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Blockchain Assembled Supply Chains to Foster Secure Trading Using distributed Ledger 9

Blockchain Assembled Supply Chains to Foster Secure Trading ...

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9th IEEE international conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021

作者： Baliyan, Anupam Kaswan, Kuldeep Singh Akansha Mittal, Neetu Chitkara University Institute of Engineering Technology Chitkara University Punjab India School of Computing Science and Engineering Galgotias University Greater Noida India Bharati Vidyapeeth Institute of Computer Application Management New Delhi India Amity University Noida Uttar Pradesh India

ISBN: (纸本)9781665417037

In this paper, we study how to assemble a supply chain with the avail of Blockchain to establish a secure trading environment. Blockchain is distributed, decentralized and a transparent mechanism which makes it suitable to share data on publicly accessible networks such that it can further be verified and audited independently thus maintaining data integrity. this paper suggests that the Blockchain technology offers great potential to foster secure trading using distributed ledger that propounds ingenious platforms as it makes the history of any digital asset unalterable, traceable and transparent. We further study how Blockchain mitigates the subsisting quandary in supply chains, how does it provide an edge over other technologies. the model is proposed to implement the Blockchain manufactured supply chain and it is further explained how it eliminates the challenges faced by the current supply chain management system. Also, challenges to adopting this technology have been discussed in the latter section of the paper. © 2021 IEEE.

关键词： distributed ledger

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2021 9th international conference on Intelligent computing and Wireless Optical Communications, ICWOC 2021

2021 9th International Conference on Intelligent Computing a...

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9th international conference on Intelligent computing and Wireless Optical Communications, ICWOC 2021

ISBN: (纸本)9781665435949

the proceedings contain 14 papers. the topics discussed include: resonant beam communication based on multi-longitudinal-mode distributed cavity laser;survivable wavelength-division-multiplexed passive optical network for fronthaul in 5g and beyond;reconnaissance and experiment on 5G-SA communication terminal capability and identity information;performance investigations of DFMA-PON systems using a parallel IM/PM transmitter for dispersion compensation;TrustZone based virtual architecture of power intelligent terminal;research on UAV trajectory planning based on artificial bee colony algorithm;partial label optimal margin distribution machine;recognition of astronomical strong gravitational lens system based on deep learning;and intelligent spectrum allocation for mmWave integrated backhaul and access network.

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Decentralized Task Scheduling in Satellite Edge computing

Decentralized Task Scheduling in Satellite Edge Computing

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international conference on Fog and Mobile Edge computing (FMEC)

作者： Emiliano Casalicchio Danilo Magliarisi Dept. Computer Science Sapienza University of Rome IT Blekinge Institute of Technology SE Dept. Computer Science Sapienza University of Rome Rome Italy

ISBN: (数字)9798350366488

ISBN: (纸本)9798350366495

Satellite Edge computing has been recently introduced to deploy innovative computational services in space using Low Earth Orbit (LEO) satellite constellations as a distributed computational platform. Running a distributed computing platform in space introduces new challenges to traditional problems like computation offloading, task scheduling, mobility management, fault detection, and recovery. this research focuses on the problem of task scheduling, proposing a system model that accounts for the dynamics of the Satellite Edge computing environment and a formulation of the scheduling problem as an optimization problem that minimizes the average task response time under constraints on available resources and task completion deadlines. then, we propose a decentralized algorithm that estimates the task response time and computes a scheduling solution in a fixed time, which depends only on the number of Inter Satellite Links a satellite has (typically four). Finally, we estimate and compare the overhead of the decentralized versus the decentralized solutions, showing the advantages of the proposed approach. Simulation experiments allow us to compare the performance of the decentralized approach with the performance of baseline decentralized and centralized solutions. Results show that, in all scenarios considered, the proposed decentralized algorithm performs better than the baseline centralized and decentralized solutions and is more scalable and highly available.

关键词： Space vehicles Satellite constellations Satellites Multi-access edge computing Processor scheduling Heuristic algorithms Low earth orbit satellites Dynamic scheduling Time factors Optimization

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A Knowledge Enhanced Pre-Training Model for Chinese Weibo Sentiment Analysis

A Knowledge Enhanced Pre-Training Model for Chinese Weibo Se...

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IEEE international conference on Cloud computing and Big Data Analysis (ICCCBDA)

作者： Li Yao Key Laboratory of Public Security Information Application Based on Big-data Architecture Ministry of Public Security Zhejiang Police College Hangzhou China

ISBN: (数字)9798350373554

ISBN: (纸本)9798350373561

Sentiment analysis aims to automatically identify and extract subjective information such as tendencies, stances, evaluations, and opinions from text. Current state-of-the-art Natural Language Processing (NLP) methods, primarily based on large-scale pre-trained language models (PLM), have significantly advanced the field of sentiment analysis. However, these methods often struggle due to the scarcity of annotated data. To address these challenges, we present a knowledge-enhanced pre-trained model for the Chinese social media platform. this model employs a phrase-based masking strategy and incorporates knowledge-related information by making adjustments to the structure of the intermediate encoder layer. We validated the model's performance through comparative experiments with other baseline methods, demonstrating the effectiveness of integrating sentiment resources into pre-trained language models.

关键词： Training Sentiment analysis Analytical models Social networking (online) Computational modeling Knowledge based systems Linguistics

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Authenticity Classification of WeChat Group Chat Messages Based on LDA and NLP

Authenticity Classification of WeChat Group Chat Messages Ba...

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IEEE international conference on Cloud computing and Big Data Analysis (ICCCBDA)

作者： Nihan Nie Hengyi Guo Wei Song School of Software and IoT Engineering Jiangxi University of Finance and Economics Nanchang China School of Information Management Dalarna University Borlänge Sweden

ISBN: (数字)9798350373554

ISBN: (纸本)9798350373561

this study conducts an in-depth verification and analysis of the authenticity of information in WeChat group chats by integrating Latent Dirichlet Allocation (LDA) topic modeling with advanced Natural Language Processing (NLP) techniques such as XLNet and BERT. Leveraging LDA, the thematic structure of group chat content is revealed, and through the integration of NLP technologies like XLNet and BERT, a comprehensive analysis of the information is achieved. Experimental results demonstrate that our developed model performs exceptionally well in identifying the authenticity of information, confirming the effectiveness of this method in the domain of social media information verification. this research not only deepens our understanding of the authenticity of information in WeChat group chats but also provides a more effective tool for social media platforms to detect and prevent the spread of false information. It opens up a new perspective on social media information authentication research and points out future research directions.

关键词： Analytical models Accuracy Social networking (online) Message services Natural language processing Data models Vectors

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Incentive-based task matching with evolving preferences in distributed fog computing: A trust-aware approach

Incentive-based task matching with evolving preferences in d...

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international conference on Computer and Communications (ICCC)

作者： Lei Yan Zaigui Zhang Bin Sun Yonghai Wang Inspur Group Company Limited Jinan Inspur (Zhengzhou) Data Technology Co. Ltd Zhengzhou China

Fog computing has been a promising technology for the computation-intensive Apps with the resource pool adjacent to the mobile users. In which, users’ workloads or management can be offloaded to servers with a designed matching scheme. However, the selfish servers are reluctant to share their resources cooperatively. An efficient incentive scheme is desirable for the edge networks, especially for the decentralized fog networks. In addition, existing works mainly assume that the preferences of users and servers are static or fixed, and it is not practical for the fog networks with dynamicity caused by many uncertainties. In this paper, a trust-aware incentive scheme for task matching with evolving preferences in decentralized fog computing is proposed. We first formulate a long-term trust management scheme for the network considering the participants’ behaviors, such as, service qualities and payment behavior, etc. then, the evolving preferences of both users and fog nodes are derived with their variable trust levels, and a trust-aware task matching algorithm is proposed. Finally, a trust-aware incentive scheme is designed to encourage users and fog nodes to behave positively during the offloading interaction. the simulation results demonstrate that our proposed trust-aware fog computing scheme is more efficient than existing methods regarding energy cost and delay.

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DIEF: An Autopsy Module for distributed Identification of E-mail Files from Disk Images 9

DIEF: An Autopsy Module for Distributed Identification of E-...

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9th IEEE international conference on Smart City and Informatization (iSCI) / 15th IEEE international conference on Big Data Science and Engineering (BigDataSE)

作者： Ozcan, Selim Astekin, Merve Glisson, William Bradley Choo, Kim-Kwang Raymond Sam Houston State Univ Dept Comp Sci Cyber Forens Intelligence Ctr Dept Hunstville TX 77340 USA Simula Res Lab Data Driven Software Engn Dept Fornebu Norway Univ Texas San Antonio Dept Informat Syst & Cyber Secur San Antonio TX USA

Hard drives are a predominant source of residual data in today9;s digital environments. However, the increasing size of hard disks compounds the challenge of digital forensics, particularly in time-poor and resourc... 详细信息

ISBN: (纸本)9781665400404

Hard drives are a predominant source of residual data in today's digital environments. However, the increasing size of hard disks compounds the challenge of digital forensics, particularly in time-poor and resource-constrained forensic laboratories (e.g., due to the time required to recover residual data), using conventional digital investigation techniques. there are various types of information in the disk images such as e-mail data (a key source of information in disk images). However, it is time-consuming to identify and extract e-mail files from the disk images, when the hard disk size is big and contains large number of (other) files. We posit the importance of improving existing processes, for example by incorporating efficient and scalable processing mechanisms, to handle increasing volume of data. this study investigates the development of an Autopsy module for distributed Identification of E-mail Files (DIEF). Initial experiments on the benchmark dataset show that DIEF achieves an average of 52% performance improvement in the process method, as compared to a traditional approach that does not employ distributed processing.

关键词： Digital forensics E-mail forensics distributed computing Big digital forensic data Big data analysis Scalability Runtime comparison Software development Autopsy the Sleuth Kit

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Research on Unknown distributed Denial-of-Service Attacks Intrusion Detection Based on Deep Learning

Research on Unknown Distributed Denial-of-Service Attacks In...

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6th international conference on Intelligent computing and Signal Processing (ICSP)

作者： Liumei Zhang Zhaoyang An Yuanjiao Hu School of Computer Science Xi'an Shiyou University Xi'an China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

the increasing prevalence of distributed Denial-of- Service (DDoS) attacks poses a serious threat to network security, emphasizing the crucial need for effective intrusion detection methods. the continuous evolution of attack strategies has exposed the limitations of traditional feature engineering and statistical analysis in detection mechanisms. To address this challenge, this study proposes an innovative DDoS attack detection framework based on deep learning. At the core of this framework lies a Temporal Convolutional Network (TCN) structure, cleverly integrated with an attention mechanism to enhance the model's ability to identify and extract crucial information. this integration not only aids in capturing long- term dependencies and global patterns in time-series data but also significantly improves detection accuracy and system robustness. To validate the effectiveness of the proposed method, comprehensive experimental evaluations were conducted using the CICDDoS2019 dataset. the results demonstrate a notable achievement, with our model achieving a high classification accuracy of 98.14%. In comparison to traditional machine learning methods, the model exhibits significantly reduced false positive and false negative rates.

关键词： Deep learning Adaptation models Accuracy Attention mechanisms Statistical analysis Computational modeling Intrusion detection Signal processing Convolutional neural networks Long short term memory

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Quarks: A Secure and Decentralized Blockchain-Based Messaging Network

Quarks: A Secure and Decentralized Blockchain-Based Messagin...

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IEEE international conference on Cyber Security and Cloud computing (CSCloud)

作者： Mirza K. B. Shuhan Tariqul Islam Enam A. Shuvo Faisal H. Bappy Kamrul Hasan Carlos Caicedo Software Research & Engineering bKash Limited Dhaka Bangladesh School of Information Studies (iSchool) Syracuse University Syracuse NY USA School of Computing Asia Pacific University of Technology and Innovation Kuala Lumpur Malaysia Tennessee State University Nashville TN USA

Over the past two decades, the popularity of messaging systems has increased both in enterprise and consumer level. Many of these systems used secure protocols like end-to-end encryption to ensure strong security features such as “future secrecy” for one-to-one communication. However, the majority of them rely on centralized servers owned by big IT companies, which allows them to use their users’ personal data. Also it allows the government to track and regulate their citizens’ activities, which poses significant threats to “digital freedom”. Also, these systems have failed to achieve security attributes like confidentiality, integrity, privacy, and future secrecy for group communications. In this paper, we present a novel blockchain-based secure messaging system named Quarks that overcomes the security pitfalls of the existing systems and eliminates the centralized control. We have analyzed our design of the system with security models and definitions from existing literature to demonstrate the system’s reliability and usability. We have developed a Proof of Concept (PoC) of the Quarks system leveraging distributed Ledger Technology (DLT), and conducted load testing on that. We noticed that our PoC system achieves all the desired attributes that are prevalent in a traditional centralized messaging scheme despite the limited capacity of the development and testing environment. therefore, this assures us the applicability of such systems in near future if scaled up properly.

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Oblivious Robots Performing Different Tasks on Grid Without Knowing their Team Members

Oblivious Robots Performing Different Tasks on Grid Without ...

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international conference on Autonomous Robots and Agents, ICARA

作者： Satakshi Ghosh Avisek Sharma Pritam Goswami Buddhadeb Sau Department of Mathematics Jadavpur University Kolkata India

Two fundamental problems of distributed computing are Gathering and Arbitrary pattern formation (APF). these two tasks are different in nature as in gathering robots meet at a point but in Apfrobots form a fixed pattern in distinct positions. In most of the current literature on swarm robot algorithms, it is assumed that all robots in the system perform one single task together. Two teams of oblivious robots deployed in the same system and different teams of robots performing two different works simultaneously where no robot knows the team of another robot is a new concept in the literature introduced by Bhagat et al. [ICDCN'2020]. In this work, a swarm of silent and oblivious robots are deployed on an infinite grid under an asynchronous scheduler. the robots do not have access to any global coordinates. Some of the robots are given input of an arbitrary but unique pattern. the set of robots with the given pattern is assigned the task of forming the given pattern on the grid. the remaining robots are assigned with the task of gathering to a vertex of the grid (not fixed from earlier and not any point where a robot that is forming a pattern terminates). Each robot knows to which team it belongs, but can not recognize the team of another robot. Considering weak multiplicity detection, a distributed algorithm is presented in this paper which leads the robots with the input pattern into forming it and other robots into gathering on a vertex of the grid on which no other robot forming the pattern, terminates.

关键词： Knowledge engineering Pattern formation Automation Robot kinematics Swarm robotics Task analysis distributed computing

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