This work addresses submodular maximization problems, a widely-used mathematical tool to model many real-world decisions. Though this set of problems is NP-Hard, a well-known result is that a distributed greedy algori...
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Programmable logic controllers (PLCs) are crucial devices for implementing automated control in various industrial controlsystems (ICS), such as smart power grids, water treatment systems, manufacturing, and transpor...
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ISBN:
(纸本)9798400704826
Programmable logic controllers (PLCs) are crucial devices for implementing automated control in various industrial controlsystems (ICS), such as smart power grids, water treatment systems, manufacturing, and transportation systems. Owing to their importance, PLCs are often the target of cyber attackers that are aiming at disrupting the operation of ICS, including the nation's critical infrastructure, by compromising the integrity of control logic execution. While a wide range of cybersecurity solutions for ICS have been proposed, they cannot counter strong adversaries with a foothold on the PLC devices, which could manipulate memory, I/O interface, or PLC logic itself. These days, many ICS devices in the market, including PLCs, run on ARM-based processors, and there is a promising security technology called ARM TrustZone, to offer a Trusted Execution Environment (TEE) on embedded devices. Envisioning that such a hardware-assisted security feature becomes available for ICS devices in the near future, this paper investigates the application of the ARM TrustZone TEE technology for enhancing the security of PLC. Our aim is to evaluate the feasibility and practicality of the TEE-based PLCs through the proof-of-concept design and implementation using open-source software such as OP-TEE and OpenPLC. Our evaluation assesses the performance and resource consumption in real-world ICS configurations, and based on the results, we discuss bottlenecks in the OP-TEE secure OS towards a large-scale ICS and desired changes for its application on ICS devices. Our implementation is made available to public for further study and research.
As we move towards the era of 6G and IoE (Internet of Everything), there is more and more seamless interconnection and interaction among things, people, data, and processes in one intelligent network. In IoE, whether ...
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ISBN:
(纸本)9798350319439
As we move towards the era of 6G and IoE (Internet of Everything), there is more and more seamless interconnection and interaction among things, people, data, and processes in one intelligent network. In IoE, whether 5G or 6G, the ecosystem embodies a plethora of connected devices and people, user-context heterogeneity, and fully distributed interactions, adding up to a highly complex ecosystem. The 5G will increase cellular bandwidth by huge amounts, making it much easier for the IoE to network large numbers of devices together. Adaptation to the right situational context, especially when it comes to security and protection has become a key requirement for IoE and other complex ecosystems. Especially the Access control (AC) part is required to be robust, scalable, and resilient (from a security point of view). A dynamic, context-aware security with a breakout from the traditional statically mapped roles and mechanisms is essential today. Robust authentication can be achieved for IoT and IoE using a technique called Device Fingerprinting (DF) that we thoroughly investigate in this paper. We look at the mechanism itself, where and how it applies, and how Access control (AC) works and scales with DF. We also model the DF generation process and look at different cases with different devices, and the respective overhead incurred by DF compared to the payload as well as the security overhead incurred for different frame sizes and devices as a percentage of the overall traffic (DF and payload combined). All models and assessments provided serve as a basis for future publications based on the continuous ongoing work we are doing in this area.
PurposeAs technology advances, more research dedicated to medical interactive systems emphasizes the integration of touchless and multimodal interaction (MMI). Particularly in surgical and interventional settings, thi...
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PurposeAs technology advances, more research dedicated to medical interactive systems emphasizes the integration of touchless and multimodal interaction (MMI). Particularly in surgical and interventional settings, this approach is advantageous because it maintains sterility and promotes a natural interaction. Past reviews have focused on investigating MMI in terms of technology and interaction with robots. However, none has put particular emphasis on analyzing these kind of interactions for surgical and interventional *** databases were included in the query to search for relevant publications within the past 10 years. After identification, two screening steps followed which included eligibility criteria. A forward/backward search was added to identify more relevant publications. The analysis incorporated the clustering of references in terms of addressed medical field, input and output modalities, and challenges regarding the development and *** sample of 31 references was obtained (16 journal articles, 15 conference papers). MMI was predominantly developed for laparoscopy and radiology and interaction with image viewers. The majority implemented two input modalities, with voice-hand interaction being the most common combination-voice for discrete and hand for continuous navigation tasks. The application of gaze, body, and facial control is minimal, primarily because of ergonomic concerns. Feedback was included in 81% publications, of which visual cues were most often *** work systematically reviews MMI for surgical and interventional scenarios over the past decade. In future research endeavors, we propose an enhanced focus on conducting in-depth analyses of the considered use cases and the application of standardized evaluation methods. Moreover, insights from various sectors, including but not limited to the gaming sector, should be exploited.
Power quality upgrade in grid-connected photovoltaic systems ensures stable and highly efficient operation of modern energy grids. Meanwhile, the high penetration of renewable energy sources brings real challenges to ...
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Authorities' reactive approach to water quality issues and infrastructure can cause delays. Predicting future complaints based on environmental factors can help to improve infrastructure and prevent complaints. It...
Remote keyless entry (RKE) systems have become a standard feature in modern vehicles, offering the convenience of wireless control. However, this convenience is accompanied by significant security vulnerabilities, par...
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In this paper, a method of fusing distance information and camera data is presented, the objective being that of combining LIDAR measurements with the output of a segmentation neural network, applied on the merged ima...
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This paper addresses the problem of mobile robot manipulation using object detection. Our approach uses detection and control as complimentary functions that learn from real-world interactions. We develop an end-to-en...
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ISBN:
(纸本)9781665493468
This paper addresses the problem of mobile robot manipulation using object detection. Our approach uses detection and control as complimentary functions that learn from real-world interactions. We develop an end-to-end manipulation method based solely on detection and introduce Task-focused Few-shot Object Detection (TFOD) to learn new objects and settings. Our robot collects its own training data and automatically determines when to retrain detection to improve performance across various subtasks (e.g., grasping). Notably, detection training is low-cost, and our robot learns to manipulate new objects using as few as four clicks of annotation. In physical experiments, our robot learns visual control from a single click of annotation and a novel update formulation, manipulates new objects in clutter and other mobile settings, and achieves state-of-the-art results on an existing visual servo control and depth estimation benchmark. Finally, we develop a TFOD Benchmark to support future object detection research for robotics: https://***/griffbr/TFOD.
This paper brings the concept of 'optimism' to the new and promising framework of online Non-stochastic control (NSC). Namely, we study how NSC can benefit from a prediction oracle of unknown quality responsib...
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