Assistant professor Laboratory of Cryptography and Systems Security (CrySyS)
Department of Networked Systems and Services
Budapest University of Technology and Economics
e-mail: dpapp92@crysys39.hu (Please remove ALL the numbers!)
office: I.E. 429 (CrySyS Lab)
Short Bio
Dorottya Futóné Papp was born in 1992 in Budapest. She achieved her PhD in November 2021 at the Budapest Univeristy of Technology and Economics. She has been involved with the Laboratory of Cryptography and System Security (CrySyS Lab) since 2013.
research | publications | teaching | miscellaneous
2022
D. Papp, G. Ács, R. Nagy, L. ButtyánSIMBIoTA-ML: Light-weight, Machine Learning-based Malware Detection for Embedded IoT Devices
7th International Conference on Internet of Things, Big Data and Security (IoTBDS)
Online streaming, April 2022
Link to paper
Best Paper Award
2021
Nagy, R., Németh, K., D. Papp, L. ButtyánRootkit Detection on Embedded IoT Devices
Acta Cybernetica (2021) online-first paper pp. 1 - 32
Link to paper
Cs. Tamás, D. Papp, L. Buttyán
SIMBIoTA: Similarity-Based Malware Detection on IoT Devices
6th International Conference on Internet of Things, Big Data and Security (IoTBDS)
Online streaming, April 2021
Link to pdf
© SCITEPRESS
D. Papp, M. Zombor, L. Buttyán
TEE-based protection of cryptographickeys on embedded IoT devices
Annales Mathematicae et Informaticae 53 (2021) pp. 245 - 256
Link to pdf
2020
M. Juhász, D. Papp, L. ButtyánTowards Secure Remote Firmware Update on Embedded IoT Devices
12th Conference of PhD Students in Computer Science
Szeged, Hungary, June 2020
Link to pdf
M. Bak, D. Papp, Cs. Tamás, L. Buttyán
Clustering IoT Malware based on Binary Similarity
6th IEEE/IFIP Workshop on Security for Emerging Distributed Network Technologies (DISSECT)
Budapest, Hungary, April 2020
Link to pdf
© IEEE
2019
D. Papp, T. Tarrach, L. ButtyánTowards Detecting Trigger-based Behavior In Binaries: Uncovering the Correct Environment
International Conference on Software Engineering and Formal Methods (SEFM)
Oslo, Norway, September 2019
Link to pdf
© Springer
D. Papp, K. Tamás, L. Buttyán
IoT Hacking - A Primer
Infocommunications Journal, 2nd Issue in 2019.
Link to pdf
2017
D. Papp, L. Buttyán, Z. MaTowards Semi-automated Detection of Trigger-based Behavior for Software Security Assurance
ARES '17, Workshop on Software Assurance
Reggio Calabria, Italy, August-September 2017
Link to pdf
© ACM
2016
D. Papp, Z. Ma, L. ButtyánRoViM: Rotating Virtual Machines for Security and Fault-Tolerance
EMC2 Summit at CPS Week 2016
Vienna, Austria, April 2016
Link to pdf
© IEEE
2015
D. Papp, B. Kócsó, T. Holczer, L. Buttyán, B. BencsáthROSCO: Repository Of Signed COde
Virus Bulletin 2015
Prague, Czech Republic, September 2015
Link to pdf
D. Papp, Z. Ma, L. Buttyán
Embedded System Security: Threats, Vulnerabilities, and Attack Taxonomy
IEEE International Confenrence on Privacy, Security, and Trust (PST)
Izmir, Turkey, July 2015
Link to pdf, Scripts
© IEEE
PhD thesis
Improved security and protection from malware for embedded IoT devices
The field of embedded devices is changing rapidly. While these devices have originally been developed to perform specific tasks, they are now increasingly connected to the Internet, leading to the Internet of Things (IoT). Consequently, embedded devices are increasingly called embedded IoT devices. Internet connectivity enables new and innovative application areas, however, it is a new attack surface which need protection.
In this dissertation, we study the threat landscape of embedded IoT devices and proposed a new attack taxonomy to systematically identify and classify common attacks. We draw two conclusions from this study, namely, that malware is a significant threat in the case of embedded IoT devices and that the vulnerabilities of these devices form a diverse set. These conclusions motivate the following research.
- We study the possibility of clustering malware based on their binary similarity in order to reduce the workload of analysts.
- We also investigate a type of stealthy malware, which exhibits malicious behavior only when it receives specific inputs from its environment. Such malware samples are especially challenging to analyze because the analyst has no knowledge about the necessary inputs.
- Given the wide set of vulnerabilities in embedded IoT devices, we propose a new mode of operation, called RoViM, which allows devices to periodically cleanse themselves, restoring a compromise-free state.