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PhantomPatch: Easy-ignoring Attacks on Object Detectors Using Ghosting Artifacts 22

PhantomPatch: Easy-ignoring Attacks on Object Detectors Usin...

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22nd IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Guo, Xiaolong Yao, Qingsong Li, Jingwei Dong, Xuewen Ma, Jianfeng Xidian University School of Cyber Engineering Xi'an China Xidian University State Key Lab of Isn School of Telecommunications Engineering Xi'an China Xidian University School of Computer Science and Technology Xi'an China

ISBN: (纸本)9798331509712

Current patches used to attack object detectors are easily noticeable as abnormal. To mitigate this shortcoming, we devise an innovative technique named PhantomPatch, which leverages lens flare phenomena to attack object detectors, particularly in autonomous driving systems. Leveraging transfer-based adversarial examples, this method fools object detectors by projecting deceptive lens flares or ghost images, which are meaningless to people, while the light source looks like nearby light for people. Thus, it is easy to *** this way, we enable a cost-effective approach to manipulate the perception of the vehicle remotely. This strategy harmonizes adversarial patches with projecting image integrity correcting. Firstly, we propose to train a black-box transfer-based adversarial patch to fool the object-detecting system behind the camera. Then, the patch is printed and attached in front of a flashlight, which casts the patch onto the camera, resulting in a ghost image. We maintain the integrity of the image captured by the camera while casting the patch with image loss correction and optical distortion *** experimental results validate the effectiveness of PhantomPatch in evading existing object detectors such as YOLO V3/V5 and Faster R-CNN. Notably, during nocturnal scenarios, the technique achieves a success rate of 98.2%. Furthermore, our approach addresses limitations of existing methods, like conspicuousness and positional constraints, offering a low-cost and effective technique for adversarial attacks, especially for autonomous vehicles. Code and demo are available at https://***/rufus0803/PhantomPatch. © 2024 IEEE.

关键词： Phantoms

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Optimization and Energy Management of Microgrid Considering Demand Response

Optimization and Energy Management of Microgrid Considering ...

引用

2024 international Conference on Futuristic Technologies in Control systems and Renewable Energy, ICFCR 2024

作者： Nesihath, M.K. Aneesha, M.V. Nafeesa, K. Sreedharan, Sasidharan Mes College of Engineering Kuttippuram Apj Abdul Kalam Technological University Dept. of Eee Kerala India Mes College of Engineering Kuttippuram Apj Abdul Kalam Technological University Dept. of Cse Kerala India

ISBN: (数字)9798331504601

ISBN: (纸本)9798331504601

Microgrid is a self-sufficient energy system that provides power to a specific geographic area, such as neighborhood, business center, hospital complex, or college campus. It can connect and disconnect from the grid to operate in grid-connected or island mode. This is a hybrid system in which several distributed Energy Resources (DERs) are connected in parallel, including a photovoltaic system, a wind turbine, an energy storage system and a diesel generator. It is also connected to the utility grid. Optimization and energy management of microgrid considering demand response is an effective component size optimization as well as cost reduction technique implemented by reducing or eliminating the mismatch between the generation and consumption profiles by time shift and schedule of dispatchable loads. The optimization of standalone system with and without demand response program was done by using Homer PRO software and that of grid connected system by using HOMER GRID software where wind speed and solar radiant data taken from NASA's meteorological department. The effectiveness of demand response program was checked in both systems by calculating the net present cost and CO2 emission. Standalone microgrid gives promising results considering CO2 emission and Grid connected system gives better results considering net present cost. © 2024 IEEE.

关键词： Demand response

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Massive Natural Language Processing in distributed Environment 20th

Massive Natural Language Processing in Distributed Environm...

引用

20th international symposium on distributed Computing and Artificial Intelligence, DCAI 2023

作者： Krechowicz, Adam Faculty of Electrical Engineering Automatic Control and Computer Science Kielce University of Technology Kielce Poland

ISBN: (纸本)9783031383175

Natural Language Processing (NLP) models are one of the most promising topics nowadays. Applications like ChatGPT uncover the power of such models and their broad applications. However, developing such models requires an extensive amount of training data sets to operate on. As such data sets grow, it becomes impossible to process them on a single machine, even using parallel computations. In this paper, the problem of distributing the NLP computations is taken into consideration. The Scalable distributed Two-Layer Data Structures were used to organize the distributed environment. Stanford Core NLP library was used to perform accurate NLP computations. The experiments focused on the efficiency of the computation in the distributed environment and the accuracy of the predictions in relation to the scale of the distributions. The results clearly show that an increase in performance can be obtained without a significant decrease in accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Natural language processing systems

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Simulation and implementation of local electrical markets in photovoltaic energy communities with PVLEM 10

Simulation and implementation of local electrical markets in...

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10th IEEE international symposium on systems engineering, ISSE 2024

作者： Moreno-Vassart, X. Toledo, F. Javier Herranz, Victoria Galiano, Vicente Miguel Hernández University of Elche Computers Engineering Dept. Elche Spain Miguel Hernández University of Elche Operational Research Center Elche Spain

ISBN: (纸本)9798350353723

In recent decades, the increase in environmental awareness and the need to reduce greenhouse gas emissions have led to growing interest in renewable energy sources. Among them, photovoltaic solar energy has emerged as a promising option due to its abundance, sustainability, and potential for the decentralisation of energy supply. In this paper, we explore the concept of photovoltaic energy communities (PEC), an innovative model that integrates distributed photovoltaic solar energy generation with storage technologies and demand management systems. The constant increase of prosumers (producers and consumers of electrical energy) is causing a change in the rules of the electrical market. This paper presents a software architecture for a distributed energy community system based on nodes installed in each prosumer. This system is specifically designed to be implemented in embedded systems, making it suitable for deployment in residential settings and small communities. The decentralised structure and main components of the system are described, highlighting its ability to efficiently manage energy generation, storage, and consumption. In our PVLEM (PhotoVoltaic Local Electrical Market) proposal, the elements of this architecture are defined, and an implementation that allows the simulation of an energy community and its execution in a real environment is presented. Through this proposal, we facilitate the transformative potential of PECs as a sustainable approach to energy generation, capable of promoting community participation, energy resilience, and climate change mitigation. © 2024 IEEE.

关键词： distributed System Energy Communities Optimization Photovoltaic Energy Prosumers

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Detection of Covert Tunnel over Internet Control Message Protocol Based on Baseline Features 29

Detection of Covert Tunnel over Internet Control Message Pro...

引用

29th IEEE international Conference on parallel and distributed systems, ICPADS 2023

作者： Duan, Haiying Wang, Baohui Beihang University School of Software Beijing China

ISBN: (纸本)9798350330717

Covert tunnel is gradually used in threat attacks, such as remote control and data theft. In this paper, we propose a baseline feature-based malicious traffic detection method for Internet Control Message Protocol (ICMP) covert tunnel. We first analyze the packets involved in benign ICMP traffic and ICMP covert tunnel, and determine five features that show better ability to differentiate benign ICMP traffic and ICMP covert tunnel, including the average length of packet payloads, the frequency of packets, the session duration, the ratio of request and reply, and the entropy value of payload. Then, we employ a variety of machine learning models to build binary classifiers for the detection of ICMP covert tunnel. A set of experimental results show that the best detection precision, recall and Fl value of the proposed method are as high as 99.51%, 99% and 99.48%, respectively. Meanwhile, the proposed method has millisecond traffic parsing and detection analysis capabilities, which can be applied to the detection of ICMP covert tunnel in real-world scenarios. © 2023 IEEE.

关键词： feature engineering ICMP covert tunnel machine learning malicious traffic detection

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Coverage Holes Recovery in Hybrid Sensor Networks Based on Key Perceptual Intersection 22

Coverage Holes Recovery in Hybrid Sensor Networks Based on K...

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22nd IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Li, He Sun, Shixian Dong, Chuang Fu, Zhufeng Zhao, Cong Qi, Qinglei University of Nanyang Normal School of Artificial Intelligence and Software Engineering Nanyang China

ISBN: (纸本)9798331509712

Wireless sensor networks are widely used in various applications such as military surveillance, wildlife monitoring, industrial process monitoring and so on. Detecting and recovering from coverage holes is a major issue in wireless sensor networks. The gradual energy depletion of sensor nodes with limited battery energy leads to dysfunction of some of the nodes, thus creating holes in the monitored area. In this paper, propose a method to detect and recover coverage holes in wireless sensor networks. This method first divides the network into equally sized units, and then selects a representative node for each unit, called an agent. Then, the percentage of each cell covered by nodes can be accurately calculated and holes can be detected. Finally, the holes are recovered using the average of the key perceptual intersections as the initial value of the global optimal point of the particle swarm optimization algorithm. Simulation indicates show that the algorithm reduces the network energy consumption, reduces the distance travelled by the mobile nodes and increases the percentage of network holes recovery as compared to other algorithms. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Budget-aware Scheduling Algorithm Using Negative Offset Mechanism for Snake Optimization in Heterogeneous Cloud 22

Budget-aware Scheduling Algorithm Using Negative Offset Mech...

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22nd IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Zhang, Longxin Zhang, Yanfen Lu, Xiaotong Tan, Runti Huang, Xianming Chen, Jianguo Hunan University of Technology College of Computer Science Zhuzhou China Sun YatSen University School of Software Engineering Zhuhai519082 China

ISBN: (纸本)9798331509712

Cloud computing, as a cutting-edge computing paradigm, offers substantial data processing and storage capabilities. In a heterogeneous cloud environment, the diversity among cloud platforms results in varying task execution times, posing challenges in minimizing workflow makespan under budget constraints. On this basis, a novel meta-heuristic optimization algorithm, named snake optimizer (SO), is proposed for workflow scheduling in the cloud. Then, a negative offset mechanism is designed to dynamically guide the offset of individual positions during population update to prevent falling into local optimums, thereby optimizing the search for feasible solutions and improving the success rate. Finally, using the negative offset mechanism, a snake optimization budget-aware scheduling algorithm (NO-SO) is developed to schedule budget-constrained workflows in heterogeneous cloud computing environments and minimize the makespan. A series of comparative experiments conducted on real-world scientific workflows demonstrates that the NO-SO algorithm enhances the success rate in finding a feasible solution by 38.89% and 34.45% compared with the advanced MG-PRO algorithm and the original SO algorithm, respectively. Moreover, it achieves an average reduction in makespan of 30.30% and 32.19%. © 2024 IEEE.

关键词： Cloud platforms

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Privacy-preserving scheme of cotton supply chain based on blockchain 22

Privacy-preserving scheme of cotton supply chain based on bl...

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22nd IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Zhang, Linlin Li, Wenwen Huo, Jing Bi, Xuehua Zhao, Kai Xinjiang University College of Software Urumqi China Xinjiang University College of Computer Science and Technology Urumqi China Xinjiang Medical University College of Medical Engineering and Technology Urumqi China

ISBN: (纸本)9798331509712

With the popularization and development of artificial intelligence and intelligent agriculture, the supply chain has become an effective management method. However, the complexity and variety of data types and the large amount of data in the supply chain make its privacy and security a major challenge. Especially in the cotton supply chain, due to the large number of participants involved and the varying levels of data security protection of each participant, it is easy to leak the user's identity privacy and private data in the supply chain during data sharing. Therefore, this paper is dedicated to improving privacy security in the cotton supply chain. First, we define the data in the cotton supply chain and divide it into private data and shared data, which is conducive to the secure storage and sharing of data in the cotton supply chain. Second, we introduce blockchain and advanced cryptography techniques and propose a method of the pseudo-identity encryption based on SM9, which ensures the security of data in the supply chain while ensuring the privacy and security of the identities of the data owners and data receivers, and realizes the tracking of the identities of the malicious users who have uploaded false data. Finally, we adopt the method of dual-chain storage and introduce IPFS to reduce the storage burden of blockchain as much as possible and carry out security and experimental analyses of the proposed scheme to verify its feasibility. © 2024 IEEE.

关键词： Differential privacy

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FedHPM: Online Federated Learning via Heterogeneous Prediction Model 22

FedHPM: Online Federated Learning via Heterogeneous Predicti...

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22nd IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Zhang, Zhi Zhang, Shiwen Chen, Shuang Liang, Wei Hunan University of Science and Technology College of Computer Science and Technology Xiangtan China Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology School of Computer Science and Engineering Xiangtan411201 China

ISBN: (纸本)9798331509712

In the era of big data and growing privacy concerns, Federated Learning (FL) has emerged as a promising solution for collaborative model training while preserving user data privacy. However, FL faces challenges such as inconsistent data quality and frequent client dropouts, which hinder its performance. To address these challenges, we propose FedHPM, a novel framework that leverages the predictive capabilities of Long Short-Term Memory (LSTM) networks. FedHPM incorporates an intelligent client selection mechanism that utilizes LSTM-based analysis of historical data to forecast clients' potential data quality and dropout likelihood. This mechanism enables efficient selection of the top best-performing clients for participation in each round of global model training. By mitigating the impact of dropouts and optimizing the composition of participating clients, FedHPM significantly improves both the convergence speed and final performance of the global model. Through extensive empirical evaluations, we demonstrate the superior performance of FedHPM in enhancing FL stability, accelerating the convergence rate, and maintaining model accuracy. The results highlight the effectiveness of our framework in addressing the challenges associated with data quality and dropouts, thereby advancing the field of federated learning. © 2024 IEEE.

关键词： Federated learning

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A Rotating Target Detection Algorithm for Ships in SAR Images Based on LAOBB-YOLOv8n 22

A Rotating Target Detection Algorithm for Ships in SAR Image...

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22nd IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Huang, Min Wang, Shuaihui Luo, Shuaili Sun, Qiuhong Zhou, Xiaokang Hebei University of Science and Technology School of Information Science and Engineering Shijiazhuang China Kansai University Faculty of Business Data Science Osaka565-0823 Japan

ISBN: (纸本)9798331509712

Aiming to address challenges in SAR image ship detection tasks, such as the dense concentration of inshore ships, small target sizes, and large overlapping areas, this paper proposes an improved algorithm LAOBB-YOLOv8n based on YOLOv8n for detecting rotating ships in SAR images. In this model, we propose the Detect-LSCD detection head, which replaces the BatchNorm in the convolutional layers of the Detect module in YOLOv8n with GroupNorm to improve the positioning and classification capabilities of the detection head;Replace the original Spatial Pyramid Pooling-Fast (SPPF) module with the Attention-based Intrascale Feature Interaction (AIFI) module, which focuses on processing advanced image features through self-attention mechanism, thus improving the flexibility and accuracy of the model in processing complex scenes while reducing unnecessary computational consumption;Based on the original network structure, we add a small target detection layer to improve the detection ability for small targets;Use rotating bounding box instead of traditional horizontal bounding box, which can better accommodate the rotating posture of the target and reduce the overlapping areas between detection boxes, thereby improving the accuracy of inshore target detection. The comparative and ablation experiments are conducted on the RSDD-SAR dataset to verify the model's effectiveness. The experimental results show that the mAP50 of LAOBB-YOLOv8n reaches 98%, which is 1.4% higher than that of YOLOv8n. Although the number of parameters of LAOBB-YOLOv8n is larger than that of YOLOv8n, it is still very small compared with other baseline models, and the accuracy of LAOBB-YOLOv8n is much higher than other models. © 2024 IEEE.

关键词： Radar imaging

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