Accuracy of computation for Sommerfeld integrals is examined for applications to microstrip geometries. In a numerical approach proposed earlier, the influence of the singularities in the integrand is obviated by defo...
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This study presents the application of Faster RCNN, a popular Region Based Convolutional Neural Network, for detecting hyperbolic patterns in Ground Penetrating Radar (GPR) images. GPR is an important tool for subsurf...
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Transport systems are fundamental to supporting economic growth, and the need for smarter, safer, more efficient and climate neutral transport systems continues to grow. Maintenance and operation of transport infrastr...
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Operating Systems enforce logical isolation using abstractions such as processes, containers, and isolation tech-nologies to protect a system from malicious or buggy code. In this paper, we show new types of side chan...
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ISBN:
(数字)9798331522360
ISBN:
(纸本)9798331522377
Operating Systems enforce logical isolation using abstractions such as processes, containers, and isolation tech-nologies to protect a system from malicious or buggy code. In this paper, we show new types of side channels through the file system that break this logical isolation. The file system plays a critical role in the operating system, managing all I/O activities between the application layer and the physical storage device. We observe that the file system implementation is shared, leading to timing leakage when using common I/O system calls. Specifically, we found that modern operating systems take advantage of any flush operation (which saves cached blocks in memory to the SSD or disk) to flush all of the I/O buffers, even those used by other isolation domains. Thus, by measuring the delay of syncfs, the attacker can infer the I/O behavior of victim programs. We then demonstrate a syncfs covert channel attack on multiple file systems, including both Linux native file systems and the Windows file system, achieving a maximum bandwidth of 5 Kbps with an error rate of 0.15% on Linux and 7.6 Kbps with an error rate of 1.9% on Windows. In addition, we construct three side-channel attacks targeting both Linux and Android devices. On Linux devices, we implement a website fingerprinting attack and a video fingerprinting attack by tracking the write patterns of temporary buffering files. On Android devices, we design an application fingerprinting attack that leaks application write patterns during boot-up. The attacks achieve over 90% F1 score, precision, and recall. Finally, we demonstrate that these attacks can be exploited across containers implementing a container detection technique and a cross-container covert channel attack.
The growing integration of Distributed Energy Resources (DERs) into modern power grids, managed via DER Management Systems (DERMS), has introduced significant cybersecurity challenges. Communication vulnerabilities in...
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ISBN:
(数字)9798331520182
ISBN:
(纸本)9798331520199
The growing integration of Distributed Energy Resources (DERs) into modern power grids, managed via DER Management Systems (DERMS), has introduced significant cybersecurity challenges. Communication vulnerabilities in DERMS architecture create opportunities for adversarial attacks, such as Man-in-the-Middle (MITM), that intercept and manipulate critical data flows, disrupting grid operations and compromising reliability. This paper investigates MITM attacks targeting three critical nodes in DER-DERMS communication: (i) DER gateway routers, (ii) inter-router pathways, and (iii) DERMS gateway routers. To analyze these vulnerabilities, we developed CPS-DERMS, a multi-co-simulation hardware-in-the-loop testbed integrating grid-side simulations with OPAL-RT, large-scale cyber simulations using NS-3, and an indige-nous Python-based DERMS platform. The study demonstrates innovative strategies for executing MITM attacks, including maintaining payload integrity and bypassing detection mechanisms, while highlighting the critical vulnerabilities within DER-DERMS communication systems. We considered a real utility's DER-integrated distribution grid as a case study. Experimental results reveal that MITM attacks can cause overvoltages, reactive power imbalances, and increased tap-changer operations, significantly degrading power quality and grid reliability.
Nowadays, unmanned aerial vehicles (UAVs) are increasingly utilized in search and rescue missions, a trend driven by technological advancements, including enhancements in automation, avionics, and the reduced cost of ...
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Imitation learning mitigates the resource-intensive nature of learning policies from scratch by mimicking expert behavior. While existing methods can accurately replicate expert demonstrations, they often exhibit unpr...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
Imitation learning mitigates the resource-intensive nature of learning policies from scratch by mimicking expert behavior. While existing methods can accurately replicate expert demonstrations, they often exhibit unpredictability in unexplored regions of the state space, thereby raising major safety concerns when facing perturbations. We propose SNDS, an imitation learning approach aimed at efficient training of scalable neural policies while formally ensuring global stability. SNDS leverages a neural architecture that enables the joint training of the policy and its associated Lyapunov candidate to ensure global stability throughout the learning process. We validate our approach through extensive simulations and deploy the trained policies on a real-world manipulator arm. The results confirm SNDS’s ability to address instability, accuracy, and computational intensity challenges highlighted in the literature, positioning it as a promising solution for scalable and stable policy learning in complex environments.
Natural language understanding models often make use of surface patterns or idiosyncratic biases in a given dataset to make predictions pertaining to natural language inference (NLI) tasks. Unfortunately, this renders...
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Data transfer from underwater acoustic sensor networks (UASNs) to cloud services is challenging due to the severe bandwidth constraints of acoustic communication and energy consumption constraints of battery-powered s...
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Data transfer from underwater acoustic sensor networks (UASNs) to cloud services is challenging due to the severe bandwidth constraints of acoustic communication and energy consumption constraints of battery-powered sensor devices. To mitigate this problem, various forms of time series compression algorithms, both lossless and lossy, have been proposed in the literature. These proposals, however, focus on large time series whose in-memory buffering is not feasible in a UASN context. Furthermore, especially in oceanographic data acquisition, buffering large time series sacrifices the Age of Information. To address this gap, we evaluate a modern lossy compression algorithm, Mix-Piece, on small-sized time series. Motivated by our findings, we have developed the Custom-Piece algorithm, an adaptation of Mix-Piece that yields higher data compression at the expense of increased execution times. Our experimental evaluation of the Mix-Piece/Custom-Piece algorithms on real-world oceanographic data shows that compression ratios are highly dependent on the configuration of the algorithms due to the emerging characteristics of the underlying data sets. To facilitate practical use of the Mix-Piece/Custom-Piece algorithms, we outline how a digital twin may dynamically run simulations on available past data to support end-users in developing sensor configurations according to data acquisition requirements.
Recently, a considerable number of investigations on deep learning methodologies for early identification of Alzheimer's disease (AD) have been reported in the literature. For accurate diagnosis, the currently use...
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