Privacy and Security

Our research in privacy and security takes an interdisciplinary approach to detecting and removing threats of cyberattacks, enhancing predictability and trust, and understanding online privacy and information manipulation. Our research methodology is rooted in several disciplines, including computer science, applied mathematics, cognitive science, control theory, economics, social sciences, and public policy. Specifically, we conduct research to understand issues and seize opportunities in systems and software security, usability considerations in privacy and security, economics of information security, and data-driven security, among many others.

Research-Active Faculty
Photo of Nicklaus A. Giacobe

Assistant Teaching Professor

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Photo of Hong Hu

Assistant Professor

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Photo of Dongwon Lee

Professor

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Photo of Peng Liu

Raymond G. Tronzo, MD Professor of Cybersecurity

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Photo of Linhai Song

Assistant Professor

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Photo of Anna Squicciarini

Associate Professor

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Photo of Ting Wang

Assistant Professor

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Photo of Dinghao Wu

Professor

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Photo of Xinyu Xing

Assistant Professor

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Photo of Aiping Xiong

Assistant Professor

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Recent News

Women and lower-education users more likely to tweet personal information

July 7, 2021

When it comes to what users share on Twitter, women and users who never attended college voluntarily disclose more personal information than users from other socioeconomic and demographic backgrounds — potentially making these populations more susceptible to online privacy threats, according to a recent study led by the Penn State College of Inf

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$1.2 million NSF grant to create search engine for online privacy research

June 23, 2021

A $1.2 million National Science Foundation (NSF) grant will help researchers build a search engine and create other resources for scientists who need to scour billions of online documents to improve online privacy.

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Clickbait headlines might not lure readers as much, may confuse AI

June 18, 2021

A Penn State team of researchers found that clickbait often did not perform any better and, in some cases, performed worse than traditional headlines. They also found that artificial intelligence systems designed to spot clickbait struggled with the task.

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Researchers test detection methods for AI-generated content

February 5, 2021

In an effort to combat malicious use of artificial intelligence text generators—for example, an adversary generating fake news to share on social media—researchers at the College of Information Sciences and Technology analyzed eight different state-of-the-art natural language generators to identify whether each had a distinct writing style that

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Office of Research

E339 Westgate Building
University Park, PA 16802

researchadmin@ist.psu.edu
(814) 863-6801