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Prof. Dr. Martin Schramm

Professor

Head of Institute ProtectIT; Course Co-ordinator Bachelor Cyber Security;Member of Examination Board Further Education Centre

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0991/3615-578

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publications

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Lecture

Martin Schramm
Andreas Grzemba

The Beneﬁts of Combining Trusted Computing with Virtualization Techniques.

In: Applied Electronics International Conference

Pilsen, Tschechische Republik

2010 (2010)

Lecture

Martin Schramm
Andreas Grzemba

The Benefits of Combining Trusted Computing with Virtualization Techniques.

In: IEEE International Conference on Applied Electronics 2010

Pilsen, Tschechische Republik

08.-09.09.2010 (2010)

Lecture

Martin Schramm
Andreas Grzemba
et al.

Utilizing a State-of-the-art Trust Anchor in Order to Increase the Trustworthiness of Embedded Platforms.

In: Embedded World International Conference 2011

Nürnberg

2011 (2011)

Lecture

Martin Schramm
Andreas Grzemba

Trustworthy Building Blocks for a More Secure Embedded Computing Environment.

In: Applied Electronics International Conference

Pilsen, Tschechische Republik

2011 (2011)

Lecture

Karl Leidl
Martin Schramm
Andreas Grzemba

The Establishment of High Degrees of Trust in a Linux Environment.

In: Embedded World International Conference 2012

Nürnberg

28.02.-01.03.2012 (2012)

Lecture

Martin Schramm
Andreas Grzemba

Reconfigurable Trust for Embedded Computing Platforms.

In: IEEE Applied Electronics International Conference

Pilsen, Tschechische Republik

05.-06.09.2012 (2012)

Lecture

Martin Schramm
Andreas Grzemba

On the Implementation of a Lightweight Generic FPGA ECC Crypto-Core over GF(p).

In: IEEE Applied Electronics International Conference

Pilsen, Tschechische Republik

2013 (2013)

Lecture

Martin Schramm
Andreas Grzemba

On the Implementation of an Efficient Multiplier Logic for FPGA-based Cryptographic Applications.

In: IEEE Applied Electronics International Conference

Pilsen, Tschechische Republik

2013 (2013)

Lecture

Martin Schramm
Karl Leidl
Andreas Grzemba
N. Kuntze

Enhanced Embedded Device Security by Combining Hardware-Based Trust Mechanisms. Poster-Session.

In: ACM Conference on Computer and Communications Security

Berlin

04.-08.11.2013 (2013)

Lecture

Martin Schramm

Embedded Trusted Computing on ARM-based Systems.

In: Security Forum 2014

Hagenberg im Mühlkreis, Österreich

09.-10.04.2014 (2014)

Lecture

Martin Schramm
Andreas Grzemba

Trusted Computing Concepts for Resilient Embedded Networks. International Workshop on Engineering Cyber Security and Resilience.

In: 2014 ASE Bigdata/SocialCom/Cybersecurity Conference

Stanford University Stanford, CA, USA

Mai 2014 (2014)

Lecture

Martin Schramm

Resilience in Embedded Industrial Networks.

In: Trusted Computing Group Members Meeting 2014

Barcelona, Spanien

Juni 2014 (2014)

Contribution

Michael Heigl
Martin Schramm
Laurin Dörr
Andreas Grzemba

Embedded Plug-In Devices to Secure Industrial Network Communications.

In: IEEE Proceedings of the 21st International Conference on Applied Electronics (Sept 6-7 2016, Pilsen, Czech Republic).

(2016)

Contribution

Laurin Dörr
D. Fiala
Michael Heigl
Martin Schramm

Assessment simulation model for uncoupled message authentication.

In: Proceedings of the 22nd International Conference on Applied Electronics (AE 2017) [Sep 5-7, 2017; University of West Bohemia, Pilsen, Czech Republic].

Eds.:
Institute of Electrical and Electronics Engineers Inc.

(2017)

DOI: 10.23919/AE.2017.8053580

show abstract

Today's trend of an increasing number of networked embedded devices pervades many areas. Ranging from home automation, industrial or automotive applications with a large number of different protocols, low resources and often high demands on real-time make it difficult to secure the communication of such systems. A concept of an uncoupled MAC which is able to ensure the authenticity and integrity of communication flows between two network parties can be used. This is in particular of advance for outdated legacy components still participating in the network. In this paper a assessment simulation model of the mechanism behind this technology is described. It outlines the probability of detecting an attack depending on the message authentication overhead. The model considers all control variables and performs measurements based on random data traffic. The results of the statistical analysis state that a high attack detection rate can be obtained even with a small communication overhead.

Contribution

Martin Schramm
R. Dojen
Michael Heigl

Experimental assessment of FIRO- and GARO-based noise sources for digital TRNG designs on FPGAs.

In: Proceedings of the 22nd International Conference on Applied Electronics (AE 2017) [Sep 5-7, 2017; University of West Bohemia, Pilsen, Czech Republic]. pg. 1-6

Eds.:
Institute of Electrical and Electronics Engineers Inc.

(2017)

DOI: 10.23919/AE.2017.8053618

show abstract

The quality of TRNG designs mainly depends on the grade of the noise source from which the entropy will be harvested to extract randomness. Especially for purely digital noise sources suitable for FPGA implementations the use of Ring Oscillators is suggested in many scientific publications. Standard Ring Oscillator based noise sources however have earned some criticism regarding the amount of entropy generated. On this account different enhancements have been proposed, with Fibonacci Ring Oscillators (FIROs) and Galois Ring Oscillators (GAROs) being prominent examples, which under some circumstances are able to sustain a chaotic oscillation suitable for entropy extraction. This paper deals with the assessment of fully constrained FIRO and GARO noise source designs for a specific target FPGA. Due to the restrictive placement of ring elements the assessment yielded new criteria for choosing proper FIRO/GARO feedback configurations and an enhanced sampling method for entropy extraction has been derived.

Contribution

Michael Heigl
Laurin Dörr
Amar Almaini
D. Fiala
Martin Schramm

Incident Reaction Based on Intrusion Detections’ Alert Analysis.

In: Proceedings of the 23rd International Conference on Applied Electronics (AE) 2018 (University of West Bohemia, Pilsen, Czech Republic; September 11-12, 2018). pg. 1-6

Eds.:
Institute of Electrical and Electronics Engineers Inc.

(2018)

DOI: 10.23919/AE.2018.8501419

show abstract

The protection of internetworked systems by cryptographic techniques have crystallized as a fundamental aspect in establishing secure systems. Complementary, detection mechanisms for instance based on Intrusion Detection Systems has established itself as a fundamental part in holistic security eco-systems in the previous years. However, the interpretation of and reaction on detected incidents is still a challenging task. In this paper an incident handling environment with relevant components and exemplary functionality is proposed that involves the processes from the detection of incidents over their analysis to the execution of appropriate reactions. An evaluation of a selection of implemented interacting components using technology such as OpenFlow or Snort generally proofs the concept.

Journal article

Martin Schramm
R. Dojen
Michael Heigl

A Vendor-Neutral Unified Core for Cryptographic Operations in GF(p) and GF( 2m ) Based on Montgomery Arithmetic (Article ID 4983404).

In: Security and Communication Networks pg. 1-18

(2018)

DOI: 10.1155/2018/4983404

show abstract

In the emerging IoT ecosystem in which the internetworking will reach a totally new dimension the crucial role of efficient security solutions for embedded devices will be without controversy. Typically IoT-enabled devices are equipped with integrated circuits, such as ASICs or FPGAs to achieve highly specific tasks. Such devices must have cryptographic layers implemented and must be able to access cryptographic functions for encrypting/decrypting and signing/verifying data using various algorithms and generate true random numbers, random primes, and cryptographic keys. In the context of a limited amount of resources that typical IoT devices will exhibit, due to energy efficiency requirements, efficient hardware structures in terms of time, area, and power consumption must be deployed. In this paper, we describe a scalable word-based multivendor-capable cryptographic core, being able to perform arithmetic operations in prime and binary extension finite fields based on Montgomery Arithmetic. The functional range comprises the calculation of modular additions and subtractions, the determination of the Montgomery Parameters, and the execution of Montgomery Multiplications and Montgomery Exponentiations. A prototype implementation of the adaptable arithmetic core is detailed. Furthermore, the decomposition of cryptographic algorithms to be used together with the proposed core is stated and a performance analysis is given.

Lecture

Martin Schramm

A Practical Introduction to Cryptographic Engineering. [Invited Talk; eingeladen von Dalibor Fiala (PhD)].

Fakultät angewandte Wissenschaften, Department of Computer Science and Engineering Pilsen, Tschechische Republik

14.12.2018 (2018)

Journal article

Michael Heigl
Laurin Dörr
Nicolas Tiefnig
D. Fiala
Martin Schramm

A Resource-Preserving Self-Regulating Uncoupled MAC Algorithm to be Applied in Incident Detection.

In: Computers & Security vol. 85 pg. 270-285

(2019)

DOI: 10.1016/j.cose.2019.05.010

show abstract

The connectivity of embedded systems is increasing accompanied with thriving technology such as Internet of Things/Everything (IoT/E), Connected Cars, Smart Cities, Industry 4.0, 5G or Software-Defined Everything. Apart from the benefits of these trends, the continuous networking offers hackers a broad spectrum of attack vectors. The identification of attacks or unknown behavior through Intrusion Detection Systems (IDS) has established itself as a conducive and mandatory mechanism apart from the protection by cryptographic schemes in a holistic security eco-system. In systems where resources are valuable goods and stand in contrast to the ever increasing amount of network traffic, sampling has become a useful utility in order to detect malicious activities on a manageable amount of data. In this work an algorithm – Uncoupled MAC – is presented which secures network communication through a cryptographic scheme by uncoupled Message Authentication Codes (MAC) but as a side effect also provides IDS functionality producing alarms based on the violation of Uncoupled MAC values. Through a novel self-regulation extension, the algorithm adapts it’s sampling parameters based on the detection of malicious actions. The evaluation in a virtualized environment clearly shows that the detection rate increases over runtime for different attack scenarios. Those even cover scenarios in which intelligent attackers try to exploit the downsides of sampling.

Contribution

Laurin Dörr
Michael Heigl
D. Fiala
Martin Schramm

Comparison of Energy-Efficient Key Management Protocols for Wireless Sensor Networks.

In: Proceedings of the 2019 International Electronics Communication Conference (IECC '19) [July 7-9, 2019; Okinawa, Japan]. pg. 21-26

(2019)

DOI: 10.1145/3343147.3343156

show abstract

A Wireless Sensor Network (WSN) contains small sensor nodes which monitor physical or environmental conditions. WSN is an important technology for digitalization of industrial periphery and is often used in environments which are not hardened against security impacts. These networks are easy to attack due to the open communication medium and low computing resources of the applied devices. Establishing security mechanisms is difficult while taking into account low energy consumption. Low cost sensors with limited resources make the implementation of cryptographic algorithms even more challenging. For WSNs cryptographic functions are needed without high impact on energy consumption and latency. Therefore, security in WSNs is a challenging field of research. This paper compares lightweight energy-efficient key exchange protocols which are suitable for WSN. The protocols were also implemented in WSN-capable Texas Instrument boards and the energy consumption was measured during the key exchange. This paper shows that schemes have to be chosen depending on the specific network requirements and that the usage of asymmetric cryptography does not always result in a high energy consumption.

Contribution

Robert Wildenauer
Karl Leidl
Martin Schramm

Hacking an optics manufacturing machine: You don't see it coming?!.

In: Proceedings of SPIE 11171 (Sixth European Seminar on Precision Optics Manufacturing, 1117101 [9-10 April 2019, Teisnach]). pg. 11171071-11171076

Eds.:
Christian Schopf
Rolf Rascher

Bellingham, WA, USA

(2019)

DOI: 10.1117/12.2526691

show abstract

With more and more industrial devices getting inter-connected the attack surface for cyber attacks is increasing steadily. In this paper the possible approach of an attacker who got access to the office network at the Institute for Precision Manufacturing and High-Frequency Technology (IPH) to attack one of the optic machines that reside in another network segment is presented. Based on known vulnerabilities from the Common Vulnerabilities and Exposures (CVE), like the shellshock exploit or remote code execution with PsExec, for devices identified in the network, an attacker can bypass the firewall between the office network and the laboratory network and get full access to the HMI of the target machine.

Contribution

Michael Heigl
Martin Schramm
D. Fiala

A Lightweight Quantum-Safe Security Concept for Wireless Sensor Network Communication.

In: Proceedings of the IEEE Annual International Conference on Pervasive Computing and Communications Workshops (March 11-15, 2019; Kyoto, Japan). pg. 906-911

(2019)

DOI: 10.1109/PERCOMW.2019.8730749

show abstract

The ubiquitous internetworking of devices in all areas of life is boosted by various trends for instance the Internet of Things. Promising technologies that can be used for such future environments come from Wireless Sensor Networks. It ensures connectivity between distributed, tiny and simple sensor nodes as well as sensor nodes and base stations in order to monitor physical or environmental conditions such as vibrations, temperature or motion. Security plays an increasingly important role in the coming decades in which attacking strategies are becoming more and more sophisticated. Contemporary cryptographic mechanisms face a great threat from quantum computers in the near future and together with Intrusion Detection Systems are hardly applicable on sensors due to strict resource constraints. Thus, in this work a future-proof lightweight and resource-aware security concept for sensor networks with a processing stage permeated filtering mechanism is proposed. A special focus in the concepts evaluation lies on the novel Magic Number filter to mitigate a special kind of Denial-of-Service attack performed on CC1350 LaunchPad ARM Cortex-M3 microcontroller boards.

Contribution

Amar Almaini
A. Al Dubai
I. Romdhani
Martin Schramm

Delegation of Authentication to the Data Plane in Software Defined Networks.

In: Proceedings of the 18th IEEE International Conference on Ubiquitous Computing and Communications (IUCC 2019) [October 21-23, 2019, Shenyang, China]. pg. 58-65

(2019)

DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00038

show abstract

OpenFlow is considered as the most known protocol for Software Defined Networking (SDN). The main drawback of OpenFlow is the lack of support of new header definitions, which is required by network operators to apply new packet encapsulations. While SDN's logically centralized control plane could enhance network security by providing global visibility of the network state, it still has many side effects. The intelligent controllers that orchestrate the dumb switches are overloaded and become prone to failure. Delegating some level of control logic to the switches can offload the controllers from local state based decisions that do not require global network-wide knowledge. Thus, this paper, to the best of our knowledge, is the first to propose the delegation of typical security functions from specialized middleboxes to the data plane. We leverage the opportunities offered by P4 language to implement the functionality of authenticating nodes using port knocking. Our experimental results indicate that our proposed technique improves the network overall availability by offloading the controller as well as reducing the traffic in the network without noticeable negative impact on switches' performance.

Contribution

Michael Heigl
Laurin Dörr
Martin Schramm
D. Fiala

On the Energy Consumption of Quantum-resistant Cryptographic Software Implementations Suitable for Wireless Sensor Networks.

In: Proceedings of the 16th International Joint Conference on e-Business and Telecommunications (July 26-28, 2019; Prague, Czech Republic). pg. 72-83

(2019)

DOI: 10.5220/0007835600720083

show abstract

For an effective protection of the communication in Wireless Sensor Networks (WSN) facing e.g. threats by quantum computers in the near future, it is necessary to examine the applicability of quantum-resistant mechanisms in this field. It is the aim of this article to survey possible candidate schemes utilizable on sensor nodes and to compare the energy consumption of a selection of freely-available software implementations using a WSN-ready Texas Instruments CC1350 LaunchPad ARM® Cortex®-M3 microcontroller board.

Journal article

Amar Almaini
A. Al Dubai
I. Romdhani
Martin Schramm
A. Alsarhan

Lightweight edge authentication for software defined networks.

In: Computing (Special Issue)

(2020)

DOI: 10.1007/s00607-020-00835-4

show abstract

OpenFlow is considered as the most known protocol for Software Defined Networking (SDN). The main drawback of OpenFlow is the lack of support of new header definitions, which is required by network operators to apply new packet encapsulations. While SDN’s logically centralized control plane could enhance network security by providing global visibility of the network state, it still has many side effects. The intelligent controllers that orchestrate the dumb switches are overloaded and become prone to failure. Delegating some level of control logic to the edge or, to be precise, the switches can offload the controllers from local state based decisions that do not require global network wide knowledge. Thus, this paper, to the best of our knowledge, is the first to propose the delegation of typical security functions from specialized middleboxes to the data plane. We leverage the opportunities offered by programming protocol-independent packet processors (P4) language to present two authentication techniques to assure that only legitimate nodes are able to access the network. The first technique is the port knocking and the second technique is the One-Time Password. Our experimental results indicate that our proposed techniques improve the network overall availability by offloading the controller as well as reducing the traffic in the network without noticeable negative impact on switches’ performance.

Journal article

Michael Heigl
Kumar Anand
Andreas Urmann
D. Fiala
Martin Schramm
Robert Hable

On the Improvement of the Isolation Forest Algorithm for Outlier Detection with Streaming Data.

In: Electronics vol. 10 pg. 1534

(2021)

DOI: 10.3390/electronics10131534

show abstract

In recent years, detecting anomalies in real-world computer networks has become a more and more challenging task due to the steady increase of high-volume, high-speed and high-dimensional streaming data, for which ground truth information is not available. Efficient detection schemes applied on networked embedded devices need to be fast and memory-constrained, and must be capable of dealing with concept drifts when they occur. Different approaches for unsupervised online outlier detection have been designed to deal with these circumstances in order to reliably detect malicious activity. In this paper, we introduce a novel framework called PCB-iForest, which generalized, is able to incorporate any ensemble-based online OD method to function on streaming data. Carefully engineered requirements are compared to the most popular state-of-the-art online methods with an in-depth focus on variants based on the widely accepted isolation forest algorithm, thereby highlighting the lack of a flexible and efficient solution which is satisfied by PCB-iForest. Therefore, we integrate two variants into PCB-iForest—an isolation forest improvement called extended isolation forest and a classic isolation forest variant equipped with the functionality to score features according to their contributions to a sample’s anomalousness. Extensive experiments were performed on 23 different multi-disciplinary and security-related real-world datasets in order to comprehensively evaluate the performance of our implementation compared with off-the-shelf methods. The discussion of results, including AUC, F1 score and averaged execution time metric, shows that PCB-iForest clearly outperformed the state-of-the-art competitors in 61% of cases and even achieved more promising results in terms of the tradeoff between classification and computational costs.

Journal article

Michael Heigl
Enrico Weigelt
Andreas Urmann
D. Fiala
Martin Schramm

Exploiting the Outcome of Outlier Detection for Novel Attack Pattern Recognition on Streaming Data.

In: Electronics vol. 10 pg. 2160

(2021)

DOI: 10.3390/electronics10172160

show abstract

Future-oriented networking infrastructures are characterized by highly dynamic Streaming Data (SD) whose volume, speed and number of dimensions increased significantly over the past couple of years, energized by trends such as Software-Defined Networking or Artificial Intelligence. As an essential core component of network security, Intrusion Detection Systems (IDS) help to uncover malicious activity. In particular, consecutively applied alert correlation methods can aid in mining attack patterns based on the alerts generated by IDS. However, most of the existing methods lack the functionality to deal with SD data affected by the phenomenon called concept drift and are mainly designed to operate on the output from signature-based IDS. Although unsupervised Outlier Detection (OD) methods have the ability to detect yet unknown attacks, most of the alert correlation methods cannot handle the outcome of such anomaly-based IDS. In this paper, we introduce a novel framework called Streaming Outlier Analysis and Attack Pattern Recognition, denoted as SOAAPR, which is able to process the output of various online unsupervised OD methods in a streaming fashion to extract information about novel attack patterns. Three different privacy-preserving, fingerprint-like signatures are computed from the clustered set of correlated alerts by SOAAPR, which characterizes and represents the potential attack scenarios with respect to their communication relations, their manifestation in the data’s features and their temporal behavior. Beyond the recognition of known attacks, comparing derived signatures, they can be leveraged to find similarities between yet unknown and novel attack patterns. The evaluation, which is split into two parts, takes advantage of attack scenarios from the widely-used and popular CICIDS2017 and CSE-CIC-IDS2018 datasets. Firstly, the streaming alert correlation capability is evaluated on CICIDS2017 and compared to a state-of-the-art offline algorithm, called Graph-based Alert Correlation (GAC), which has the potential to deal with the outcome of anomaly-based IDS. Secondly, the three types of signatures are computed from attack scenarios in the datasets and compared to each other. The discussion of results, on the one hand, shows that SOAAPR can compete with GAC in terms of alert correlation capability leveraging four different metrics and outperforms it significantly in terms of processing time by an average factor of 70 in 11 attack scenarios. On the other hand, in most cases, all three types of signatures seem to reliably characterize attack scenarios such that similar ones are grouped together, with up to 99.05% similarity between the FTP and SSH Patator attack.

Journal article

Michael Heigl
Enrico Weigelt
D. Fiala
Martin Schramm

Unsupervised Feature Selection for Outlier Detection on Streaming Data to Enhance Network Security.

In: Applied Sciences vol. 11 pg. 12073

(2021)

DOI: 10.3390/app112412073

show abstract

Over the past couple of years, machine learning methods—especially the outlier detection ones—have anchored in the cybersecurity field to detect network-based anomalies rooted in novel attack patterns. However, the ubiquity of massive continuously generated data streams poses an enormous challenge to efficient detection schemes and demands fast, memory-constrained online algorithms that are capable to deal with concept drifts. Feature selection plays an important role when it comes to improve outlier detection in terms of identifying noisy data that contain irrelevant or redundant features. State-of-the-art work either focuses on unsupervised feature selection for data streams or (offline) outlier detection. Substantial requirements to combine both fields are derived and compared with existing approaches. The comprehensive review reveals a research gap in unsupervised feature selection for the improvement of outlier detection methods in data streams. Thus, a novel algorithm for Unsupervised Feature Selection for Streaming Outlier Detection, denoted as UFSSOD, will be proposed, which is able to perform unsupervised feature selection for the purpose of outlier detection on streaming data. Furthermore, it is able to determine the amount of top-performing features by clustering their score values. A generic concept that shows two application scenarios of UFSSOD in conjunction with off-the-shell online outlier detection algorithms has been derived. Extensive experiments have shown that a promising feature selection mechanism for streaming data is not applicable in the field of outlier detection. Moreover, UFSSOD, as an online capable algorithm, yields comparable results to a state-of-the-art offline method trimmed for outlier detection. V

Contribution

Amar Almaini
Jakob Folz
D. Wölfl
A. Al Dubai
Martin Schramm
Michael Heigl

A New Scalable Distributed Homomorphic Encryption Scheme for High Computational Complexity Models.

In: Proceedings of the International Wireless Communications & Mobile Computing Conference (IWCMC 2023): Smart & Sustainable Communications.

(2023)

DOI: 10.1109/IWCMC58020.2023.10183131

show abstract

Due to the increasing privacy demand in data processing, Fully Homomorphic Encryption (FHE) has recently received growing attention for its ability to perform calculations over encrypted data. Since the data can be processed in encrypted form and the output remains encrypted, only an authorized user or a user who holds the key can decrypt the data and understand its meaning. Hence, it is possible to securely outsource data processing to untrustworthy but powerful public computing resources on the edge. However, due to the high computational complexity, FHE-based data processing experiences scalability related concerns. It is currently unclear whether FHE can be used to solve large-scale problems. In this paper, we propose a novel general distributed FHE-based data processing approach as a concrete step towards solving the scalability challenge. The main idea behind our approach is to use slightly more communication overhead for a shorter computing circuit in FHE, hence, reducing the overall complexity. We verify our new model’s efficiency and effectiveness by comparing the distributed approach with the central approach over various FHE schemes (CKKS, BGV, and BFV). This is performed using one of the more popular libraries of FHE “Microsoft SEAL”, by performing specific mathematical operations and observing the time consumed. The empirical results demonstrate that the proposed approach results in a significant reduction in time, up to 54% compared to the traditional central approach.

Journal article

Robert Aufschläger
Jakob Folz
E. März
J. Guggumos
Michael Heigl
B. Buchner
Martin Schramm

Anonymization Procedures for Tabular Data: An Explanatory Technical and Legal Synthesis.

In: Information vol. 14 pg. 487

(2023)

DOI: 10.3390/info14090487

show abstract

In the European Union, Data Controllers and Data Processors, who work with personal data, have to comply with the General Data Protection Regulation and other applicable laws. This affects the storing and processing of personal data. But some data processing in data mining or statistical analyses does not require any personal reference to the data. Thus, personal context can be removed. For these use cases, to comply with applicable laws, any existing personal information has to be removed by applying the so-called anonymization. However, anonymization should maintain data utility. Therefore, the concept of anonymization is a double-edged sword with an intrinsic trade-off: privacy enforcement vs. utility preservation. The former might not be entirely guaranteed when anonymized data are published as Open Data. In theory and practice, there exist diverse approaches to conduct and score anonymization. This explanatory synthesis discusses the technical perspectives on the anonymization of tabular data with a special emphasis on the European Union’s legal base. The studied methods for conducting anonymization, and scoring the anonymization procedure and the resulting anonymity are explained in unifying terminology. The examined methods and scores cover both categorical and numerical data. The examined scores involve data utility, information preservation, and privacy models. In practice-relevant examples, methods and scores are experimentally tested on records from the UCI Machine Learning Repository’s “Census Income (Adult)” dataset.

Contribution

Amar Almaini
Tobias Koßmann
Jakob Folz
Martin Schramm
Michael Heigl
A. Al Dubai

Integrating Reality: A Hybrid SDN Testbed for Enhanced Realism in Edge Computing Simulations.

In: Proceedings of the 10th International Conference on Ubiquitous Networking (UNet24).

(2024)

show abstract

Recent advancements in Software-Defined Networking (SDN) have facilitated its deployment across diverse network types, including edge networks. Given the broad applicability of SDN and the complexity of large-scale environments, establishing a comprehensive real-world test environment is both challenging and expensive. To circumvent these obstacles, software-based simulations are typically employed to validate solutions prior to real-world deployment. However, these simulations often do not incorporate real-time hardware data, limiting their realism. This paper introduces a novel hybrid SDN simulation testbed that integrates real hardware data within a Mininet-emulated network, addressing this limitation. To demonstrate the efficacy of our hybrid testbed, we present a specific scenario involving the dynamic allocation of edge resources to various client requests through a machine learning approach. This scenario focuses on detecting LiDAR spoofing attacks within automotive systems. Additionally, our hybrid testbed facilitates the generation and replication of new datasets for tailored scenarios, enhancing research capabilities in more intricate contexts.

Contribution

Robert Aufschläger
Sebastian Wilhelm
Michael Heigl
Martin Schramm

ClustEm4Ano: Clustering Text Embeddings of Nominal Textual Attributes for Microdata Anonymization.

In: Database Engineered Applications. (Lecture Notes in Computer Science) pg. 122-137

Eds.:
R. Chbeir
S. Ilarri
J. Bernardino
P. Revesz
Y. Manolopoulos
C. Leung

Springer Nature Switzerland Cham

(2025)

DOI: 10.1007/978-3-031-83472-1_9

show abstract

This work introduces ClustEm4Ano, an anonymization pipeline that can be used for generalization and suppression-based anonymization of nominal textual tabular data. It automatically generates value generalization hierarchies (VGHs) that, in turn, can be used to generalize attributes in quasi-identifiers. The pipeline leverages embeddings to generate semantically close value generalizations through iterative clustering. We applied KMeans and Hierarchical Agglomerative Clustering on 13 different predefined text embeddings (both open and closed-source (via APIs)). Our approach is experimentally tested on a well-known benchmark dataset for anonymization: The UCI Machine Learning Repository’s Adult dataset. ClustEm4Ano supports anonymization procedures by offering more possibilities compared to using arbitrarily chosen VGHs. Experiments demonstrate that these VGHs can outperform manually constructed ones in terms of downstream efficacy (especially for small k-anonymity) and therefore can foster the quality of anonymized datasets. Our implementation is made public.

projects

Institute ProtectIT

labs

IT-Security

core competencies

Applied cryptography
- Elliptic Curve Cryptography
- Pairing-based Cryptography
- Post-Quantum Cryptography
- Lightweight Cryptography
Distributed Ledger Technologies
FPGA Programming
Security aspects for autonomous driving
Security mechanisms in industrial networks
Trusted Computing Technologies (TPM, TNC)

Vita

since 2017: head of the institute ProtectIT - Protection for Industrial Technologies
since 2017: professor at the Deggendorf Institute of Technology, Faculty of Computer Science
since 2014: freelancer for ProtectEM GmbH
2012 - 2016: cooperative promotion, University of Limerick, Ireland
2010 – 2011: Masterstudium Master’s Degree by Research an Thesis, University of Limerick, Irland, Studienabschluss: M.Eng.
2006 - 2010: studies in Mechatronics (majoring in Mechatronic Systems) at the Deggendorf Institute of Technology, B.Eng

Other

Head of Institute ProtectIT
Course Co-ordinator Bachelor Cyber Security
Member of Examination Board Further Education Centre