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Adaboost-based Graph Convolutional Networks with Channel Attention for Intrusion Detection in Internet-of-Things 21

Adaboost-based Graph Convolutional Networks with Channel Att...

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21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International conference on Big Data and Cloud computing, 16th IEEE International conference on social computing and Networking and 13th International conference on Sustainable computing and Communications, ISPA/BDCloud/socialCom/SustainCom 2023

作者： Long, Jing Luo, Cuiting Chen, Ruxin Liang, Wei Qin, Zheng Hunan Normal University College of Information Science and Engineering Changsha410081 China Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

ISBN: (纸本)9798350329223

With the increasing proliferation of Internet of Things (IoT) and industrial big data technologies, while IoT scenarios offer intelligent services, cyberspace faces various types of threats and attacks. Despite Graph Convolutional Networks (GCN) having been demonstrated as a potent tool for learning graph data representations, many current IoT intrusion detection methods tend to overlook the adoption of graph-related techniques, given the non-graph-structured nature of most IoT traffic data. This leads to the model design overlooking the potential correlations among variables, thus limiting the accuracy of intrusion detection. In this study, we introduce an integrated intrusion detection model that fuses graph learning with a dual attention mechanism(A-GCA). Initially, our research adopts a combination of GCN and Convolutional Neural Networks (CNN) to deeply capture intricate interactions between data nodes. To further enhance the model's feature-learning capability, we incorporate a channel attention mechanism for emphasizing features with pivotal information. Additionally, a multi-head attention mechanism is adopted to amalgamate a wealth of contextual information, ensuring more vivid feature representations. Regarding the training strategy, we employ a variant of Adaboost which uniquely steers weak classifiers from focusing on high-precision fitting of raw data towards precise binary classification tasks, aiming to augment the model's overall performance in intrusion detection. Evaluations and performance analyses using real-world datasets UNSW-NB15 and CICIDS2017 indicate that the proposed method achieves improvements of 2.5% and 3.7% over the best baseline model in the accuracy and F1-score, respectively, relative to the baseline, surpassing other approaches. © 2023 IEEE.

关键词： Adaptive boosting

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MCoT: Multi-Modal Vehicle-to-Vehicle cooperative Perception with Transformers 29

MCoT: Multi-Modal Vehicle-to-Vehicle Cooperative Perception ...

引用

29th IEEE International conference on Parallel and Distributed Systems, ICPADS 2023

作者： Shi, Shanwei Zhang, Chaokun Lv, Aojia He, Shen Tianjin University College of Intelligence and Computing Tianjin China China Xiong'an Group Digital City Technology Co. Ltd. Xiong'an China

ISBN: (纸本)9798350330717

Highly accurate perception is one of the pivotal factors for the safe operation of Intelligent Connected Vehicles (ICVs). Nevertheless, occlusion blind spots, limited fields-of-view, and low-point density of the sensor data lead to limited perception for the single ICV, which can be well addressed with vehicle-to-vehicle (V2V) cooperative perception. Recent development of V2V cooperative perception technology have made the perception of ICVs more and more accurate and reliable. In V2V cooperative perception, LiDAR and Camera are two types of complementary sensors for ICVs. However, using only specific single-modal data such as Camera RGB images or LiDAR point clouds for V2V collaborative perception cannot fully improve perception accuracy. Furthermore, the large model based on Transformers has been proven to effectively enhance multi-modal fusion. To this end, we propose MCoT, a novel approach for multi-modal V2V cooperative perception with Transformers. Our MCoT extracts intermediate features from RGB images and point cloud of different agents, aligning them in the Bird's-Eye View (BEV) perspective through rigid association. Subsequently, we use the cross-attention mechanism to perform a soft fusion of these features in the BEV domain. The attention mechanism empowers our model with the ability to adaptively discern which regions of the image and LiDAR are most relevant, and what information should be extracted from them. Extensive evaluations demonstrate that MCoT can significantly enhance the accuracy and robustness of perception. Our model achieved remarkable results on the large-scale simulation dataset OPV2V, improving the average accuracy by 71.43% compared to the baseline and outperforming the second-place by nearly 3.95%. Our approach also demonstrates the fastest convergence rate under the same number of training epochs. © 2023 IEEE.

关键词： Bird's-Eye View Intelligent Connected Vehicle Multi-Modal Data Fusion Transformers Vehicle-to-Vehicle cooperative Perception

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Application of Edge computing in Investigation and Interrogation 21

Application of Edge Computing in Investigation and Interroga...

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5th International conference on Electronic Information Technology and computer Engineering, EITCE 2021

作者： Gong, Siyuan Chen, Xiang People's Public Security University of China Beijing China

ISBN: (纸本)9781450384322

Under the background of the trial-centered litigation system reform, the investigation and interrogation work, as the basic link before trial in criminal proceedings, has required higher standards of evidence collection procedures. The characteristics of edge computing, such as low delay transmission, reliable sharing, data optimization and data security management, as well as its supporting moving object detection technology, video frame diversion technology and intelligent monitoring system, make it highly adaptable to the application in the field of investigation and interrogation. At the same time, the algorithm and model carried by edge computing can well calculate and control the evidence collection process. Moreover, the special method of processing video data of investigation and interrogation procedures also reduces space of data storage and the cost of examination, thus continuously advancing the trial-centered litigation system reform. © 2021 acm.

关键词： Edge computing

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Do You Really Understand What I Mean? A Visual Representation of Micro-operation Intention 24

Do You Really Understand What I Mean? A Visual Representatio...

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24th IEEE International conference on computer supported cooperative work in Design (IEEE CSCWD)

作者： Wang, Zhuo Wang, Yang Bai, Xiangliang Zhang, Shusheng He, Weiping Huo, Xiangyu Northwestern Polytech Univ Sch Mech & Elect Engn Xian Peoples R China Xinxiang Aviat Ind Grp Co Ltd Civil Aircraft Div Xinxiang Aviat Ind Grp Xinxiang Henan Peoples R China Zhengzhou Univ Sch Mech & Elect Engn Zhengzhou Peoples R China

ISBN: (纸本)9781728165974

In AR assembly, only experienced workers can complete the physical tasks with high operation precision requirements. The reason is that they use their brains to transform the information reflecting micro-operation intention into a series of manual operation rules. Because novices are not familiar with these rules, they often encounter problems of low precision and low efficiency. In order to describe these rules with AR instruction, this paper does some research work. Firstly, traditional AR and microAR are defined, and their differences and relations in guiding micro-operation are explained. On this basis, a microAR oriented to human microoperation rules is proposed. Then, according to the traditional AR and microAR, three instructions are designed to guide novice micro-operation assembly. An example is designed to test the assembly time and operation experience of three interfaces under a physical task. The results show that compared with traditional AR instruction, microAR instruction can better guide novice micro-operation.

关键词： human-centered computing visualization visualization design and evaluation methods

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Community supported Agriculture: The Concept of Solidarity in Mitigating Between Harvests and Needs 21

Community Supported Agriculture: The Concept of Solidarity i...

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CHI conference on Human Factors in computing Systems

作者： Landwehr, Marvin Engelbutzeder, Philip Wulf, Volker Univ Siegen Siegen Germany Int Inst SocioInformat IISI Bonn Germany

ISBN: (纸本)9781450380966

There is a developing recognition of the social and economic costs entailed in global supply chains. In this paper, we report on efforts to provide alternative, more sustainable and resilient models of production. Community supported Agricultures (CSAs) address this problem but require new means of exchange which, we suggest, offer a design opportunity for sustainable HCI research. This paper presents a two months participatory observation in a food movement, a German CSA which developed a distribution system involving their own currency. Based on our ethnographic observations, we focus our discussion on (1) the solidaristic principles upon which the movement is based and (2) techniques of mediating between consumers' wishes and the constraints of local agricultural production. By relating to the continued development of CSAs, we identify three interrelated innovation gaps and discuss new software architectures aimed at resolving the problems which arise as the movement grows.

关键词： Community supported Agriculture Sustainable HCI Solidarity Trust Currency Distributed Ledger Technology cooperative work Technological Sovereignty Food Sovereignty

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Efficient and Secure Collaborative Processing in Mobile Edge computing via Blockchain 15

Efficient and Secure Collaborative Processing in Mobile Edge...

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2022 IEEE Congress on Cybermatics: 15th IEEE International conferences on Internet of Things, iThings 2022, 18th IEEE International conferences on Green computing and Communications, GreenCom 2022, 2022 IEEE International conference on Cyber, Physical and social computing, CPSCom 2022 and 8th IEEE International conference on Smart Data, SmartData 2022

作者： Le, Yuwei Jiang, Yiheng Ling, Xintong Wang, Jiaheng Southeast University National Mobile Communications Research Laboratories Nanjing210096 China Purple Mountain Laboratories Nanjing211100 China

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

Mobile edge computing (MEC) provides resource-hungry, energy-efficient, latency-sensitive, and privacy-secure computing services close to end-users, whereas the services are usually restricted to a single network. Blockchain emerges as a promising way to establish cooperative trust among MEC networks and enable large-scale and trusted cross-network edge cooperation on task processing. Meanwhile, integrating blockchain and cross-network edge collaboration faces a wide range of efficiency and security challenges. In this work, we propose a blockchain-native edge collaboration architecture to support trusted network information sharing, enable cross-network task distribution, and safeguard data processing in a collaborative cluster. We design a two-layer efficient permissioned consensus protocol dedicated to securing, validating, and monitoring the cross-network edge collaborations. Finally, comprehensive simulations are conducted to illustrate the effectiveness of the proposed architecture. © 2022 IEEE.

关键词： Blockchain

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How to Train a (Bad) Algorithmic Caseworker: A Quantitative Deconstruction of Risk Assessments in Child Welfare

How to Train a (Bad) Algorithmic Caseworker: A Quantitative ...

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2022 CHI conference on Human Factors in computing Systems, CHI EA 2022

作者： Saxena, Devansh Repaci, Charles Sage, Melanie D Guha, Shion Dept. of Computer Science Marquette University MilwaukeeWI United States School of Medicine Washington University in St. Louis Saint LouisMO United States School of Social Work University at Bufalo BuffaloNY United States Faculty of Information University of Toronto TorontoON Canada

ISBN: (纸本)9781450391566

Child welfare (CW) agencies use risk assessment tools as a means to achieve evidence-based, consistent, and unbiased decision-making. These risk assessments act as data collection mechanisms and have been further developed into algorithmic systems in recent years. Moreover, several of these algorithms have reinforced biased theoretical constructs and predictors because of the easy availability of structured assessment data. In this study, we critically examine the Washington Assessment of Risk Model (WARM), a prominent risk assessment tool that has been adopted by over 30 states in the United States and has been repurposed into more complex algorithmic systems. We compared WARM against the narrative coding of casenotes written by caseworkers who used WARM. We found significant discrepancies between the casenotes and WARM data where WARM scores did not not mirror caseworkers' notes about family risk. We provide the SIGCHI community with some initial findings from the quantitative de-construction of a child-welfare risk assessment algorithm. © 2022 Owner/Author.

关键词： Risk assessment

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Ensuring Data Freshness for In-Storage computing with cooperative Buffer Manager

Ensuring Data Freshness for In-Storage Computing with Cooper...

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2025 Design, Automation and Test in Europe conference, DATE 2025

作者： Xue, Jin Song, Yuhong Guo, Yang Shao, Zili The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9783982674100

In-storage computing (ISC) aims to mitigate the excessive data movement between the host memory and storage by offloading computation to storage devices for in-situ execution. However, ensuring data freshness remains a key challenge for practical ISC. For performance considerations, many data processing systems implement a buffer manager to cache part of the on-disk data in the host memory. While the host applications commit updates to the in-memory cached copies of the data, ISC operators offloaded to the device only have access to the on-disk persistent data. Thus, ISC may miss the most recent updates from the host and produce incorrect results after reading the stale and inconsistent data from the persistent storage. With this limitation, current ISC can only be used in read-only settings where the on-disk data are not subject to concurrent updates. To tackle this problem, we propose a cooperative buffer manager for ISC to transparently provide data freshness guarantees to host applications. Proposed methods allow the device to synchronize with the host buffer manager and decide whether to read the most recent copy of data from host memory or flash memory. We implement our method based on a real hardware platform and perform evaluation with a Bs - tree based key-value store. Experiments show that our method can provide transparent data freshness for host applications with reduced latency. © 2025 EDAA.

关键词： Cache memory

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Human perceptions on moral responsibility of ai: A case study in ai-assisted bail decision-making 21

Human perceptions on moral responsibility of ai: A case stud...

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2021 CHI conference on Human Factors in computing Systems: Making Waves, Combining Strengths, CHI 2021

作者： Lima, Gabriel Grgic-Hlaca, Nina Cha, Meeyoung School of Computing Kaist Data Science Group Ibs Korea Republic of

ISBN: (纸本)9781450380966

How to attribute responsibility for autonomous artifcial intelligence (AI) systems' actions has been widely debated across the humanities and social science disciplines. This work presents two experiments (N=200 each) that measure people's perceptions of eight diferent notions of moral responsibility concerning AI and human agents in the context of bail decision-making. Using real-life adapted vignettes, our experiments show that AI agents are held causally responsible and blamed similarly to human agents for an identical task. However, there was a meaningful diference in how people perceived these agents' moral responsibility;human agents were ascribed to a higher degree of present-looking and forward-looking notions of responsibility than AI agents. We also found that people expect both AI and human decision-makers and advisors to justify their decisions regardless of their nature. We discuss policy and HCI implications of these fndings, such as the need for explainable AI in high-stakes scenarios. © 2021 acm.

关键词： Decision making

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Reinforcement learning-based IoT sensor scheduling strategy for bridge structure health monitoring 15

Reinforcement learning-based IoT sensor scheduling strategy ...

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作者： Zhang, Yuan Wu, Hengshan Yi, Lingzhi Luo, Bin Qiu, Yun Tang, Feilong School of Civil Engineering University of South China China Department of Computer Science St. Francis Xavier University Canada Foshan Highway and Bridge Engineering Monitoring Station Co China The School of Data Science and Engineering East China Normal University Shanghai200062 China

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

Internet of Things (IoT) based Bridge Structural Health Monitoring (BSHM) is a hot topic in the field of civil engineering and computer science, and has been widely concerned by academia and industry. The lifetime of the sensors is much less than that of the bridge, which is one of the main technical bottlenecks in BSHM. Therefore, how to effectively improve the network lifetime is the focus of current research. Based on reinforcement learning and Fisher information matrix, this paper proposed a node sleep scheduling strategy by using the learning automata model and confident information coverage (CIC) model to learn the optimal sensor sleep scheduling strategy through cooperative sensing among nodes. Fisher information matrix, which is widely used in civil engineering, was introduced to define the node sleep scheduling problem as a multi-objective optimization problem. With information validity as the modal assurance criterion, the network performance was measured by combining energy efficiency, network coverage requirements and network connectivity. While ensuring the network connectivity and coverage requirements, the system parameter identification error is minimized and the network life is maximized. Through the simulation of jiangbei Bridge in Guangdong, China, the effectiveness, energy efficiency and applicability of the proposed scheme are verified. © 2022 IEEE.

关键词： Internet of things

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