Z. Berkay Celik

336 Westgate Building
University Park, PA 16802, USA

Curriculum Vitae
Google Scholar

About Me

I am a research assistant in Department of Electrical Engineering and Computer Science at the Pennsylvania State University working with Prof. Patrick McDaniel and a member of the Systems and Internet Infrastructure Security Laboratory (SIIS). During my Msc. studies, I worked with Prof. George Kesidis and Prof. David J. Miller. My research was on machine learning systems and network security. Previously I have worked at VMware evaluating the security of VMware source code, Vencore Labs building machine learning systems under privileged information, and Istanbul Technical University doing research on feature engineering for malware detection.

Generally, I am interested in developing secure systems through program analysis and machine learning. My recent work seeks to improve security, safety and privacy guarantees in commodity IoT.


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Publications (Selected)

Soteria: Automated IoT Safety and Security Analysis
Z. Berkay Celik, Patrick McDaniel and Gang Tan
Proceedings of the USENIX Annual Technical Conference (USENIX ATC), 2018
Acceptance Rate: 19%

Sensitive Information Tracking in Commodity IoT
Z. Berkay Celik, Leonardo Babun, Amit K. Sikder, Hidayet Aksu, Gang Tan, Patrick McDaniel and Selcuk Uluagac
Proceedings of the USENIX Security Symposium (USENIX Security), 2018
Acceptance Rate: 18%

Detection under Privileged Information
Z. Berkay Celik, Patrick McDaniel, Rauf Izmailov, Ryan Sheatsley, Nicolas Papernot, Ryan Sheatsley, Raquel Alvarez and Ananthram Swami
Proceedings of the Asia Conference on Computer and Communications Security (ASIACCS), 2018
Acceptance Rate: 20%

Malware Modeling and Experimentation through Parameterized Behavior
Z. Berkay Celik, Patrick McDaniel, and Thomas Bowen
In Journal of Defense Modeling and Simulation (JDMS), 2018

Extending Detection with Privileged Information via Generalized Distillation
Z. Berkay Celik and Patrick McDaniel
IEEE Workshop on Deep Learning and Security (colocated with IEEE S&P), 2018
Acceptance Rate: 27%

Mission-oriented Security Model, Incorporating Security Risk, Cost and Payout
Sayed Saghaian, Tom La Porta, Trent Jaeger, Z. Berkay Celik, Patrick McDaniel
Proceedings of the Security and Privacy in Communication Networks (SecureComm), 2018
[Best Paper Award]

Patient-Driven Privacy Control through Generalized Distillation
Z. Berkay Celik, David Lopez-Paz, and Patrick McDaniel
Proceedings of the IEEE Privacy-aware Computing (PAC), 2017

Practical Black-Box Attacks against Machine Learning
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z. Berkay Celik, and Ananthram Swami
Proceedings of the Asia Conference on Computer, and Communications Security (ASIACCS), 2017
Acceptance Rate: 20%

Achieving Secure and Differentially Private Computations in Multiparty Settings
Abbas Acar, Z. Berkay Celik, Hidayet Aksu, A. Selcuk Uluagac, and Patrick McDaniel
Proceedings of the IEEE Privacy-aware Computing (PAC), 2017

Machine Learning in Adversarial Settings
Patrick McDaniel, Nicolas Papernot, and Z. Berkay Celik
IEEE Security & Privacy Magazine (May/June), 2016

The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot, Patrick McDaniel, Somesh Jha, Matt Fredrikson, Z. Berkay Celik, and Ananthram Swami
Proceedings of the European Symposium on Security and Privacy (Euro S&P), 2016
Acceptance Rate: 17.3%