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Cyber Security in the Age of Large-Scale Adversaries

CASA Distinguished Lectures

In our CASA Distinguished Lectures, we welcome selected international and national scientists at the HGI. The lectures of these influential and pioneering guest speakers, usually lasting one hour, are always followed by a discussion with the participants. Our goal is to encourage discussions and open up new perspectives within the field of cybersecurity research.

Due to COVID-19, the lectures will be held online - and will, therefore, be accessible to people all over the world. You will find the access link to the events below the speakers' information.

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Topic: Building Secure Key Exchange Protocols From Passwords

Cyber Security in the Age of Large-Scale Adversaries

Topic: "Usable Verifiable Electronic Voting"

"On the Security of (UWB) Distance Measurement"

"Differentially Oblivious Protocols for Differential Privacy"

"Learning from the People: From Normative to Descriptive Solutions to Problems in Security, Privacy & Machine Learning"

"Who's Calling? Characterizing and Addressing Telephone Network Abuse"

"Intriguing Properties of Adversarial ML Attacks in the Problem Space"

"Property Driven Hardware Security"

"Extraction of Complex DNN Models: Real Threat or Boogeyman?"

"We Need A Discipline of Cyber Public Health"

Understanding and Mitigating Technology-Enabled Misinformation: Present and Future

tba.

Attacks on ECDSA with nonce leakage: recent progress and perspectives

"Learning the Language of Failure"

Wild Patterns: Ten Years after the Rise of Adversarial Machine Learning

On deck functions

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Security Testing Hard to Reach Code

Toward a Quantum-Safe Future

From hash-function security in a post-quantum world to SPHINCS+

Post-quantum crypto on embedded microcontrollers

Sorting integer arrays: security, speed, and verification

A human-centered approach to the secure application of cryptography

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Trapdoor Hash Functions and their Applications

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Transient Execution Attacks

Strong network anonymity with mixnets

Expressive, Robust and Accountable Machine Learning for Real-world Data

When Good Components Go Bad: Formally Secure Compilation Despite Dynamic Compromise

A User-Centric Approach to Securing the HTTPS Ecosystem