József SÁNDOR
PhD Student at BME
Email: jozsef.sandor@crysys.hu
Location: Budapest, Hungary
Short Bio
József Sándor was born in 2000 in Székelyudvarhely, Romania. He earned both his B.Sc. and M.Sc. degrees in Computer Engineering from the Budapest University of Technology and Economics (BME). During his studies, he actively participated in research conducted at the Laboratory of Cryptography and System Security (CrySyS Lab) under the supervision of Dr. Levente Buttyán. His research focused on IoT security, particularly in the area of IoT malware detection. In the final semester of his M.Sc. program, he participated in the Erasmus+ program at the Technical University of Munich (TUM), while concurrently conducting research at Fraunhofer AISEC. His focus was on the side-channel power analysis of AES implementations. After a brief detour in the form of a summer internship at TU Graz, he began his PhD studies at BME in 2024.
Research Interests
- IoT Security
- System Security
- Machine Learning
Publications
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PATRIoTA: A Similarity-based IoT Malware Detection Method Robust Against Adversarial Samples
In Proceedings of the IEEE Symposium on Intelligent Edge Computing and Communications (iEDGE), July 7, Chicago, USA.
Authors: József Sándor, Roland Nagy, and Levente Buttyán
Year: 2023
Link: https://doi.org/10.1109/EDGE60047.2023.00057 -
Increasing the Robustness of a Machine Learning-based IoT Malware Detection Method with Adversarial Training
In Proceedings of the ACM Workshop on Wireless Security and Machine Learning (WiseML), June 1, Guildford, UK.
Authors: József Sándor, Roland Nagy, and Levente Buttyán
Year: 2023
Link: https://doi.org/10.1145/3586209.3591401 -
A New Method for Increasing the Robustness of Similarity-based IoT Malware Detection
At Student Scientific Conference at BME, Budapest, Hungary.
Author: József Sándor
Year: 2023
Link: https://tdk.bme.hu/VIK/beagy2/Hasonlosagalapu-IoT-malwaredetekcios -
Robustness Against Evasion of Similarity-based IoT Malware Detection Methods
At Student Scientific Conference at BME, Budapest, Hungary.
Author: József Sándor
Year: 2022
Link: https://tdk.bme.hu/VIK/beagy1/Robusztussag-vizsgalat-a-hasonlosagalapu-IoT
Education
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MSc in Computer Engineering
School: Budapest University of Technology and Economics (BME)
Overall diploma classification: Excellent with highest honours (4.85/5.0)
Thesis: Improving the robustness of similarity-based IoT malware detection methods against adversarial samples
Supervisor: Dr. Levente Buttyán
Duration: February 2022 - January 2024
Erasmus+: Technical University of Munich (2023/24 winter semester)
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BSc in Computer Engineering
School: Budapest University of Technology and Economics (BME)
Overall diploma classification: Excellent with highest honours (4.93/5.0)
Thesis: In-silico simulation framework in Julia environment (Hungarian)
Supervisor: Dr. Balázs István Benyó
Duration: September 2018 - January 2022
Work Experience
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IAIK TU Graz
Position: Research Assistant
Duration: June 2024 - August 2024
Location: Graz, Austria
Description: Linux kernel security measures.
Website: IAIK -
Fraunhofer AISEC
Position: Research Assistant
Duration: November 2023 - April 2024
Location: Munich, Germany
Description: Side-channel power analysis of masked AES implementations.
Website: Fraunhofer AISEC -
CrySyS Lab
Position: Research Assistant
Duration: May 2022 - September 2023
Location: Budapest, Hungary
Description: Increasing the robustness of similarity-based IoT malware detection methods.
Website: CrySyS Lab -
Kinepict Health Ltd
Position: Junior Software Developer
Duration: June 2021 - September 2022
Location: Budapest, Hungary
Description: Development and testing of the company's main product, which is a unique medical device software called Kinepict Medical Imaging Tool.
Website: Kinepict