Script list Publications
(1) Non-Profiled Semi-Supervised Horizontal Attack Against Elliptic Curve Scalar Multiplication using Support Vector Machines
M. Aftowicz, I. Kabin, Z. Dyka, P. Langendörfer
Proc. 26th Euromicro Conference Series on Digital System Design (DSD 2023), (2023)
(Total Resilience)
(2) You Are What You Attack: Breaking the Cryptographically-Protected S7 Protocol
W. Alsabbagh, P. Langendörfer
Proc. 19th IEEE International Conference on Factory Communication Systems (WFCS 2023), (2023)
DOI: 10.1109/WFCS57264.2023.10144251
(3) Good Night, and Good Luck: A Control Logic Injection Attack on OpenPLC
W. Alsabbagh, C. Kim, P. Langendörfer
Proc. 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023), (2023)
DOI: 10.1109/IECON51785.2023.10312570, (EMiL)
(4) A Stealthy False Command Injection Attack on Modbus based SCADA Systems
W. Alsabbagh, S. Amogbonjaye, D. Urrego and P. Langendörfer
Proc. 5th International Workshop on Security Trust Privacy for Cyber-Physical Systems (STP-CPS 2023), (2023)
DOI: 10.1109/CCNC51644.2023.10059804, (KITS)
(5) On the Stability and Homogeneous Ensemble of Feature Selection for Predictive Maintenance: A Classification Application for Tool Condition Monitoring in Milling
M. Assafo, J.P. Städter, T. Meisel, P. Langendörfer
Sensors (MDPI) 23(9), 4461 (2023)
DOI: 10.3390/s23094461, (iCampus)
Feature selection (FS) represents an essential step for many machine learning-based predictive maintenance (PdM) applications, including various industrial processes, components, and monitoring tasks. The selected features not only serve as inputs to the learning models but also can influence further decisions and analysis, e.g., sensor selection and understandability of the PdM system. Hence, before deploying the PdM system, it is crucial to examine the reproducibility and robustness of the selected features under variations in the input data. This is particularly critical for real-world datasets with a low sample-to-dimension ratio (SDR). However, to the best of our knowledge, stability of the FS methods under data variations has not been considered yet in the field of PdM. This paper addresses this issue with an application to tool condition monitoring in milling, where classifiers based on support vector machines and random forest were employed. We used a five-fold cross-validation to evaluate three popular filter-based FS methods, namely Fisher score, minimum redundancy maximum relevance (mRMR), and ReliefF, in terms of both stability and macro-F1. Further, for each method, we investigated the impact of the homogeneous FS ensemble on both performance indicators. To gain broad insights, we used four (2:2) milling datasets obtained from our experiments and NASA’s repository, which differ in the operating conditions, sensors, SDR, number of classes, etc. For each dataset, the study was conducted for two individual sensors and their fusion. Among the conclusions: (1) Different FS methods can yield comparable macro-F1 yet considerably different FS stability values. (2) Fisher score (single and/or ensemble) is superior in most of the cases. (3) mRMR’s stability is overall the lowest, the most variable over different settings (e.g., sensor(s), subset cardinality), and the one that benefits the most from the ensemble.
(6) The ForTune Toolbox: Building Solutions for Condition-Based and Predictive Maintenance Focusing on Retrofitting
M. Assafo, M. Lautsch, P. Suawa, M. Jongmanns, M.Huebner, M. Reichenbach, C. Brockmann, D. Reinhardt, P. Langendörfer
Proc. 10. MikroSystemTechnik Kongress (MST 2023), 541 (2023)
(7) Novel Approach to a Plant Inspired Distributed Security Scheme for Wireless Sensor Networks
B. Förster, P. Langendörfer, T. Hinze
Proc. Mediterranean Conference on Embedded Computing (MECO 2023), 353 (2023)
DOI: 10.1109/MECO58584.2023.10154949
(8) Determining Distributions of Security Means for Wireless Sensor Networks based on the Model of a Neighbourhood Watch
B. Förster, P. Langendörfer, T. Hinze
International Journal of Information Security
zu finden unter: https://arxiv.org/abs/2212.09050
Neighbourhood watch is a concept that allows a community to distribute a complex security task in between all members. Members of the community carry out individual security tasks to contribute to the overall security of it. It reduces the workload of a particular individual while securing all members and allowing them to carry out a multitude of security tasks. Wireless sensor networks (WSNs) are composed of resource-constraint independent battery driven computers as nodes communicating wirelessly. Security in WSNs is essential. Without sufficient security, an attacker is able to eavesdrop the communication, tamper monitoring results or deny critical nodes providing their service in a way to cut off larger network parts. The resource-constraint nature of sensor nodes prevents them from running full-fledged security protocols. Instead, it is necessary to assess the most significant security threats and implement specialised protocols. A neighbourhood-watch inspired distributed security scheme for WSNs has been introduced by Langendörfer. Its goal is to increase the variety of attacks a WSN can fend off. A framework of such complexity has to be designed in multiple steps. Here, we introduce an approach to determine distributions of security means on large-scale static homogeneous WSNs. Therefore, we model WSNs as undirected graphs in which two nodes connected iff they are in transmission range. The framework aims to partition the graph into η distinct security means resulting in the targeted distribution. The underlying problems turn out to be NP hard and we attempt to solve them using linear programs (LPs). To evaluate the computability of the LPs, we generate large numbers of random {\lambda}-precision unit disk graphs (UDGs) as representation of WSNs. For this purpose, we introduce a novel {\lambda}-precision UDG generator to model WSNs with a minimal distance in between nodes.
(9) Machine Learning based Real Time Detection of Freezing of Gait of Parkinson Patients Running on a Body Worn Device
A. Haddadi Esfahani, O. Maye, M. Frohberg, M. Speh, M. Jöbges, P. Langendörfer
Proc. IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2023), 181 (2023)
DOI: 10.1145/3580252.3589423, (FastGait)
(10) Television, Authoritarianism, and Support for Trump: A Replication
E. Hermann, M. Morgan, J. Shanahan, H.Y. Yan
Public Opinion Quarterly 87(2), 389 (2023)
DOI: 10.1093/poq/nfad015
Many factors contributed to support for Donald Trump in the 2016 US presidential election, among them media influences. Morgan and Shanahan (2017) found that television viewing was associated with support for Trump, mediated through authoritarianism. In light of the changes in the political and media environments during Trump’s presidency, our study examined whether Morgan and Shanahan’s (2017) findings still held in the 2020 US presidential election. Replicating their findings, we found that authoritarianism still mediates the relationship between television viewing and Trump support. As in the original study, the indirect effect is moderated by political ideology and gender, with stronger indirect effects among liberals and females.
(11) Randomized Addressing Countermeasures are Inefficient against Address-Bit SCA
I. Kabin, Z. Dyka, P. Langendörfer
Proc. IEEE International Conference on Cyber Security and Resilience (CSR 2023), 580 (2023)
DOI: 10.1109/CSR57506.2023.10224968, (Total Resilience)
(12) Vulnerability of Atomic Patterns to Simple SCA
I. Kabin, P. Langendörfer, Z. Dyka
Proc. 19th IEEE East-West Design & Test Symposium (EWDTS 2023), (2023)
DOI: 10.1109/EWDTS59469.2023.10297074, (Total Resilience)
(13) Information Security: The Cornerstone for Surviving the Digital Wild
P. Langendörfer, St. Kornemann, W. Alsabbagh, E. Hermann
The Future of Smart Production for SMEs, 1st Edition, Editors: O. Madsen, U. Berger, C. Moller, A. Lassen Heidemann, B. Waehrens Vejrum, C. Schou, Chapter. Information Security: The Cornerstone for Surviving the Digital Wild, Springer, 335 (2023)
DOI: 10.1007/978-3-031-15428-7_29, (KITS)
(14) Coarse-Grained Control Flow Integrity Check for Processors with Sliding Register Windows
K. Lehniger, M. Aftowicz, M. Schölzel, P. Langendörfer
Proc. 12th Mediteranean Conference on Embedded Computing (MECO 2023), 205 (2023)
DOI: 10.1109/MECO58584.2023.10154928, (MORFEUS)
(15) Window Canaries: Re-Thinking Stack Canaries for Architectures with Register Windows
K. Lehniger, P. Langendörfer
IEEE Transactions on Dependable and Secure Computing 20(6), 4637 (2023)
DOI: 10.1109/TDSC.2022.3230748, (MORFEUS)
This paper presents Window Canaries, a novel approach to Stack Canaries for architectures with a register window that protects return addresses and stack pointers without the need of adding additional instruction to each potentially vulnerable function. Instead, placement and check of the canary word is moved to window exception handlers that are responsible to handle register window overflows and underflows. The approach offers low performance overhead while guaranteeing that return addresses are protected by stack buffer overflows without relying on a heuristic that decides which functions to instrument. The contributions of this paper are a complete implementation of the approach for the Xtensa LX architecture with register window option as well as a performance evaluation and discussion of advantages and drawbacks.
(16) Through the Window: Exploitation and Countermeasures of the ESP32 Register Window Overflow
K. Lehniger, P. Langendörfer
Future Internet (MDPI) 15(6), 217 (2023)
DOI: 10.3390/fi15060217, (MORFEUS)
With the increasing popularity of IoT (Internet-of-Things) devices, their security becomes an increasingly important issue. Buffer overflow vulnerabilities have been known for decades, but are still relevant, especially for embedded devices where certain security measures cannot be implemented due to hardware restrictions or simply due to their impact on performance. Therefore, many buffer overflow detection mechanisms check for overflows only before critical data are used. All data that an attacker could use for his own purposes can be considered critical. It is, therefore, essential that all critical data are checked between writing a buffer and its usage. This paper presents a vulnerability of the ESP32 microcontroller, used in millions of IoT devices, that is based on a pointer that is not protected by classic buffer overflow detection mechanisms such as Stack Canaries or Shadow Stacks. This paper discusses the implications of vulnerability and presents mitigation techniques, including a patch, that fixes the vulnerability. The overhead of the patch is evaluated using simulation as well as an ESP32-WROVER-E development board. We showed that, in the simulation with 32 general-purpose registers, the overhead for the CoreMark benchmark ranges between 0.1% and 0.4%. On the ESP32, which uses an Xtensa LX6 core with 64 general-purpose registers, the overhead went down to below 0.01%. A worst-case scenario, modeled by a synthetic benchmark, showed overheads up to 9.68%.
(17) On the Feasibility of Single-Trace Attacks on the Gaussian Sampler using a CDT
S. Marzougui, I. Kabin, J. Krämer, T. Aulbach, J.-P. Seifert
Proc. International Workshop on Constructive Side-Channel Analysis and Secure Design (COSADE 2023), in: Lecture Notes in Computer Science, Springer, LNCS 13979, 149 (2023)
DOI: 10.1007/978-3-031-29497-6_8, (Total Resilience)
(18) GPS-Spoofing Attack Detection Mechanism for UAV Swarms
P. Mykytyn, M. Brzozowski, Z. Dyka, P. Langendörfer
Proc. 11th International Conference on Cyber-Physical Systems and Internet-of-Things (CPS&IoT 2023), 18 (2023)
DOI: 10.1109/MECO58584.2023.10154998, (iCampus)
(19) Modular Platform for Teaching Robotics
D. Nagajek, M. Rapala, K. Woloszyn, K. Turchan, K. Piotrowski
Proc. 10th Machine Intelligence and Digital Interaction (MIDI 2022), in: Lecture Notes in Networks and Systems, Springer, LNNS 710, 167 (2023)
DOI: 10.1007/978-3-031-37649-8_17, (Space Region)
(20) Optical Fault Injection Attacks against Different Logic and Memory Cells
D. Petryk, Z. Dyka
Proc. 11th Prague Embedded Systems Workshop (PESW 2023), 24 (2023)
(Total Resilience)
(21) A Modular Communication Architecture for Adaptive UAV Swarms
K. Shahin, R. Rotta, O. Archila, P. Mykytyn, M. Nattke, M. Reichenbach, J. Nolte, R. Natarov
Proc. IEEE International Conference on Omni Layer Intelligent Systems (COINS 2023), (2023)
DOI: 10.1109/COINS57856.2023.10189245, (iCampus II)
(22) Intelligence and Motion Models of Continuum Robots: an Overview
O. Shamilyan, I. Kabin, Z. Dyka, O. Sudakov, A. Cherninsky, M. Brzozowski, P. Langendörfer
IEEE Access 11, 60988 (2023)
DOI: 10.1109/ACCESS.2023.3286300, (Total Resilience)
Many technical solutions are bio-inspired. Octopus-inspired robotic arms belong to continuum robots which are used in minimally invasive surgery or for technical system restoration in areas difficult-to-access. Continuum robot missions are bounded with their motions, whereby the motion of the robots is controlled by humans via wireless communication. In case of a lost connection, robot autonomy is required. Distributed control and distributed decision-making mechanisms based on artificial intelligence approaches can be a promising solution to achieve autonomy of technical systems and to increase their resilience. However these methods are not well investigated yet. Octopuses are the living example of natural distributed intelligence but their learning and decision-making mechanisms are also not fully investigated and understood yet. Mechanisms of Distributed Artificial Intelligence can be investigated using a physical continuum robot prototype that is able to perform some basic movements and combine them into sequences of motions by itself. For the experimental investigations a suitable physical prototype has to be selected, its motion control has to be implemented and automated. In this paper, we give an overview combining different fields of research, such as Distributed Artificial Intelligence and continuum robots based on 97 publications. We provide a detailed description of the basic motion control models of continuum robots based on the literature reviewed, discuss different aspects of autonomy and give an overview of physical prototypes of continuum robots.
(23) Successful Simple Side Channel Analysis: Vulnerability of an Atomic Pattern kP Algorithm Implemented with a Constant Time Crypto Library to Simple Electromagnetic Analysis Attacks
A.A. Sigourou, I. Kabin, P. Langendörfer, N. Sklavos, Z. Dyka
Proc. 12th Mediterranean Conference on Embedded Computing (MECO 2023), 167 (2023)
DOI: 10.1109/MECO58584.2023.10154940, (Total Resilience)
(24) AI4U: Modular Framework for AI Application Design
K. Wołoszyn, K. Turchan, M. Rąpała, K. Piotrowski
Proc. 10th Machine Intelligence and Digital Interaction (MIDI 2022), in: Lecture Notes in Networks and Systems, Springer, LNNS 710, 56 (2023)
DOI: 10.1007/978-3-031-37649-8_6, (Space Region)
M. Aftowicz, I. Kabin, Z. Dyka, P. Langendörfer
Proc. 26th Euromicro Conference Series on Digital System Design (DSD 2023), (2023)
(Total Resilience)
(2) You Are What You Attack: Breaking the Cryptographically-Protected S7 Protocol
W. Alsabbagh, P. Langendörfer
Proc. 19th IEEE International Conference on Factory Communication Systems (WFCS 2023), (2023)
DOI: 10.1109/WFCS57264.2023.10144251
(3) Good Night, and Good Luck: A Control Logic Injection Attack on OpenPLC
W. Alsabbagh, C. Kim, P. Langendörfer
Proc. 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023), (2023)
DOI: 10.1109/IECON51785.2023.10312570, (EMiL)
(4) A Stealthy False Command Injection Attack on Modbus based SCADA Systems
W. Alsabbagh, S. Amogbonjaye, D. Urrego and P. Langendörfer
Proc. 5th International Workshop on Security Trust Privacy for Cyber-Physical Systems (STP-CPS 2023), (2023)
DOI: 10.1109/CCNC51644.2023.10059804, (KITS)
(5) On the Stability and Homogeneous Ensemble of Feature Selection for Predictive Maintenance: A Classification Application for Tool Condition Monitoring in Milling
M. Assafo, J.P. Städter, T. Meisel, P. Langendörfer
Sensors (MDPI) 23(9), 4461 (2023)
DOI: 10.3390/s23094461, (iCampus)
Feature selection (FS) represents an essential step for many machine learning-based predictive maintenance (PdM) applications, including various industrial processes, components, and monitoring tasks. The selected features not only serve as inputs to the learning models but also can influence further decisions and analysis, e.g., sensor selection and understandability of the PdM system. Hence, before deploying the PdM system, it is crucial to examine the reproducibility and robustness of the selected features under variations in the input data. This is particularly critical for real-world datasets with a low sample-to-dimension ratio (SDR). However, to the best of our knowledge, stability of the FS methods under data variations has not been considered yet in the field of PdM. This paper addresses this issue with an application to tool condition monitoring in milling, where classifiers based on support vector machines and random forest were employed. We used a five-fold cross-validation to evaluate three popular filter-based FS methods, namely Fisher score, minimum redundancy maximum relevance (mRMR), and ReliefF, in terms of both stability and macro-F1. Further, for each method, we investigated the impact of the homogeneous FS ensemble on both performance indicators. To gain broad insights, we used four (2:2) milling datasets obtained from our experiments and NASA’s repository, which differ in the operating conditions, sensors, SDR, number of classes, etc. For each dataset, the study was conducted for two individual sensors and their fusion. Among the conclusions: (1) Different FS methods can yield comparable macro-F1 yet considerably different FS stability values. (2) Fisher score (single and/or ensemble) is superior in most of the cases. (3) mRMR’s stability is overall the lowest, the most variable over different settings (e.g., sensor(s), subset cardinality), and the one that benefits the most from the ensemble.
(6) The ForTune Toolbox: Building Solutions for Condition-Based and Predictive Maintenance Focusing on Retrofitting
M. Assafo, M. Lautsch, P. Suawa, M. Jongmanns, M.Huebner, M. Reichenbach, C. Brockmann, D. Reinhardt, P. Langendörfer
Proc. 10. MikroSystemTechnik Kongress (MST 2023), 541 (2023)
(7) Novel Approach to a Plant Inspired Distributed Security Scheme for Wireless Sensor Networks
B. Förster, P. Langendörfer, T. Hinze
Proc. Mediterranean Conference on Embedded Computing (MECO 2023), 353 (2023)
DOI: 10.1109/MECO58584.2023.10154949
(8) Determining Distributions of Security Means for Wireless Sensor Networks based on the Model of a Neighbourhood Watch
B. Förster, P. Langendörfer, T. Hinze
International Journal of Information Security
zu finden unter: https://arxiv.org/abs/2212.09050
Neighbourhood watch is a concept that allows a community to distribute a complex security task in between all members. Members of the community carry out individual security tasks to contribute to the overall security of it. It reduces the workload of a particular individual while securing all members and allowing them to carry out a multitude of security tasks. Wireless sensor networks (WSNs) are composed of resource-constraint independent battery driven computers as nodes communicating wirelessly. Security in WSNs is essential. Without sufficient security, an attacker is able to eavesdrop the communication, tamper monitoring results or deny critical nodes providing their service in a way to cut off larger network parts. The resource-constraint nature of sensor nodes prevents them from running full-fledged security protocols. Instead, it is necessary to assess the most significant security threats and implement specialised protocols. A neighbourhood-watch inspired distributed security scheme for WSNs has been introduced by Langendörfer. Its goal is to increase the variety of attacks a WSN can fend off. A framework of such complexity has to be designed in multiple steps. Here, we introduce an approach to determine distributions of security means on large-scale static homogeneous WSNs. Therefore, we model WSNs as undirected graphs in which two nodes connected iff they are in transmission range. The framework aims to partition the graph into η distinct security means resulting in the targeted distribution. The underlying problems turn out to be NP hard and we attempt to solve them using linear programs (LPs). To evaluate the computability of the LPs, we generate large numbers of random {\lambda}-precision unit disk graphs (UDGs) as representation of WSNs. For this purpose, we introduce a novel {\lambda}-precision UDG generator to model WSNs with a minimal distance in between nodes.
(9) Machine Learning based Real Time Detection of Freezing of Gait of Parkinson Patients Running on a Body Worn Device
A. Haddadi Esfahani, O. Maye, M. Frohberg, M. Speh, M. Jöbges, P. Langendörfer
Proc. IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2023), 181 (2023)
DOI: 10.1145/3580252.3589423, (FastGait)
(10) Television, Authoritarianism, and Support for Trump: A Replication
E. Hermann, M. Morgan, J. Shanahan, H.Y. Yan
Public Opinion Quarterly 87(2), 389 (2023)
DOI: 10.1093/poq/nfad015
Many factors contributed to support for Donald Trump in the 2016 US presidential election, among them media influences. Morgan and Shanahan (2017) found that television viewing was associated with support for Trump, mediated through authoritarianism. In light of the changes in the political and media environments during Trump’s presidency, our study examined whether Morgan and Shanahan’s (2017) findings still held in the 2020 US presidential election. Replicating their findings, we found that authoritarianism still mediates the relationship between television viewing and Trump support. As in the original study, the indirect effect is moderated by political ideology and gender, with stronger indirect effects among liberals and females.
(11) Randomized Addressing Countermeasures are Inefficient against Address-Bit SCA
I. Kabin, Z. Dyka, P. Langendörfer
Proc. IEEE International Conference on Cyber Security and Resilience (CSR 2023), 580 (2023)
DOI: 10.1109/CSR57506.2023.10224968, (Total Resilience)
(12) Vulnerability of Atomic Patterns to Simple SCA
I. Kabin, P. Langendörfer, Z. Dyka
Proc. 19th IEEE East-West Design & Test Symposium (EWDTS 2023), (2023)
DOI: 10.1109/EWDTS59469.2023.10297074, (Total Resilience)
(13) Information Security: The Cornerstone for Surviving the Digital Wild
P. Langendörfer, St. Kornemann, W. Alsabbagh, E. Hermann
The Future of Smart Production for SMEs, 1st Edition, Editors: O. Madsen, U. Berger, C. Moller, A. Lassen Heidemann, B. Waehrens Vejrum, C. Schou, Chapter. Information Security: The Cornerstone for Surviving the Digital Wild, Springer, 335 (2023)
DOI: 10.1007/978-3-031-15428-7_29, (KITS)
(14) Coarse-Grained Control Flow Integrity Check for Processors with Sliding Register Windows
K. Lehniger, M. Aftowicz, M. Schölzel, P. Langendörfer
Proc. 12th Mediteranean Conference on Embedded Computing (MECO 2023), 205 (2023)
DOI: 10.1109/MECO58584.2023.10154928, (MORFEUS)
(15) Window Canaries: Re-Thinking Stack Canaries for Architectures with Register Windows
K. Lehniger, P. Langendörfer
IEEE Transactions on Dependable and Secure Computing 20(6), 4637 (2023)
DOI: 10.1109/TDSC.2022.3230748, (MORFEUS)
This paper presents Window Canaries, a novel approach to Stack Canaries for architectures with a register window that protects return addresses and stack pointers without the need of adding additional instruction to each potentially vulnerable function. Instead, placement and check of the canary word is moved to window exception handlers that are responsible to handle register window overflows and underflows. The approach offers low performance overhead while guaranteeing that return addresses are protected by stack buffer overflows without relying on a heuristic that decides which functions to instrument. The contributions of this paper are a complete implementation of the approach for the Xtensa LX architecture with register window option as well as a performance evaluation and discussion of advantages and drawbacks.
(16) Through the Window: Exploitation and Countermeasures of the ESP32 Register Window Overflow
K. Lehniger, P. Langendörfer
Future Internet (MDPI) 15(6), 217 (2023)
DOI: 10.3390/fi15060217, (MORFEUS)
With the increasing popularity of IoT (Internet-of-Things) devices, their security becomes an increasingly important issue. Buffer overflow vulnerabilities have been known for decades, but are still relevant, especially for embedded devices where certain security measures cannot be implemented due to hardware restrictions or simply due to their impact on performance. Therefore, many buffer overflow detection mechanisms check for overflows only before critical data are used. All data that an attacker could use for his own purposes can be considered critical. It is, therefore, essential that all critical data are checked between writing a buffer and its usage. This paper presents a vulnerability of the ESP32 microcontroller, used in millions of IoT devices, that is based on a pointer that is not protected by classic buffer overflow detection mechanisms such as Stack Canaries or Shadow Stacks. This paper discusses the implications of vulnerability and presents mitigation techniques, including a patch, that fixes the vulnerability. The overhead of the patch is evaluated using simulation as well as an ESP32-WROVER-E development board. We showed that, in the simulation with 32 general-purpose registers, the overhead for the CoreMark benchmark ranges between 0.1% and 0.4%. On the ESP32, which uses an Xtensa LX6 core with 64 general-purpose registers, the overhead went down to below 0.01%. A worst-case scenario, modeled by a synthetic benchmark, showed overheads up to 9.68%.
(17) On the Feasibility of Single-Trace Attacks on the Gaussian Sampler using a CDT
S. Marzougui, I. Kabin, J. Krämer, T. Aulbach, J.-P. Seifert
Proc. International Workshop on Constructive Side-Channel Analysis and Secure Design (COSADE 2023), in: Lecture Notes in Computer Science, Springer, LNCS 13979, 149 (2023)
DOI: 10.1007/978-3-031-29497-6_8, (Total Resilience)
(18) GPS-Spoofing Attack Detection Mechanism for UAV Swarms
P. Mykytyn, M. Brzozowski, Z. Dyka, P. Langendörfer
Proc. 11th International Conference on Cyber-Physical Systems and Internet-of-Things (CPS&IoT 2023), 18 (2023)
DOI: 10.1109/MECO58584.2023.10154998, (iCampus)
(19) Modular Platform for Teaching Robotics
D. Nagajek, M. Rapala, K. Woloszyn, K. Turchan, K. Piotrowski
Proc. 10th Machine Intelligence and Digital Interaction (MIDI 2022), in: Lecture Notes in Networks and Systems, Springer, LNNS 710, 167 (2023)
DOI: 10.1007/978-3-031-37649-8_17, (Space Region)
(20) Optical Fault Injection Attacks against Different Logic and Memory Cells
D. Petryk, Z. Dyka
Proc. 11th Prague Embedded Systems Workshop (PESW 2023), 24 (2023)
(Total Resilience)
(21) A Modular Communication Architecture for Adaptive UAV Swarms
K. Shahin, R. Rotta, O. Archila, P. Mykytyn, M. Nattke, M. Reichenbach, J. Nolte, R. Natarov
Proc. IEEE International Conference on Omni Layer Intelligent Systems (COINS 2023), (2023)
DOI: 10.1109/COINS57856.2023.10189245, (iCampus II)
(22) Intelligence and Motion Models of Continuum Robots: an Overview
O. Shamilyan, I. Kabin, Z. Dyka, O. Sudakov, A. Cherninsky, M. Brzozowski, P. Langendörfer
IEEE Access 11, 60988 (2023)
DOI: 10.1109/ACCESS.2023.3286300, (Total Resilience)
Many technical solutions are bio-inspired. Octopus-inspired robotic arms belong to continuum robots which are used in minimally invasive surgery or for technical system restoration in areas difficult-to-access. Continuum robot missions are bounded with their motions, whereby the motion of the robots is controlled by humans via wireless communication. In case of a lost connection, robot autonomy is required. Distributed control and distributed decision-making mechanisms based on artificial intelligence approaches can be a promising solution to achieve autonomy of technical systems and to increase their resilience. However these methods are not well investigated yet. Octopuses are the living example of natural distributed intelligence but their learning and decision-making mechanisms are also not fully investigated and understood yet. Mechanisms of Distributed Artificial Intelligence can be investigated using a physical continuum robot prototype that is able to perform some basic movements and combine them into sequences of motions by itself. For the experimental investigations a suitable physical prototype has to be selected, its motion control has to be implemented and automated. In this paper, we give an overview combining different fields of research, such as Distributed Artificial Intelligence and continuum robots based on 97 publications. We provide a detailed description of the basic motion control models of continuum robots based on the literature reviewed, discuss different aspects of autonomy and give an overview of physical prototypes of continuum robots.
(23) Successful Simple Side Channel Analysis: Vulnerability of an Atomic Pattern kP Algorithm Implemented with a Constant Time Crypto Library to Simple Electromagnetic Analysis Attacks
A.A. Sigourou, I. Kabin, P. Langendörfer, N. Sklavos, Z. Dyka
Proc. 12th Mediterranean Conference on Embedded Computing (MECO 2023), 167 (2023)
DOI: 10.1109/MECO58584.2023.10154940, (Total Resilience)
(24) AI4U: Modular Framework for AI Application Design
K. Wołoszyn, K. Turchan, M. Rąpała, K. Piotrowski
Proc. 10th Machine Intelligence and Digital Interaction (MIDI 2022), in: Lecture Notes in Networks and Systems, Springer, LNNS 710, 56 (2023)
DOI: 10.1007/978-3-031-37649-8_6, (Space Region)
