session Chair

Daniele Sgandurra

Ioannis Krontiris

Huawei Technologies
Enabling Trusted Digital Identities – From Connected Citizens to Connected Objects

Regular Papers Session #2

Session Chair

Thanassis Giannetsos

Sandrine Blazy

University of Rennes, France

From Verified Compilation to Secure Compilation: a Semantic Approach

Secure Multiparty and Oblivious Computation

Types for Gradual Security and Verification of Security Protocols

Jean Yang

Akita Software, USA
How APIs Are Both the Illness and the Cure

Program Synthesis and Blockchain

Salil Vadhan

OpenDP: A Community Effort to Build Trustworthy Differential Privacy Software

Private Reinforcement Learning with PAC and Regret Guarantees

Auditing Differentially Private Machine Learning: How Private is Private SGD?

Characterizing Private Clipped Gradient Descent on Convex Generalized Linear Problems

Private Query Release Assisted by Public Data

An Equivalence Between Private Classification and Online Prediction

Differentially Private Set Union

Christina Ilvento

Prof. Vitaly Shmatikov

How to Backdoor a Deep Learning Model

Adversarial Machine Learning

Malware Detection

Machine Learning for Security and Privacy