Using look up table content as signatures to identify IP cores in modern FPGAs. - In: Architecture of computing systems, (2022), S. 132-147
The increasing amount of logic resources in FPGA architectures has enabled the realization of larger and more complex designs. Today, most of the large-scale designs rely heavily on off-the-shelf Intellectual Property Cores (IP Cores) to ease their development. This dependency raises an important issue: the unlicensed use of IP Cores. In this paper, we utilize LUT contents, which represent the functionality of an IP Core, as a signature to determine if a core might be part of an accused design. For this, we present a technique to reconstruct the contained LUT contents from modern FPGA configurations which not only contain 6-input one-output LUTs but also 5-input two-output LUTs. By making use of LUT decomposition together with a fast Boolean matching algorithm, we consolidate the work for commercial architectures. The proposed method is evaluated using 8 IP Cores to find in 4 different designs using two different architectures. Our findings show a 100% identification rate with no false-positives or false-negatives for all experiments carried out. Especially the presence of larger cores can be established with a difference of at least 10% between true and false positives.
https://doi.org/10.1007/978-3-031-21867-5_9
Putting IMT to the test: revisiting and expanding interval matching techniques and their calibration for SCA. - In: ASHES '22, (2022), S. 65-74
Side-Channel Analysis (SCA) requires the detection of the specific time frame Cryptographic Operations (COs) take place in the side-channel signal. Under laboratory conditions with full control over the Device under Test (DuT), dedicated trigger signals can be implemented to indicate the start and end of COs. For real-world scenarios, waveform-matching techniques have been established which compare the side-channel signal with a template of the CO's pattern in real time to detect the CO in the side channel. State-of-the-Art approaches describe implementations based on Field-Programmable Gate Arrays (FPGAs). However, the maximal length of the template is restricted by the resources available on an FPGAs. Particularly, for high sampling rates the recording of an entire CO may need more samples than the maximum template length supported by a waveform-matching system. Consequently, the template has to be reduced such that it fits the resources while still containing all features relevant for detecting the COs via waveform matching. In this paper, we introduce a generic interval-matching technique which provides several degrees of freedom for fine-tuning it to the statistical deviations of waveform measurements of COs. Moreover, we introduce a novel calibration method that finds the best parameters automatically based on statistical analysis of training data. Furthermore, we investigate a technique to reduce the number of features used for the interval matching by utilizing machine-learning-based feature extraction to find the most important samples in a template. Finally, we evaluate the state-of-the-art interval matching and our expansions during calibration and during the application on a test set. The results show, that a reliable reduction to 10% of the original template size is possible with a reduction method from literature for our example. However, the combination of our proposed methods can reliably work with only 1.5% of the original size and is less volatile than the state-of-the-art approach for reducing the number of features.
https://doi.org/10.1145/3560834.3563828
Robust tracking control with £1 adaptive augmentation for a long-stroke vertical nanopositioning system: part II. - In: 2022 IEEE Conference on Control Technology and Applications (CCTA), (2022), S. 621-627
In this paper and its companion paper [1], we address the problem of modeling and robust adaptive tracking control for an overactuated vertical nanopositioning system. In virtue of the derived model, the control is accomplished via a composite control law involving a nominal full-state feedback controller plus an L1 adaptive augmentation. To pre-serve PID-type robustness properties, the nominal (or baseline) controller comprises integral action and features sufficiently high bandwidth for mere stabilization and attenuation of slowly varying disturbances. The L1 adaptive component plays a central role for recovering the nominal closed-loop dynamics in the presence of complex time-varying perturbations and external disturbances. The effectiveness and robustness of the presented control strategy is verified via real-time experiments featuring subnanometer positioning errors which seem to be fully-dominated by the measurement noise.
https://doi.org/10.1109/CCTA49430.2022.9965993
Robust tracking control with £1 adaptive augmentation for a long-stroke vertical nanopositioning system: part I. - In: 2022 IEEE Conference on Control Technology and Applications (CCTA), (2022), S. 614-620
In this paper and its companion paper [1], we address the problem of modeling and robust adaptive tracking control for an overactuated vertical nanopositioning system. We first introduce the operation principle of the lifting modules. In relation to the integrated actuators, their dynamics and important parameters are obtained from experimental and projected data. We further derive a physical model from the relevant components of the motion system. The model is validated with measured data in order to illustrate that it adequately reflects the real behavior. Emphasis is placed on the merits of control allocation (CA) to handle the overactuated nature of the overall motion system. The proposed CA concept proves to be effective for the ongoing application since it demands low computational costs and fulfills the heat emission constraint. We close this paper with the formulation and analysis of a suitable model for the derivation of advanced control strategies.
https://doi.org/10.1109/CCTA49430.2022.9966103
Design and error analysis of accuracy-configurable sequential multipliers via segmented carry chains. - In: Information technology, ISSN 2196-7032, Bd. 64 (2022), 3, S. 89-98
We present the design and a closed-form error analysis of accuracy-configurable multipliers via segmented carry chains. To address this problem, we model the approximate partial-product accumulations as a sequential process. According to a given splitting point of the carry chains, the technique herein discussed allows varying the quality of the accumulations and, consequently, the overall product. Due to these shorter critical paths, such kinds of approximate multipliers can trade-off accuracy for an increased performance whilst exploiting the inherent area savings of sequential over combinatorial approaches. We implemented multiple architectures targeting FPGAs and ASICs with different bit-widths and accuracy configurations to 1) estimate resources, power consumption, and delay, as well as to 2) evaluate those error metrics that belong to the so-called #P-complete class.
https://doi.org/10.1515/itit-2021-0040
Bandwidth-optimal relational joins on FPGAs. - Konstanz : University of Konstanz. - 1 Online-Ressource (Seite 1:27-1:39)Online-Ausgabe: Proceedings of the 25th International Conference on Extending Database Technology, EDBT 2022, Edinburgh, UK, March 29 - April 1, 2022. - OpenProceedings.org 2022, ISBN 978-3-89318-086-8
https://doi.org/10.5441/002/edbt.2022.03
Cornucopia: tool support for selecting machine learning lifecycle artifact management systems. - Setúbal : Scitepress. - 1 Online-Ressource (Seite 444-450)Online-Ausgabe: Proceedings of the 18th International Conference on Web Information Systems and Technologies, WEBIST, October 25-27, 2022, in Valletta, Malta / editors: Stefan Decker ... - Setúbal : Scitepress, 2022, ISBN 978-989-758-613-2
The explorative and iterative nature of developing and operating machine learning (ML) applications leads to a variety of ML artifacts, such as datasets, models, hyperparameters, metrics, software, and configurations. To enable comparability, traceability, and reproducibility of ML artifacts across the ML lifecycle steps and iterations, platforms, frameworks, and tools have been developed to support their collection, storage, and management. Selecting the best-suited ML artifact management systems (AMSs) for a particular use case is often challenging and time-consuming due to the plethora of AMSs, their different focus, and imprecise specifications of features and properties. Based on assessment criteria and their application to a representative selection of more than 60 AMSs, this paper introduces an interactive web tool that enables the convenient and time-efficient exploration and comparison of ML AMSs.
https://doi.org/10.5220/0011591700003318
Raw filtering of JSON data on FPGAs. - In: Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE 2022), (2022), S. 250-255
https://doi.org/10.23919/DATE54114.2022.9774696
Towards more effective identification keys: a study of people identifying plant species characters. - In: People and nature, ISSN 2575-8314, Bd. 4 (2022), 6, S. 1603-1615
Accurate species identification is essential for ecological monitoring and biodiversity conservation. Interactive plant identification keys have been considerably improved in recent years, mainly by providing iconic symbols, illustrations, or images for the users, as these keys are also commonly used by people with relatively little plant knowledge. Only a few studies have investigated how well morphological characteristics can be recognized and correctly identified by people, which is ultimately the basis of an identification key's success. This study consists of a systematic evaluation of people's abilities in identifying plant-specific morphological characters. We conducted an online survey where 484 participants were asked to identify 25 different plant character states on six images showing a plant from different perspectives. We found that survey participants correctly identified 79% of the plant characters, with botanical novices with little or no previous experience in plant identification performing slightly worse than experienced botanists. We also found that flower characters are more often correctly identified than leaf characteristics and that characters with more states resulted in higher identification errors. Additionally, the longer the time a participant needed for answering, the higher the probability of a wrong answer. Understanding what influences users' plant character identification abilities can improve the development of interactive identification keys, for example, by designing keys that adapt to novices as well as experts. Furthermore, our study can act as a blueprint for the empirical evaluation of identifications keys. Read the free Plain Language Summary for this article on the Journal blog.
https://doi.org/10.1002/pan3.10405
Methods and tools of video monitoring for remote laboratory. - In: Building bridges towards responsible smart cities, (2022), S. 184-189
The ability to monitor the progress of online experiments using a video monitoring system is one of the most important advantages of remote laboratories. In this case, special requirements are imposed on the capture area, quality and degree of image details. Therefore, the further development of methods and tools of capturing, broadcasting, receiving and displaying video images to improve the quality of educational services provided by a remote laboratory is an urgent task. In the course of the work, technologies for capturing and processing video images, implementing wireless protocols for receiving (commands, requests) and transmitting data (images), as well as architectural features, principles of software implementation and operation of video monitoring systems are investigated and realized. The developed system provides the ability to organize video monitoring for remote experiments observing and fixing. Thus, students receive the fullest information and data streaming provides the effect of physical presence at the site of the experiment. The hardware/software complex is developed on the basis of ESP-32 and ESP-32-CAM modules, as well as Wi-Fi, HTTP and WebSocket protocols. The ability to update the developed software is implemented using the OtaDrive cloud service. This makes it easier and faster to deploy and test new software. The main advantages of the proposed solution are ease of assembly, customization, availability of components, the possibility of easy modernization of both hardware and software parts of the complex, low power consumption. It has low cost, which ensures availability even for small educational laboratories. The practical value of the work lies in the fact that the created software/hardware complex can be used to organize effective video monitoring of experiments in remote laboratories, as well as for other video surveillance systems in various fields.
https://doi.org/10.1109/E-TEMS53558.2022.9944406