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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Brendan Black Joseph Rafferty Jose A. Santos Andrew Ennis School of Computing Ulster University Belfast Northern Ireland

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Over the last number of years Unmanned Aerial Vehicles (UAVs) have become increasingly popular in several fields such as agriculture and medicine. Recently UAVs have been used for the deployment within Emergency Response for visual scouting of an impacted area in addition to delivering supplies via payload. UAVs are also capable of acting as networking nodes using incorporated technology or by attaching independent hardware via the UAVs payload capability. The application of UAVs as a network node(s) can enable increased performance within the network as UAV based nodes can alter their current position due to their unique nature of mobility. Therefore, this study aims to assess the performance of aerial communication using UVAs which incorporate the use of a small Bluetooth 5.0 (BLE 5.0) node as a payload. In this research, the impact generated via Air-Ground Propagation on the Received Signal Strength Indicator (RSSI) measurement was investigated. In addition to this, this paper also investigates any performance difference displayed between different Transmission Power Profiles as this in turn affects the overall power consumption of the transmitting device. When operating at heights of 5, 10, and 15 Metres the maximum average loss was found to be 2.37 dBm among the Standard Transmission Power profile and a maximum average loss of 1.18 dBm occurring with the Enhanced Transmission Power Profile.

关键词： Visualization Privacy Bluetooth Autonomous aerial vehicles Propagation losses Emergency services Received signal strength indicator

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Anomaly Detection in Dynamic Networks through Edge-Tight Structure Embedding

Anomaly Detection in Dynamic Networks through Edge-Tight Str...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Liming Wang Jiaxing Fan Fengzhe Zhong Yan Liu Jinyang Liu School of Cyber Science and Engineering Zhengzhou University Zheng China Henan Key Laboratory of Cyberspace Situation Awareness Zheng China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Anomaly detection within dynamic networks holds significant relevance in fields such as cybersecurity, e-commerce, and social media. Recent methods employing deep learning concentrate on alterations in node-dependent substructures within dynamic networks, yielding superior outcomes compared to graph embedding-based techniques. Nevertheless, these methods grapple with two primary problems in dynamic network anomaly detection: the disruption caused by relevant neighbors during node sampling and the inadequate integration of spatio-temporal information. To address these issues, we propose a framework ESEAD for anomaly edge detection in dynamic networks in this paper. This proposed framework devises a random walk-based node sampling strategy, selecting nodes intimately associated with the edge under scrutiny, and designs an encoder model utilizing a multi-headed attention mechanism to learn the spatio-temporal features of the edge neighborhood. Subsequently, these domain-specific spatio-temporal features are fed into an anomaly discriminator for anomaly detection. Empirical results demonstrate that our proposed ESEAD framework surpasses existing state-of-the-art methods across five real-world datasets.

关键词： Deep learning Privacy Social networking (online) Image edge detection Detectors Feature extraction Complexity theory

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international conference of Modern Applications on Information and Communication Technology (ICMAICT),University of Babylon, Babylon, Iraq

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Journal of Physics: conference Series 2021年第1期1804卷

作者： Obaid, Ahmed J. Albermany, Salah Hamad, Bassma H. Ahmed, Hiba A. Faculty of Computer Science and Mathematics University of Kufa Najaf Iraq Alkarkh University of Science Iraq Dept of Mathematics Baghdad University Iraq

Ahmed J. Obaid1*, Salah Albermany2, Bassma H. Hamad3, Hiba A. Ahmed4 1, 2Faculty of Computer Science and Mathematics, University of Kufa, Najaf, Iraq. 3Alkarkh University of Science, Iraq 4Dept of Mathematics, Baghdad University, Iraq E-Mails: ***@***, salah_albermany@*** ICMAICT proceedings volume involved the contributions that were presented through the Second international conference of Modern Applications on Information and Communication Technology (ICMAICT), which has been held at University of Babylon, Iraq(http://***), at 22-23 October 2020, ICMAICT also hosted sessions from Koneru Lakshmaiah Education Foundation, Department of Electronics and Communication Engineering for their events international conference on Innovations in Electronics, Communication, computing & Automation (ICIECCA) The conference provided a forum for discussion and sharing the knowledge and recent studies in many Fields and Subjects among Researchers, Academics Participants, Lecturers, and other Communities. ICMAICT focused on the Aspects of computing and Security Systems, Global Economy and Statistics, Communication and networking, Mathematics and Information Theory, where the received papers come from the authors who working in academics centers, universities, research institutes, corporations, industries, and other agencies. General public theme of ICMAICT is to explore the recent techniques and technologies in the field of Information Technology, computing, Information Theory, Security systems, and mathematics. ICMAICT also hosted sessions in Nano Technologies, IoT, Biomedical Systems, Hyper-Modal Signal Processing, Wireless Communication Technologies, Networks & Big Data Applications, Electromagnetic, RF, Microwave and Wearable Technology, Sciences. The conference has been a great opportunity for participants coming from UK, Turkey, Nepal, Philippines, Australia, Egypt, Lebanon, Algeria, Iran, India, Pakistan, Malaysia, and Many other Countri

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TrustedBench: An Efficient and User-friendly distributed Performance Testing Tool for Blockchain System

TrustedBench: An Efficient and User-friendly Distributed Per...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Yang Cheng Kai Wei Yihui Zhang Chunyu Jiang Weiwei Pang Qi Zhang Bin Liu Lifeng Zhang Tingting Liu Yinqian Wu Cloud. Computing and Big Data Research Institute China Academy of Information and Communications Technology Beijing China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Performance is a crucial indicator for the blockchain system evaluation. However, it is difficult to measure and comprehensively evaluate the performance of blockchain systems, particularly due to their complexity and diversity. Based on the comprehensive analysis of common blockchain systems and existing performance testing tools, this paper proposes a novel efficient and user-friendly performance testing tool for blockchain systems named TrustedBench. This tool supports all-round analysis and testing, and provides a powerful tool for understanding and analyzing the performance of blockchain systems. The architecture design, test execution process and important performance indicators of blockchain systems are introduced, and their calculation methods are further expounded. Finally, the overall results from the implementation of TrustedBench are presented and interpreted, revealing the operation and performance characteristics of some different blockchain products. With this tool, users can have a more comprehensive understanding of the performance of blockchain systems. Furthermore, TrustedBench effectively enhances the efficiency of the blockchain platform in many real-world scenarios.

关键词： Measurement Privacy System performance Computer architecture Blockchains Complexity theory Security

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FedRSM: Representational-Similarity-Based Secured Model Uploading for Federated Learning

FedRSM: Representational-Similarity-Based Secured Model Uplo...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Gengxiang Chen Sheng Liu Xu Yang Tao Wang Linlin You Feng Xia School of Intelligent Systems Engineering Sun Yat-Sen University Shenzhen China School of Computing Technologies Royal Melbourne Institute of Technology Melbourne Australia

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

As a novel learning paradigm, Federated learning (FL) aims at protecting privacy by avoiding raw data shifting between distributed clients and central servers. However, recent researches demonstrate the vulnerability of FL against gradient-based privacy attacks, in which, gradients intercepted by malicious adversaries may result in data leakage. Current defense methods suffer from performance drops, low privacy guarantees, and high communication costs. Motivated by this, we propose FedRSM, a Representational-Similarity-Based Secured Model Uploading for Federated Learning. FedRSM splits Deep Neural Networks (DNNs) into layers, calculates Representational Dissimilarity Vector (RDV), measures the similarity between local RDV and global RDV of each model layer, and constructs secured local model to be uploaded based on Representational Consistency Alteration (RCA). According to the evaluation result, FedRSM can improve testing accuracy by up to 2%, significantly reduce communication costs, and avoid data leakage under different model complexities.

关键词： Training Data privacy Adaptation models Costs Federated learning Computational modeling Data models

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Evaluation of distributed Collaborative Learning Approach for 5G Network Data Analytics Function

Evaluation of Distributed Collaborative Learning Approach fo...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Shoufeng Wang Hua-Min Chen Ye Ouyang Fan Li Xuan Chen Limeng Ma Zhanwu Li Sen Bian Zhidong Ren Asiainfo Technologies (China) INC. China Faculty of Information Technology Beijing University of Technology Beijing China Network Optimization Center China Unicom Beijing Branch Beijing China China Unicom Beijing China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

As a key role in the future network functionalities, artificial intelligence (AI) has been studied widely. To match the envisioned traffic evolution trend and communication requirement, Network Data Analytic Function(NWDAF) is a new proposed 5G component to provide analytics for any Network Functions (NFs). Considering sending all data to a central NWDAF instance is extremely time-consuming and it raises concerns about security vulnerabilities and data overload, it's expected to design a distributed NWDAF architecture which is able to enhance NF data localization, improve security, reduce control overhead during model training, shorten the training time, and finally, enhance the accuracy of the trained models by virtue of local testing on a real-time network. Federated learning is considered in future NWDAF design, while its detailed structure and processes are not standardized yet. This paper studies the effectiveness of distributed federated learning based traffic characteristics analysis for NWDAF. Simulation shows that the learning accuracy is nolinear with data loss probability. Under the simulation assumption, the solution could endure 30% data loss, while the learning accuracy and the retransmission dramatically rise when data loss probability is greater than 45%.

关键词： Training Analytical models Data analysis Federated learning 5G mobile communication distributed databases Data models

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Calculation of dose distributions with constraint checking for Siemens Virtual Wedge

Calculation of dose distributions with constraint checking f...

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Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： M. Miften X.R. Zhu K. Takahashi F. Lopez M.T. Gillin Comput.. Med. Syst. Inc. St. Louis MO USA Medical College Milwaukee WI USA Computerized Medical Systems Inc. Saint Louis MO USA

ISBN: (纸本)0780364651

Radiation therapy treatment planning for many clinical situations requires wedge-shaped isodose distributions. The wedged dose distributions can be generated through the use of physical wedges, motorized wedges, and the synchronization of jaw or multileaf collimator dynamic motion with accelerator dose output. The Siemens Virtual Wedge (VW) delivers wedged shaped dose distributions by combining computer controlled dose delivery with collimator motion. In this paper, we describe a model to calculate dose for VW using either the Clarkson or convolution/superposition algorithms. The VW implementation models the dose generated by VW using the Siemens monitor units (MU) analytic formalism which determines the number of MU required to deliver dose at points across the VW beam. For any treatment setup, the VW algorithm generates an intensity matrix that will be used to model the modification of fluence emanating from the source. The intensity (transmission) map is calculated as the ratio of the MU delivered on the axis divided by the monitor units delivered on the central-axis MU(O); MU(O) is also the number of monitor units that is entered at the machine console. The MCT analytic formalism used for calculating the intensity matrix (which affects the calculation of dose) may be modified through the fine tuning of the attenuation correction factor.

关键词： Collimators Condition monitoring Biomedical applications of radiation distributed computing Quantum computing Motion control Shape control Convolution Computerized monitoring Attenuation

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FaaSTCC: efficient transactional causal consistency for serverless computing 21

FaaSTCC: efficient transactional causal consistency for serv...

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proceedings of the 22nd international Middleware conference

作者： Taras Lykhenko Rafael Soares Luis Rodrigues Universidade de Lisboa Portugal

ISBN: (纸本)9781450385343

In this paper we study mechanisms that permit to augment the FaaS middleware with support for Transactional Causal Consistency (TCC). At first glance, it may seem that offering TCC to FaaS applications can trivially be achieved, given that the FaaS paadigm does not prevent applications from selecting the storage service with the properties they need. Unfortunately, most TCC storage services ensure consistency only to individual client processes, while a FaaS application is executed by multiple, independent, worker processes. Therefore, there is the need to coordinate the workers, a task that can be a significant source of overhead. We propose a novel architecture to support TCC in FaaS, named FaaSTCC, that significantly reduces the coordination overhead. FaaSTCC achieves this goal by augmenting the workers with a caching layer and by implementing novel mechanisms that maximize the cache usage. First, our storage layer offers to the caching layer a promise, that sets a horizon where the versions retrieved by the cache are guaranteed to be consistent. Second, in FaaSTCC, functions coordinate using snapshot intervals, that support the lazy identification of the read snapshot, increasing the chances of using the cached values. We have implemented and experimentally evaluated FaaSTCC. Our results show that FaaSTCC achieves up to 5x lower average latency and 6x lower tail latency than previous work.

关键词： function as a service distributed systems transactional causal consistency

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Comparison of dosimetric properties of virtual wedge and physical wedges

Comparison of dosimetric properties of virtual wedge and phy...

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Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： X.R. Zhu M.T. Gillin F. Lopez D.F. Grimm J.J. Rownd Department of Radiation Oncology Medical College Milwaukee WI USA

ISBN: (纸本)0780364651

The authors present a direct comparison of dosimetric properties of Siemens virtual wedge (VW) and physical wedge (PW). While there is a great difference in absolute values of wedge factors, VW factors (VWFs) and PW factors (PWFs) have a similar trend as a function of field size. PWFs have stronger depth dependence than VWF because of beam hardening in PW fields. Dose profiles in the wedge direction are match very well between VW and PW except in the toe area of the 45/spl deg/ wedge with large field sizes, where PW fields have a higher peak. The authors have demonstrated that it is dosimetrically acceptable to have an initial gap up to 3 cm for VW fields when compared with PW dose profiles. While maintaining the desired wedged dose distribution, VW has an advantage of creating smaller hot spot, when compared with PW, in the toe region of 45/spl deg/ wedge fields with large field sizes. Dose profiles in the non-wedge direction shows a significant reduction in PW fields due to off-axis beam softening and oblique filtration. PW fields also have significantly higher peripheral doses than open and VW fields. VW fields have similar surface doses as the open fields while PW fields have slightly lower surface doses.

关键词： Imaging phantoms Linear accelerators Performance evaluation Sensor arrays Detectors Size measurement distributed computing Physics computing Motion control Collimators

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Energy Efficient Neural Network Embedding in IoT over Passive Optical Networks

Energy Efficient Neural Network Embedding in IoT over Passiv...

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international conference on Transparent Optical Networks

作者： Mohammed Moawad Alenazi Barzan A. Yosuf Taisir El-Gorashi Jaafar M. H. Elmirghani School of Electrical Engineering University of Leeds United Kingdom

ISBN: (数字)9781728184234

ISBN: (纸本)9781728184241

In the near future, IoT based application services are anticipated to collect massive amounts of data on which complex and diverse tasks are expected to be performed. Machine learning algorithms such as Artificial Neural Networks (ANN) are increasingly used in smart environments to predict the output for a given problem based on a set of tuning parameters as the input. To this end, we present an energy efficient neural network (EE-NN) service embedding framework for IoT based smart homes. The developed framework considers the idea of Service Oriented Architecture (SOA) to provide service abstraction for multiple complex modules of a NN which can be used by a higher application layer. We utilize Mixed Integer Linear Programming (MILP) to formulate the embedding problem to minimize the total power consumption of networking and processing simultaneously. The results of the MILP model show that our optimized NN can save up to 86% by embedding processing modules in IoT devices and up to 72% in fog nodes due to the limited capacity of IoT devices.

关键词： Artificial neural networks Cloud computing Power demand Logic gates Task analysis Energy efficiency Smart homes

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