Secure authentication from facial attributeswith no privacy loss. - Orr Dunkelman; Margarita Osadchy; Mahmood Sharif (CCS, 2013)

Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition. - Mahmood Sharif; Sruti Bhagavatula; Lujo Bauer; Michael K. Reiter (CCS, 2016)

(Do Not) Track Me Sometimes: Users' Contextual Preferences for Web Tracking. - William Melicher; Mahmood Sharif; Joshua Tan; Lujo Bauer; Mihai Christodorescu; Pedro Giovanni Leon (Proc. Priv. Enhancing Technol., 2016)

Self-Confidence Trumps Knowledge: A Cross-Cultural Study of Security Behavior. - Yukiko Sawaya; Mahmood Sharif; Nicolas Christin; Ayumu Kubota; Akihiro Nakarai; Akira Yamada 001 (CHI, 2017)

Topics of Controversy: An Empirical Analysis of Web Censorship Lists. - Zachary Weinberg; Mahmood Sharif; Janos Szurdi; Nicolas Christin (Proc. Priv. Enhancing Technol., 2017)

Predicting Impending Exposure to Malicious Content from User Behavior. - Mahmood Sharif; Jumpei Urakawa; Nicolas Christin; Ayumu Kubota; Akira Yamada 001 (CCS, 2018)

On the Suitability of Lp-Norms for Creating and Preventing Adversarial Examples. - Mahmood Sharif; Lujo Bauer; Michael K. Reiter (CVPR Workshops, 2018)

Riding out DOMsday: Towards Detecting and Preventing DOM Cross-Site Scripting. - William Melicher; Anupam Das 001; Mahmood Sharif; Lujo Bauer; Limin Jia 001 (NDSS, 2018)

Comparing Hypothetical and Realistic Privacy Valuations. - Joshua Tan; Mahmood Sharif; Sruti Bhagavatula; Matthias Beckerle; Michelle L. Mazurek; Lujo Bauer (WPES@CCS, 2018)

Adversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition. - Mahmood Sharif; Sruti Bhagavatula; Lujo Bauer; Michael K. Reiter (CoRR, 2018)

On the Suitability of Lp-norms for Creating and Preventing Adversarial Examples. - Mahmood Sharif; Lujo Bauer; Michael K. Reiter (CoRR, 2018)

A Field Study of Computer-Security Perceptions Using Anti-Virus Customer-Support Chats. - Mahmood Sharif; Kevin A. Roundy; Matteo Dell'Amico; Christopher Gates 002; Daniel Kats; Lujo Bauer; Nicolas Christin (CHI, 2019)

n-ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers. - Mahmood Sharif; Lujo Bauer; Michael K. Reiter (CoRR, 2019)

Optimization-Guided Binary Diversification to Mislead Neural Networks for Malware Detection. - Mahmood Sharif; Keane Lucas; Lujo Bauer; Michael K. Reiter; Saurabh Shintre (CoRR, 2019)

A General Framework for Adversarial Examples with Objectives. - Mahmood Sharif; Sruti Bhagavatula; Lujo Bauer; Michael K. Reiter (ACM Trans. Priv. Secur., 2019)

How Risky Are Real Users' IFTTT Applets? - Camille Cobb; Milijana Surbatovich; Anna Kawakami; Mahmood Sharif; Lujo Bauer; Anupam Das 001; Limin Jia 001 (SOUPS @ USENIX Security Symposium, 2020)

Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes. - Keane Lucas; Mahmood Sharif; Lujo Bauer; Michael K. Reiter; Saurabh Shintre (AsiaCCS, 2021)

"I Have No Idea What a Social Bot Is": On Users' Perceptions of Social Bots and Ability to Detect Them. - Daniel Kats; Mahmood Sharif (HAI, 2022)

Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks. - Weiran Lin; Keane Lucas; Lujo Bauer; Michael K. Reiter; Mahmood Sharif (ICML, 2022)

Scalable verification of GNN-based job schedulers. - Haoze Wu 001; Clark W. Barrett; Mahmood Sharif; Nina Narodytska; Gagandeep Singh 001 (Proc. ACM Program. Lang., 2022)

Artifact for Paper Scalable Verification of GNN-Based Job Schedulers. - Haoze Wu 001; Clark W. Barrett; Mahmood Sharif; Nina Narodytska; Gagandeep Singh 001 (Zenodo, 2022)

Accessorize in the Dark: A Security Analysis of Near-Infrared Face Recognition. - Amit Cohen; Mahmood Sharif (ESORICS (3), 2023)

Adversarial Training for Raw-Binary Malware Classifiers. - Keane Lucas; Samruddhi Pai; Weiran Lin; Lujo Bauer; Michael K. Reiter; Mahmood Sharif (USENIX Security Symposium, 2023)

Harmful Bias: A General Label-Leakage Attack on Federated Learning from Bias Gradients. - Nadav Gat; Mahmood Sharif (AISec@CCS, 2024)

The Ultimate Combo: Boosting Adversarial Example Transferability by Composing Data Augmentations. - Zebin Yun; Achi-Or Weingarten; Eyal Ronen; Mahmood Sharif (AISec@CCS, 2024)

Training Robust ML-based Raw-Binary Malware Detectors in Hours, not Months. - Keane Lucas; Weiran Lin; Lujo Bauer; Michael K. Reiter; Mahmood Sharif (CCS, 2024)

Privacy-Preserving Collaborative Genomic Research: A Real-Life Deployment and Vision. - Zahra Rahmani; Nahal Shahini; Nadav Gat; Zebin Yun; Yuzhou Jiang; Ofir Farchy; Yaniv Harel; Vipin Chaudhary; Erman Ayday; Mahmood Sharif (HealthSec@CCS, 2024)

Group-based Robustness: A General Framework for Customized Robustness in the Real World. - Weiran Lin; Keane Lucas; Neo Eyal; Lujo Bauer; Michael K. Reiter; Mahmood Sharif (NDSS, 2024)

CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers. - Matan Ben-Tov; Daniel Deutch; Nave Frost; Mahmood Sharif (SP, 2024)

DrSec: Flexible Distributed Representations for Efficient Endpoint Security. - Mahmood Sharif; Pubali Datta; Andy Riddle; Kim Westfall; Adam Bates 001; Vijay Ganti; Matthew Lentz; David Ott (SP, 2024)

A High Coverage Cybersecurity Scale Predictive of User Behavior. - Yukiko Sawaya; Sarah Lu; Takamasa Isohara; Mahmood Sharif (USENIX Security Symposium, 2024)

Adversarial Robustness Through Artifact Design. - Tsufit Shua; Mahmood Sharif (CoRR, 2024)

Impactful Bit-Flip Search on Full-precision Models. - Nadav Benedek; Matan Levy; Mahmood Sharif (CoRR, 2024)

GASLITEing the Retrieval: Exploring Vulnerabilities in Dense Embedding-based Search. - Matan Ben-Tov; Mahmood Sharif (CoRR, 2024)

Safety Perceptions of Generative AI Conversational Agents: Uncovering Perceptual Differences in Trust, Risk, and Fairness. - Jan Tolsdorf; Alan F. Luo; Monica Kodwani; Junho Eum; Mahmood Sharif; Michelle L. Mazurek; Adam J. Aviv (SOUPS, 2025)

Universal Jailbreak Suffixes Are Strong Attention Hijackers. - Matan Ben-Tov; Mor Geva; Mahmood Sharif (CoRR, 2025)