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Securing Post-Quantum Communication for Smart Grid applications

Securing Post-Quantum Communication for Smart Grid Applicati...

引用

2024 international conference on Communications Control and computing Technologies for Smart Grids

作者： Bera, Basudeb Sikdar, Biplab Natl Univ Singapore Dept Elect & Comp Engn Singapore 117583 Singapore

ISBN: (纸本)9798350318562;9798350318555

The Smart Grid (SG) represents the next-generation power system in the future grid infrastructure, designed for self-healing, adaptability, and sustainability. However, the inter-connected and geographically dispersed nature of SG systems introduces cybersecurity risks, potentially leading to severe incidents. Cyber attacks on SG applications could result in significant events, including outages and infrastructure damage. These attacks may compromise energy data, starting with the leakage of personal information from grid members. To address these risks, confidentiality, device authentication, and data integrity are essential, traditionally implemented through publickey cryptography (PKC). The rise of quantum computers and the potential adaptation of algorithms like Shor's poses a threat to PKC algorithms in SG communications. In response, we propose a security protocol for post-quantum communication in SG applications, ensuring resilience against classical and quantum attacks. The protocol has been tested through rigorous informal security analysis, and comparative analysis demonstrates its scalability and effectiveness in real-world scenarios.

关键词： Smart grid security post-quantum RLWE cyber attacks

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Multi-Resolution Planar Region Extraction for Uneven Terrains

Multi-Resolution Planar Region Extraction for Uneven Terrain...

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ieee international conference on Robotics and Automation (ICRA)

作者： Sun, Yinghan Zheng, Linfang Chen, Hua Zhang, Wei Southern Univ Sci & Technol Sch Syst Design & Intelligent Mfg Shenzhen Key Lab Control Theory & Intelligent Sys Shenzhen 518055 Peoples R China Univ Birmingham Sch Comp Sci Birmingham W Midlands England

ISBN: (纸本)9798350384581;9798350384574

This paper studies the problem of extracting planar regions in uneven terrains from unordered point cloud measurements. Such a problem is critical in various robotic applications such as robotic perceptive locomotion. While existing approaches have shown promising results in effectively extracting planar regions from the environment, they often suffer from issues such as low computational efficiency or loss of resolution. To address these issues, we propose a multi-resolution planar region extraction strategy in this paper that balances the accuracy in boundaries and computational efficiency. Our method begins with a pointwise classification preprocessing module, which categorizes all sampled points according to their local geometric properties to facilitate multi-resolution segmentation. Subsequently, we arrange the categorized points using an octree, followed by an in-depth analysis of nodes to finish multi-resolution plane segmentation. The efficiency and robustness of the proposed approach are verified via synthetic and real-world experiments, demonstrating our method's ability to generalize effectively across various uneven terrains while maintaining real-time performance, achieving frame rates exceeding 35 FPS.

关键词： Robot applications

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Input-aware accuracy characterization for approximate circuits 53

Input-aware accuracy characterization for approximate circui...

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53rd Annual ieee/IFIP international conference on Dependable systems and Networks (DSN)

作者： Piri, Ali Pappalardo, Salvatore Barone, Salvatore Barbareschi, Mario Deveautour, Bastien Traiola, Marcello O'Connor, Ian Bosio, Alberto Univ Lyon ECL INSA Lyon CNRSUMR5270UCBLCPE LyonINL F-69130 Ecully France Univ Naples Federico II Dept Elect Engn & Informat Technol Naples Italy Univ Rennes INRIA CNRS UMR6074IRISA Rennes France

ISBN: (纸本)9798350325430

It has been a while since Approximate computing (AxC) is applied systematically at various abstraction levels to increase the efficiency of several applications such as image processing and machine learning. Despite its benefit, AxC is still agnostic concerning the specific workload (i.e., input data to be processed) of a given application. For instance, in signal processing applications (such as a filter), some inputs are constants (filter coefficients). Meaning that a further level of approximation can be introduced by considering the specific input distribution. This approach has been referred to as "input-aware approximation". In this paper, we explore how the input-aware approximate design approach can become part of a systematic, generic, and automatic design flow by knowing the data distribution. In particular, we show how input distribution can affect the error characteristics of an approximate arithmetic circuit and also the advantage of considering the data distribution by designing an input-aware approximate multiplier specifically intended for a high-pass FIR filter, where the coefficients are constant. Experimental results show that we can significantly reduce power consumption while keeping an error rate lower than state-of-the-art approximate multipliers.

关键词： Approximate computing Energy Efficiency embedded systems Input-Aware Approximation

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Improving Autonomous Driving via Recommendation systems: A Review 21

Improving Autonomous Driving via Recommendation Systems: A R...

引用

2024 ieee/ACS 21st international conference on Computer systems and applications, AICCSA 2024

作者： Ben-Aoun, Sameh Belguidoum, Meriem Hadj-Kacem, Ahmed University of Sfax ReDCAD Laboratory Sfax3018 Tunisia University of Constantine 2 LIRE Laboratory Constantine Algeria

ISBN: (纸本)9798331518240

Artificial intelligence has transformed the automotive industry, giving rise to safer and more comfortable semi-Autonomous vehicles. This review evaluates the critical role of recommendation systems in the development of autonomous driving and compares them to advanced driver assistance systems (ADAS). These systems go above and beyond typical ADAS by providing personalized driving experiences, enhancing route planning based on real-time data, and enhancing driver comfort and safety through proactive actions. The main objective of this review is to critically analyze and explain different approaches to recommendation systems for autonomous vehicles based on their algorithms, data sources, strengths, and weaknesses. This review focuses specifically on the role of personalization technologies in adapting the driver assistant to his or her individual preferences and vehicle environment data. Our analysis highlights key challenges and opportunities for future research, including addressing data limitations and evaluating system performance in complex real-world scenarios. © 2024 ieee.

关键词： Advanced driver assistance systems

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Parking Lots Management and Visualization in the Smart City - Digital Twin context

Parking Lots Management and Visualization in the Smart City ...

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2023 ieee international conference on Metaverse computing, Networking and applications, MetaCom 2023

作者： Shrivastav, Chinmay Satish Masola, Alessio Capodieci, Nicola Cavicchioli, Roberto University of Parma Parma Italy University of Modena and Reggio Emilia Reggio Emilia Modena Italy

ISBN: (纸本)9798350333336

In recent years, extensive research has been conducted to develop traffic surveillance and monitoring applications using advanced technologies in a Smart-City context. One of the fundamental challenges in an urban city scenario is developing an efficient yet affordable parking lot management system. Such systems play a crucial role in providing the necessary data to local municipalities to make informed decisions to better manage the traffic flow while saving valuable resources and time. In this paper, we propose a novel end-to-end system architecture for a real-time video-based parking management system that can be easily scaled and enforced in a Smart-City context. Using state-of-the-art object detection and tracking methods combined with novel Static Object Detection techniques, we demonstrate a localized strategy for identifying potential parking spaces. A separate parking occupancy classification pipeline is discussed which provides fast and accurate availability status of these parking spaces. Furthermore, a 3D digital-twin application to monitor and visualize the parking spaces is demonstrated. Our experiments in a real-world scenario demonstrate the significant potential of our proposed architecture to easily scale to a given city with minimal manual efforts and lower implementation costs. © 2023 ieee.

关键词： 5G mobile communication systems

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Do We Run Large-scale Multi-Robot systems on the Edge? More Evidence for Two-Phase Performance in System Size Scaling

Do We Run Large-scale Multi-Robot Systems on the Edge? More ...

引用

ieee international conference on Robotics and Automation (ICRA)

作者： Kuckling, Jonas Luckey, Robin Avrutin, Viktor Vardy, Andrew Reina, Andreagiovanni Hamann, Heiko Univ Konstanz Dept Comp & Informat Sci D-78457 Constance Germany Univ Konstanz Ctr Adv Study Collect Behav Constance Germany Univ Lubeck Inst Comp Engn Lubeck Germany Univ Stuttgart Inst Syst Theory & Automat Control Stuttgart Germany Mem Univ Newfoundland Dept Comp Sci St John NL Canada Mem Univ Newfoundland Dept Elect & Comp Engn St John NL Canada Univ Libre Bruxelles IRIDIA Brussels Belgium

ISBN: (纸本)9798350384581;9798350384574

With increasing numbers of mobile robots arriving in real-world applications, more robots coexist in the same space, interact, and possibly collaborate. Methods to provide such systems with system size scalability are known, for example, from swarm robotics. Example strategies are self-organizing behavior, a strict decentralized approach, and limiting the robot-robot communication. Despite applying such strategies, any multi-robot system breaks above a certain critical system size (i.e., number of robots) as too many robots share a resource (e.g., space, communication channel). We provide additional evidence based on simulations, that at these critical system sizes, the system performance separates into two phases: nearly optimal and minimal performance. We speculate that in real-world applications that are configured for optimal system size, the supposedly high-performing system may actually live on borrowed time as it is on a transient to breakdown. We provide two modeling options (based on queueing theory and a population model) that may help to support this reasoning.

关键词： Multipurpose robots

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Compressing VAE-Based Out-of-Distribution Detectors for embedded Deployment

Compressing VAE-Based Out-of-Distribution Detectors for Embe...

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ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Aditya Bansal Michael Yuhas Arvind Easwaran College of Computing and Data Science Nanyang Technological University Singapore Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore

ISBN: (数字)9798350387957

ISBN: (纸本)9798350387964

Out-of-distribution (OOD) detectors can act as safety monitors in embedded cyber-physical systems by identifying samples outside a machine learning model’s training distribution to prevent potentially unsafe actions. However, OOD detectors are often implemented using deep neural networks, which makes it difficult to meet real-time deadlines on embedded systems with memory and power constraints. We consider the class of variational autoencoder (VAE) based OOD detectors where OOD detection is performed in latent space, and apply quantization, pruning, and knowledge distillation. These techniques have been explored for other deep models, but no work has considered their combined effect on latent space OOD detection. While these techniques increase the VAE’s test loss, this does not correspond to a proportional decrease in OOD detection performance and we leverage this to develop lean OOD detectors capable of real-time inference on embedded CPUs and GPUs. We propose a design methodology that combines all three compression techniques and yields a significant decrease in memory and execution time while maintaining AUROC for a given OOD detector. We demonstrate this methodology with two existing OOD detectors on a Jetson Nano and reduce GPU and CPU inference time by 20% and 28% respectively while keeping AUROC within 5% of the baseline.

关键词： Training Quantization (signal) embedded systems Memory management Graphics processing units Detectors Machine learning real-time systems Safety Monitoring

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Online Handwriting Recognition using LSTM on Microcontroller and IMU Sensors 21

Online Handwriting Recognition using LSTM on Microcontroller...

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21st ieee international conference on Machine Learning and applications (ieee ICMLA)

作者： Meissl, Florian Eibensteiner, Florian Petz, Phillip Langer, Josef Univ Appl Sci Upper Austria Res & Dev Embedded Syst Lab Hagenberg Austria

ISBN: (纸本)9781665462839

The trend toward the Internet of Things has led to a rapid increase in the amount of data that needs to be processed. Artificial intelligence (AI) can serve as a very helpful tool to extract or compress essential information of data. However, AI places high demands on a system's hardware. This is not exactly in line with the strengths of embedded systems. This paper combines AI on embedded systems with the not-yet fully explored subject of online handwriting recognition (HWR). The main contribution is the deployment and real-time operation of AI on a microcontroller (MCU). Model architectures using long short-term memory (LSTM) cells and 1D convolutional neural networks (CNNs) are used to process live data from inertial measurement units (IMUs) sensors. The dataset used for training the AI models was recorded with a self-developed prototype. After training, the models are converted and deployed on a MCU. The conversion process includes quantization from a 32-bit floating-point to an 8-bit fixed-point datatype. The TensorFlow Lite Micro (TFLM) framework is used to run inference on the MCU. For predictions in real-time optimizations are applied to the framework, which results in running inference approx. 827 times faster. The optimized AI model implementation is then used to classify handwritten characters using the live data from the IMU sensors. This first approach has shown, that the separation of the symbols is necessary to be able to classify characters from live sensor data with high accuracy.

关键词： Online Handwriting Recognition Microcontroller IMU Sensor Edge computing LSTM Machine Learning

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Highly Responsive Batteryless System for Indoor Light Energy Harvesting Environments 21

Highly Responsive Batteryless System for Indoor Light Energy...

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21st ieee international conference on Pervasive computing and Communications (PerCom)

作者： Kim, Daeyong Ahn, Junick Lee, Hakjun Cha, Hojung Yonsei Univ Dept Comp Sci Seoul South Korea

ISBN: (纸本)9781665453783

Energy-neutral operation (ENO) aims to provide near-perpetual device operation using energy harvested from ambient environments. Existing ENO techniques, however, have two key problems. The batteries used in harvesting devices have inherently limited lifespans, and the device experiences a long cold-start time when charging the battery. In this paper, we propose a long-lasting and highly responsive batteryless system, called RENO, to solve the problems that occur in energy harvesting devices. Using a supercapacitor to store energy, RENO maximizes the responsiveness in ENO especially running in dynamic harvesting environments such as indoor light energy harvesting. Combining the intermittent characteristics of powerneutral operation (PNO), RENO allows dual-mode operation of PNO and ENO, depending on the current harvesting capability. The device works as a PNO device when charging the energy storage, solving the ENO cold-start issue, while the harvested energy is efficiently managed with ENO. For this dual-mode operation, RENO provides hardware and software that handle the switch between PNO and ENO effectively. Application developers are provided with a well-defined API, which enables energy-efficient development of applications without detailed knowledge of the target hardware. Using the API, developers simply declare a task to be executed as either PNO or ENO, and the rest is handled by the system. The prototype system is implemented, and its functionality is evaluated in controlled environments. We also validate the proposed system with two real-world applications, proving the efficacy of dual-mode batteryless operation.

关键词： Batteryless systems energy-harvesting

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Distributed Control Application for Smart Grids using RIAPS 9

Distributed Control Application for Smart Grids using RIAPS

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ieee international conference on Smart computing (SMARTCOMP)

作者： Ghosh, Purboday Barua, Niloy Krentz, Timothy Karsai, Gabor Dubey, Abhishek Lukic, Srdjan Vanderbilt Univ Inst Software Integrated Syst 221 Kirkland Hall Nashville TN 37235 USA North Carolina State Univ FREEDM Syst Ctr Raleigh NC USA

ISBN: (纸本)9798350322811

The integration of computational capabilities with the electrical infrastructure of the grid can be envisioned as a societal scale Cyber Physical System (CPS). Middleware frameworks can act as a layer of abstraction that manages the interaction between disparate applications to facilitate intelligent control and management of energy production and consumption. This demonstration showcases Resilient Information Architecture Platform for Smart Grid (RIAPS), a distributed software platform that combines a domain specific modeling language with framework-level services such as communication, remote deployment of applications, distributed coordination, time synchronization, and fault tolerance, to develop and run distributed applications. An example of an energy demand curtailment scheme called load shedding is presented, to highlight how the RIAPS framework can be used to implement distributed algorithms to control elements of a power system, which runs as a simulation using OpenDSS.

关键词： component distributed systems smart grid cyber pysical system opendss simulation load shedding middleware

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