Research
Machine Learning
Machine Learning
For Security and Privacy in Machine Learning, we consider the privacy of datasets and the robustness of classifiers against maliciously crafted input. We also consider Machine Learning as a tool for Security and Privacy, for example to detect vulnerabilities or malicious behaviour.
PEOPLE
PUBLICATIONS
BioNetExplorer - Architecture-Space Exploration of Biosignal Processing Deep Neural Networks for Wearables. Bharath Srinivas Prabakaran, Asima Akhtar, Semeen Rehman, Osman Hasan, Muhammad Shafique (IEEE Internet Things J., 2021) ↗
Digital Transformation for Sustainable Development Goals (SDGs) - A Security, Safety and Privacy Perspective on AI. Andreas Holzinger, Edgar R. Weippl, A Min Tjoa, Peter Kieseberg (CD-MAKE, 2021) ↗
MLComp - A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences. Alessio Colucci, Dávid Juhász, Martin Mosbeck, Alberto Marchisio, Semeen Rehman, Manfred Kreutzer, Günther Nadbath, Axel Jantsch, Muhammad Shafique (DATE, 2021) ↗
FaDec - A Fast Decision-based Attack for Adversarial Machine Learning. Faiq Khalid, Hassan Ali, Muhammad Abdullah Hanif, Semeen Rehman, Rehan Ahmed, Muhammad Shafique (IJCNN, 2020) ↗
Guest Editorial Leveraging Machine Learning in SDN/NFV-Based Networks. David S. L. Wei, Kaiping Xue, Roberto Bruschi, Stefan Schmid (IEEE J. Sel. Areas Commun., 2020) ↗
Interpretability and Refinement of Clustering. Félix Iglesias Vázquez, Tanja Zseby, Arthur Zimek (DSAA, 2020) ↗
Outside the Box - Abstraction-Based Monitoring of Neural Networks. Thomas A. Henzinger, Anna Lukina, Christian Schilling (ECAI, 2020) ↗
SSCNets - Robustifying DNNs using Secure Selective Convolutional Filters. Hassan Ali, Faiq Khalid, Hammad Tariq, Muhammad Abdullah Hanif, Rehan Ahmed, Semeen Rehman (IEEE Des. Test, 2020) ↗
An Improved Quick Artificial Bee Colony Algorithm for Portfolio Selection. Dit Suthiwong, Maleerat Sodanil, Gerald Quirchmayr (Int. J. Comput. Intell. Appl., 2019) ↗
Approximate Multi-Accelerator Tiled Architecture for Energy-Efficient Motion Estimation. Bharath Srinivas Prabakaran, Walaa El-Harouni, Semeen Rehman, Muhammad Shafique (Approximate Circuits, 2019) ↗
Building Robust Machine Learning Systems - Current Progress, Research Challenges, and Opportunities. Jeff Jun Zhang, Kang Liu, Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Theocharis Theocharides, Alessandro Artussi, Muhammad Shafique, Siddharth Garg (DAC, 2019) ↗
DeepMPLS - Fast Analysis of MPLS Configurations Using Deep Learning. Fabien Geyer, Stefan Schmid (Networking, 2019) ↗
FAdeML - Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning. Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Junaid Qadir, Muhammad Shafique (DATE, 2019) ↗
Hardware-Software Approximations for Deep Neural Networks. Muhammad Abdullah Hanif, Muhammad Usama Javed, Rehan Hafiz, Semeen Rehman, Muhammad Shafique (Approximate Circuits, 2019) ↗
Heterogeneous Approximate Multipliers - Architectures and Design Methodologies. Semeen Rehman, Bharath Srinivas Prabakaran, Walaa El-Harouni, Muhammad Shafique, Jörg Henkel (Approximate Circuits, 2019) ↗
Ismael - Using Machine Learning to Predict Acceptance of Virtual Clusters in Data Centers. Johannes Zerwas, Patrick Kalmbach, Stefan Schmid, Andreas Blenk (IEEE Trans. Netw. Serv. Manag., 2019) ↗
QuSecNets - Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks. Faiq Khalid, Hassan Ali, Hammad Tariq, Muhammad Abdullah Hanif, Semeen Rehman, Rehan Ahmed, Muhammad Shafique (IOLTS, 2019) ↗
Rax - Deep Reinforcement Learning for Congestion Control. Maximilian Bachl, Tanja Zseby, Joachim Fabini (ICC, 2019) ↗
Strategy Representation by Decision Trees with Linear Classifiers. Pranav Ashok, Tomás Brázdil, Krishnendu Chatterjee, Jan Kretínský, Christoph H. Lampert, Viktor Toman (QEST, 2019) ↗
Towards Data Anonymization in Data Mining via Meta-heuristic Approaches. Fatemeh Amiri, Gerald Quirchmayr, Peter Kieseberg, Edgar R. Weippl, Alessio Bertone (DPM/CBT@ESORICS, 2019) ↗
TrISec - Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks. Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Rehan Ahmed, Muhammad Shafique (IOLTS, 2019) ↗
