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Histopathological Image Classification and Vulnerability Analysis using Federated Learning

Histopathological Image Classification and Vulnerability Ana...

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

作者： Sankalp Vyas Amar Nath Patra Raj Mani Shukla Computing and Information Science Anglia Ruskin University Cambridge Radford University Radford USA

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Healthcare is one of the foremost applications of machine learning (ML). Traditionally, ML models are trained by central servers, which aggregate data from various distributed devices to forecast the results for newly generated data. This is a major concern as models can access sensitive user information, which raises privacy concerns. A federated learning (FL) approach can help address this issue: A global model sends its copy to all clients who train these copies, and the clients send the updates (weights) back to it. Over time, the global model improves and becomes more accurate. Data privacy is protected during training, as it is conducted locally on the clients’ ***, the global model is susceptible to data poisoning. We develop a privacy-preserving FL technique for a skin cancer dataset and show that the model is prone to data poisoning attacks. Ten clients train the model, but one of them intentionally introduces flipped labels as an attack. This reduces the accuracy of the global model. As the percentage of label flipping increases, there is a noticeable decrease in accuracy. We use a stochastic gradient descent optimization algorithm to find the most optimal accuracy for the model. Although FL can protect user privacy for healthcare diagnostics, it is also vulnerable to data poisoning, which must be addressed.

关键词： Training Privacy Data privacy Analytical models Federated learning Stochastic processes distributed databases

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SCATMAN: A Framework for Enhancing Trustworthiness in Digital Supply Chains

SCATMAN: A Framework for Enhancing Trustworthiness in Digita...

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

作者： Michael Eckel Anirban Basu Satoshi Kai Hervais Simo Fhom Siniša Ðukanović Henk Birkholz Shingo Hane Matthias Lieske Fraunhofer Institute SIT | ATHENE Center Darmstadt Germany Hitachi Ltd. Yokohama Japan Hitachi Ltd. Tokyo Japan Hitachi Europe GmbH Düsseldorf Germany

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

In this paper, we present a framework and an architecture that aim to enable and manage trust in supply chains. Our architecture addresses the authenticity and integrity of devices and processes within heterogeneous system landscapes. We identify and discuss the current challenges in digital supply chains and lay out security, privacy, and interoperability requirements that must be met for successful implementation. We hypothesize that the overall perception of trust in a supply chain depends on the trustworthiness of all digital systems involved, including hardware, software, and information flow. Our proposed architecture helps enhance trustworthiness based on verifiable, indisputable, and believable digital evidence for devices and processes in supply chains, including the entire hardware and software lifecycles. We actively advocate for a mixed landscape of centralized and decentralized solutions for the storage of evidence and trust information. This can include traditional centralized databases and distributed ledger technologies. We discuss the auditability and accountability of digital evidence using trust-enabling technologies, and present a preliminary proof-of-concept (PoC) implementation in a real-world application scenario.

关键词： Privacy distributed ledger Digital systems Supply chains distributed databases Computer architecture Software

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An Automatic Generation Method for Path Expressions of CPN Model Focus on Tested Behaviors

An Automatic Generation Method for Path Expressions of CPN M...

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international conference on Computer Supported Cooperative Work in Design

作者： Sun Tao Linjing Zhang Huiping Ma College of Computer Science Inner Mongolia University Hohhot China

ISBN: (纸本)9781538614839

With the gradually development of distributed software, collaborative work became a trend. At the same time, due to the continuous improvement of software complexity, software testing is highly susceptible to the state space explosion, and it also makes the formation of the path expressions for test behaviors become very difficult. For the above problem, a new algorithm of path expressions automation generation which based on Colored Petri Nets (CPN) is proposed in this paper. First, a new coverage criterion for parallel software testing based on transition coverage is proposed in this paper. Second, searching and optimizing the FullPath according these coverage criteria. FullPath is a set of paths that from initial elements to tested target in here. Third, extract and integrate all the arc expressions on these paths, and the results expressions only about the output arc variable of the initial position. Next, analyzing logical relation between different nodes on these paths and get the final path expressions. These path expressions combine all the information of arc expressions, guard expressions and constraint relationship of the CPN model. In particular, we need to consider the synchronization relationship of the transition, i.e., we need to consider the equivalent problem of the same name variable on the different output arc. According to the path expressions, we could obtain that the token of current place whether to reach the tested place. And, the tester also could get the change of token in tested place. Besides, these expressions could reduce the redundant path maximally and ensure effective coverage, so, it could ensure correctness and sufficiency of the test. It could be used to guide tester analyze the flow of tokens and remove redundancy testing dataset. Finally, the analysis and demonstration of the examples show that this method is reasonable and effective.

关键词： Software Software testing Finite element analysis Concurrent computing Computer science Electronic mail

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Designing and Implementing Communication-efficient Model of distributed System for Real-time Electromagnetic Transient Simulation

Designing and Implementing Communication-efficient Model of ...

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

作者： Qi Guo Binjiang Hu Zeqi Hong Yanjun Zhao Shuyong Li Liang Tu State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid China Southern Power Grid Co. Ltd

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

This paper introduces CM-RETS, a 4-Level address Communication Model designed specifically for real-time simulation of electromagnetic transients in power systems. CM-RETS incorporates a unique 4-Level address scheme and leverages Remote Direct Memory Access (RDMA) technology to enable efficient and reliable data exchanges between computing nodes in a distributed system. By effectively distributing computational load, CM-RETS facilitates faster and more realistic simulations, ensuring precise and timely data exchanges within a 5μs time step to capture transients in real time. Experimental results validate the effectiveness and efficiency of CM-RETS in achieving accurate and real-time simulations of electromagnetic transients. With its robust and cost-effective solution, CM-RETS provides researchers and engineers with the means to perform detailed analysis and studies on power systems under various transient conditions.

关键词： Computational modeling Memory management Real-time systems Data models Power system reliability Reliability Security

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A Commitment and Ring Signature based Scheme for Amount and Identity Privacy Protection in Blockchain

A Commitment and Ring Signature based Scheme for Amount and ...

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

作者： Shiyong Huang Haocong Li Ruoting Xiong Wei Ren Jie He Yi Ren School of Computer Science China University of Geosciences Wuhan China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University China School of Computer Science Beijing Jiaotong University Beijing China School of Computing Science University of East Anglia Norwich UK Beijing Key Laboratory of Urban Spatial Information Engineering Beijing China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Blockchain has been envisioned as an anonymous cryptocurrency framework and can be applied in various applications such as e-payment, share economics, and distributed ledger. Although an account is anonymous, privacy in terms of consumption behaviors still imposes leakage risks. For example, an adversary may infer the consumption capability related to an account further by analyzing the history of consumption records. It is thus of critical importance to design a solution to preserve the anonymity of both transaction amount and transaction peer’s identity, which is changeable because the amount must be still authenticated in anonymity. In this paper, we propose a scheme by using Pedersen commitment to anonymize the transaction amount, and together using ring signature to conceal the transaction peer’s identity while maintaining authentication. Especially, we further improve the security of anonymous authentication enabled by ring signature by introducing accountability, which can defend against double-spending attacks by penalization and empower auditability. The extensive performance and security analysis justify the applicability of the proposed scheme.

关键词： Economics Privacy distributed ledger Authentication Blockchains Information filtering Security

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Reference Architecture for a Collaborative Predictive Platform for Smart Maintenance in Manufacturing

Reference Architecture for a Collaborative Predictive Platfo...

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IEEE international conference on Intelligent Engineering Systems

作者： Z. Balogh E. Gatial J. Barbosa P. Leitao T. Matejka Department of Parallel and Distributed Computing Institute of Informatics Bratislava Slovakia Polytechnic Institute of Bragança Bragança Portugal Mat-obaly s.r.o. Prievidza Slovakia

Maintenance is a key factor to ensure the production efficiency, since the occurrence of unexpected failures leads to a degradation of the system performance, causing the loss of productivity and business opportunities, which are crucial roles to achieve competitiveness. The article aims to propose a reference architecture which will improve the way maintenance is considered in the current manufacturing world, by enabling an overall increase of production rates, while increasing the operational equipment effectiveness and decreasing the impact of maintenance needs. This objective would be accomplished by establishing an IoT infrastructure for the collection of the huge amount of available shop floor data, which can be analyzed, considering data analytics algorithms, predictive maintenance models and forecasting techniques, to perform the machine/system health assessment and prediction of maintenance needs, e.g. by detecting earlier the occurrence of possible failures and consequently the need to implement maintenance interventions. The scheduling of predictive maintenance needs will be integrated with the existing maintenance planning tools, and especially synchronized with the production planning tools to achieve a nondisruptive maintenance impact in the production system. A cloud-based collaborative maintenance services platform allows the secure collection, aggregation and analysis of a large amount of shared data from numerous manufacturers that use the same or similar machinery, and acts as an open market where companies can contract specialized maintenance services. This reference architecture aims to provide replicable architecture to be broadly applicable in a variety of industries, capable to improve the production efficiency through a real-time health monitoring and early detection of failures and outages, to speed up the maintenance delivery, and consequently mitigate their impact.

关键词： Predictive maintenance Manufacturing Collaboration Production facilities Sensors

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Gradients and intensity modulated radiotherapy

Gradients and intensity modulated radiotherapy

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

作者： J.M. Kapatoes G. Olivera P. Reckwerdt H. Keller J. Balog T.R. Mackie Department of Medical Physics University of Wisconsin Madison WI USA Tomotherapy Inc. Middleton WI USA

ISBN: (纸本)0780364651

A consequence of the advent of intensity modulated radiation therapy (IMRT) is the presence of large dose gradients surrounding the tumor, and the regions at risk (RAR's) near the tumor. Unlike standard radiotherapy, these gradients are not the chance result of a few beam choices, but rather they are strategically placed by the optimization software. A first issue is the magnitude of these gradients. Optimal dose plans were simulated for four clinical cases using experimental helical tomotherapy optimization software. It was found that high gradients could be divided into two categories: avoidance gradients and incidental gradients. Avoidance gradients are associated with tumor/RAR boundaries and tend to be larger, on the order of 30% per cm or higher. Incidental gradients are a secondary consequence of the optimizer doing its job: placing a large amount of dose confined to the target volume. Incidental gradients tend to be on the order of 15%-20% per cm.

关键词： Intensity modulation Computed tomography Medical simulation Breast neoplasms Biomedical applications of radiation Design optimization Spinal cord Lung neoplasms Software standards distributed computing

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Differential Privacy Frequent Closed Itemset Mining over Data Stream

Differential Privacy Frequent Closed Itemset Mining over Dat...

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

作者： Xuebin Ma Shengyi Guan Yanan Lang Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing Inner Mongolia University Hohhot China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

As the most common technique for mining and analyzing massive data, frequent itemset mining is widely used in various scenarios. However, when the data contains sensitive information, it will bring serious privacy leakage risks to mining and publishing it directly. Therefore, how to efficiently mine frequent itemset without privacy disclosure is a hot issue at present. In data stream, because the data between adjacent timestamps possess certain correlation, which makes it easier to leak privacy for frequent itemset mining in the data stream, and considering that frequent itemset will have combinatorial explosion problem in data stream, frequent closed itemset mining in the data stream will be a better choice. In this paper, we propose a differential privacy algorithm for mining frequent closed itemset in data stream, which is referred to as DPES. The algorithm uses a vertical mining method in each sliding window, which can quickly obtain the frequent closed itemset contained in the current window. Besides, to improve the data utility, we also design an adaptive privacy budget allocation strategy by computing the difference to decide whether the current timestamp should publish a low-noise statistic or an approximate statistic. Finally, we demonstrate that the DPES algorithm satisfies ε-difference privacy by privacy analysis, and the experimental results on several real datasets also show the effectiveness of the DPES algorithm.

关键词： Differential privacy Privacy Correlation Itemsets Publishing Noise Approximation algorithms

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Computer networking for Management Information System of Unmanned Vehicles

Computer Networking for Management Information System of Unm...

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international conference on Transparent Optical Networks

作者： Sergey Sokolov Andrey Boguslavsky Keldysh Institute of Applied Mathematics RAS Miusskaya Square 4 Moscow Russia

ISBN: (数字)9781728184234

ISBN: (纸本)9781728184241

The ever-increasing need for the large-scale implementation of unmanned vehicles requires situational awareness of such vehicles. In this case two general directions are possible. The first: simplification and fixing situations with vehicles movements. The second: improving the onboard control system and its information component. We focus on the second direction in our study. Information support of vehicles, especially systems of technical vision, requires ever-increasing computing resources and intelligent technologies in algorithmic support. The experience of our research shows that reconfigurable high-performance heterogeneous resources are the effective software and hardware tool for information support of autonomous vehicles Such devices combine sequentially parallel processing of visual data. In the process of developing such resources, we use a heterogeneous computer network based on the PCI express bus. The report describes the general scheme of such a network, considers hardware and software configurations for solving application task, gives the results of experiments to solve the issues of collecting and processing visual data, and discusses the prospects for the development of this approach.

关键词： Visualization Hardware Software Field programmable gate arrays Uniform resource locators Unmanned vehicles Software algorithms

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On the Adoption of Homomorphic Encryption by Financial Institutions*

On the Adoption of Homomorphic Encryption by Financial Insti...

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

作者： Michela Iezzi Carsten Maple Danilo A. Giannone Bank of Italy Italy The Alan Turing Institute U.K Gener8 U.K

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Financial institutions collect, control and process sensitive data, either personally or commercially. These data are vital for many purposes, including business process optimisation, tailored services to individuals and organisations, and preventing fraud or other misuse of the financial system. While an institution’s information is valuable, its power is amplified when combined with other data stored in different organisations horizontally, vertically or in a governance role. However, sharing data between organisations becomes difficult for commercial, legal and regulatory reasons. Privacy-enhancing Technologies (PETs) are becoming a practical solution for secure and private information sharing. One such PET, Homomorphic Encryption (HE), allows the computation over encrypted data and thus protects the confidentiality of the information while increasing its utility. This paper investigates the current position regarding the use of HE in the financial sector by analysing the LexisNexis news archive using statistical instruments on NLP and ML techniques. Our results show that the financial sector has gained momentum in discussing privacy-enhancing technology over the last few years. The discussion around this new field highlights a constantly growing match in capitalising market readiness to technology readiness.

关键词： Data privacy Social networking (online) Soft sensors Technology Information sharing Process control Writing

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