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CyLab

Societal Computing

RS-Del: Edit distance robustness certificates for sequence classifiers via randomized deletion

Widespread Third-Party Tracking On Hospital Websites Poses Privacy Risks For Patients And Legal Liability For Hospitals

Deceiving ML-Based Friend-or-Foe

Prevalence of third-party tracking on abortion clinic web pages

“Did you know this camera tracks your mood?”: Understanding Privacy Expectations and Preferences in the Age of Video Analytics

Lujo Bauer is a Professor of Electrical and Computer Engineering, and of Computer Science, at Carnegie Mellon University. He received his B.S. in Computer Science from Yale University in 1997 and his Ph.D., also in Computer Science, from Princeton University in 2003. Dr. Bauer is a member of CyLab, Carnegie Mellon's computer security and privacy institute, and serves as the director of CyLab's Cyber Autonomy Research Center.

Dr. Bauer's research examines many aspects of computer security and privacy, including developing high-assurance access-control systems, building systems in which usability and security co-exist, and designing practical tools for identifying software vulnerabilities. Bauer and fellow CMU researchers Lujo Bau and Larry Pileggi are calling on the research and policy communities to develop more comprehensive and accurate grid evaluation frameworks and datasets, and for updating threat models and grid resiliency requirements to match cyber attackers realistic capabilities. His other recent work focuses on developing tools and guidance to help users stay safer online and on examining how advances in machine learning can (or might not) lead to a more secure future.

Dr. Bauer served as the program chair for the flagship computer security conferences of the IEEE (S&P 2015) and the Internet Society (NDSS 2014) and is an associate editor of ACM Transactions on Privacy and Security.

IoT Security and Privacy

Network Security

Cybersecurity and Privacy

Internet of Things (IoT)

AI and ML for Security

System Security

Data/Network Science Systems

Cyberphysical Systems (CPS)

Carnegie Mellon University Profile

Personal Website

Google Scholar Citations

CMU Experts at the Intersection of Energy and Innovation

Researchers develop adversarial training methods to improve machine learning-based malware detection software

Q&A with Lujo Bauer on how the pandemic is affecting individuals' privacy and security

Learning to Attack the Cyberattackers Can’t Happen Fast Enough

New Technology Cracks 'Strong' Passwords -- What You Need To Know

Professor, Electrical and Computer Engineering

The data you give to Facebook or Fitbit might be less secure than you think, but Associate Professor of Electrical and Computer Engineering Lujo Bauer wants to give you more control over your information by mathematically proving privacy systems work.

Lujo Bauer: Helping Users Manage Online Data

Intelligent devices that we are bringing into our home may call in to question what kind of privacy we are giving up to make life more convenient and personalized. In this podcast, Carnegie Mellon University CyLab Associate Professor Lujo Bauer discusses computer security and privacy, and what we can expect in the ever-growing world of Artificial Intelligence

Lujo Bauer on the future of AI

Invited Researcher: Dr. Lujo Bauer, Associate Professor—CMU Institute for Software Research

CyLab presents Lujo Bauer,  Assistant Research Professor at Carnegie Mellon University, as part of the weekly seminar series.

Text-based passwords remain the dominant authentication method in computer systems, despite signiﬁcant advancement in attackers' capabilities to perform password cracking. In response to this threat, password composition policies have grown increasingly complex. In this talk, Bauer will first review our earlier results on the security and usability of different password-composition policies, and of metrics for quantifying password security.

He will then discuss two more recent studies of passwords. In one, we take a look at passphrases, which have been suggested as secure and usable for decades. Through empirical investigation, we seek to determine whether passphrases are or can be the panacea for user authentication. (Spoiler: probably not.) In the second study, we focus on password-strength meters. These visual indicators of password strength are commonly used in the hope of nudging users to create better passwords, but their effects on the security and usability of passwords have not been well understood. Our work seeks to empirically determine these effects, as well as to shed light on which elements of password-meter design are important.

Lujo Bauer - Helping Users Create Better Passwords

This is a re-recording of the conference presentation talk from Trevor Kann at CODASPY 2024 in Porto, Portugal. Feel free to email me or post comments with questions/discussion about the paper. 

You can cite the full publication here:
Trevor Kann, Lujo Bauer, and Robert K. Cunningham. 2024. CoCoT: Collaborative Contact Tracing. In Proceedings of the Fourteenth ACM Conference on Data and Application Security and Privacy (CODASPY '24). Association for Computing Machinery, New York, NY, USA, 175–186. 

A longer version is available here as a technical report:
Kann, Trevor; cunningham, Robert; Bauer, Ljudevit (2024). CoCoT: Collaborative Contact Tracing (Extended Version). Carnegie Mellon University.

As this is a CMU account I unfortunately cannot post links to these papers.

CoCoT: Collaborative Contact Tracing (CODASPY'24) by Trevor Kann, Lujo Bauer, &amp; Robert K. Cunningham

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