scholarly journals DAM-SE: A Blockchain-Based Optimized Solution for the Counterattacks in the Internet of Federated Learning Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Shichang Xuan ◽  
Ming Jin ◽  
Xin Li ◽  
Zhaoyuan Yao ◽  
Wu Yang ◽  
...  
Keyword(s):  
Learning Process ◽  
Data Privacy ◽  
Rapid Development ◽  
Optimization Method ◽  
Learning Technologies ◽  
Communication Cost ◽  
Security Evaluation ◽  
Malicious Nodes ◽  
Verification Methods ◽  
Security Verification

The rapid development in network technology has resulted in the proliferation of Internet of Things (IoT). This trend has led to a widespread utilization of decentralized data and distributed computing power. While machine learning can benefit from the massive amount of IoT data, privacy concerns and communication costs have caused data silos. Although the adoption of blockchain and federated learning technologies addresses the security issues related to collusion attacks and privacy leakage in data sharing, the “free-rider attacks” and “model poisoning attacks” in the federated learning process require auditing of the training models one by one. However, that increases the communication cost of the entire training process. Hence, to address the problem of increased communication cost due to node security verification in the blockchain-based federated learning process, we propose a communication cost optimization method based on security evaluation. By studying the verification mechanism for useless or malicious nodes, we also introduce a double-layer aggregation model into the federated learning process by combining the competing voting verification methods and aggregation algorithms. The experimental comparisons verify that the proposed model effectively reduces the communication cost of the node security verification in the blockchain-based federated learning process.

scholarly journals A Malicious Behavior Awareness and Defense Countermeasure Based on LoRaWAN Protocol

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5122 ◽  
Author(s):  
Shu-Yang Gao ◽  
Xiao-Hong Li ◽  
Mao-De Ma
Keyword(s):  
Rapid Development ◽  
Packet Transmission ◽  
Security Evaluation ◽  
Area Network ◽  
Wide Area Network ◽  
Transmission Scheme ◽  
Malicious Nodes ◽  
Transmission Strategy ◽  
Malicious Behavior ◽  
Replay Attacks

Low power wide area network (LoRaWAN) protocol has been widely used in various fields. With its rapid development, security issues about the awareness and defense against malicious events in the Internet of Things must be taken seriously. Eavesdroppers can exploit the shortcomings of the specification and the limited consumption performance of devices to carry out security attacks such as replay attacks. In the process of the over-the-air-activation (OTAA) for LoRa nodes, attackers can modify the data because the data is transmitted in plain text. If the user’s root key is leaked, the wireless sensor network will not be able to prevent malicious nodes from joining the network. To solve this security flaw in LoRaWAN, we propose a countermeasure called Secure-Packet-Transmission scheme (SPT) which works based on the LoRaWAN standard v1.1 to prevent replay attacks when an attacker has obtained the root key. The proposed scheme redefines the format of join-request packet, add the new One Time Password (OTP) encrypted method and changes the transmission strategy in OTAA between LoRa nodes and network server. The security evaluation by using the Burrows-Abadi-Needham logic (BAN Logic) and the Scyther shows that the security goal can be achieved. This paper also conducts extensive experiments by simulations and a testbed to perform feasibility and performance analysis. All results demonstrate that SPT is lightweight, efficient and able to defend against malicious behavior.

A novel multi-stage ensemble model with fuzzy clustering and optimized classifier composition for corporate bankruptcy prediction

2020 ◽  
pp. 1-17
Author(s):  
Dongqi Yang ◽  
Wenyu Zhang ◽  
Xin Wu ◽  
Jose H. Ablanedo-Rosas ◽  
Lingxiao Yang ◽  
...  
Keyword(s):  
Fuzzy Clustering ◽  
Rapid Development ◽  
Optimization Method ◽  
Selection Method ◽  
Bankruptcy Prediction ◽  
Ensemble Model ◽  
Composition Method ◽  
Classifier Selection ◽  
Multi Stage ◽  
Proposed Model

With the rapid development of commercial credit mechanisms, credit funds have become fundamental in promoting the development of manufacturing corporations. However, large-scale, imbalanced credit application information poses a challenge to accurate bankruptcy predictions. A novel multi-stage ensemble model with fuzzy clustering and optimized classifier composition is proposed herein by combining the fuzzy clustering-based classifier selection method, the random subspace (RS)-based classifier composition method, and the genetic algorithm (GA)-based classifier compositional optimization method to achieve accuracy in predicting bankruptcy among corporates. To overcome the inherent inflexibility of traditional hard clustering methods, a new fuzzy clustering-based classifier selection method is proposed based on the mini-batch k-means algorithm to obtain the best performing base classifiers for generating classifier compositions. The RS-based classifier composition method was applied to enhance the robustness of candidate classifier compositions by randomly selecting several subspaces in the original feature space. The GA-based classifier compositional optimization method was applied to optimize the parameters of the promising classifier composition through the iterative mechanism of the GA. Finally, six datasets collected from the real world were tested with four evaluation indicators to assess the performance of the proposed model. The experimental results showed that the proposed model outperformed the benchmark models with higher predictive accuracy and efficiency.

scholarly journals Accurate Instance-Based Segmentation for Boundary Detection in Robot Grasping Application

2021 ◽  
Vol 11 (9) ◽  
pp. 4248
Author(s):  
Hong Hai Hoang ◽  
Bao Long Tran
Keyword(s):  
Object Segmentation ◽  
State Of The Art ◽  
Rapid Development ◽  
Spatial Relationship ◽  
Learning Technologies ◽  
Average Precision ◽  
Novel Approach ◽  
3D Camera ◽  
Robot Grasping ◽  
Instance Segmentation

With the rapid development of cameras and deep learning technologies, computer vision tasks such as object detection, object segmentation and object tracking are being widely applied in many fields of life. For robot grasping tasks, object segmentation aims to classify and localize objects, which helps robots to be able to pick objects accurately. The state-of-the-art instance segmentation network framework, Mask Region-Convolution Neural Network (Mask R-CNN), does not always perform an excellent accurate segmentation at the edge or border of objects. The approach using 3D camera, however, is able to extract the entire (foreground) objects easily but can be difficult or require a large amount of computation effort to classify it. We propose a novel approach, in which we combine Mask R-CNN with 3D algorithms by adding a 3D process branch for instance segmentation. Both outcomes of two branches are contemporaneously used to classify the pixels at the edge objects by dealing with the spatial relationship between edge region and mask region. We analyze the effectiveness of the method by testing with harsh cases of object positions, for example, objects are closed, overlapped or obscured by each other to focus on edge and border segmentation. Our proposed method is about 4 to 7% higher and more stable in IoU (intersection of union). This leads to a reach of 46% of mAP (mean Average Precision), which is a higher accuracy than its counterpart. The feasibility experiment shows that our method could be a remarkable promoting for the research of the grasping robot.

scholarly journals Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog Computing

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Na Wang ◽  
Yuanyuan Cai ◽  
Junsong Fu ◽  
Jie Xu
Keyword(s):  
Energy Cost ◽  
Data Privacy ◽  
Low Cost ◽  
Rapid Development ◽  
Fog Computing ◽  
Bat Algorithm ◽  
Data Retrieval ◽  
High Energy ◽  
Physiological Data ◽  
Range Tree

The rapid development of Internet of Medical Things (IoMT) is remarkable. However, IoMT faces many problems including privacy disclosure, long delay of service orders, low retrieval efficiency of medical data, and high energy cost of fog computing. For these, this paper proposes a data privacy protection and efficient retrieval scheme for IoMT based on low-cost fog computing. First, a fog computing system is located between a cloud server and medical workers, for processing data retrieval requests of medical workers and orders for controlling medical devices. Simultaneously, it preprocesses physiological data of patients uploaded by IoMT, collates them into various data sets, and transmits them to medical institutions in this way. It makes the entire execution process of low latency and efficient. Second, multidimensional physiological data are of great value, and we use ciphertext retrieval to protect privacy of patient data in this paper. In addition, this paper uses range tree to build an index for storing physiological data vectors, and meanwhile a range retrieval method is also proposed to improve data search efficiency. Finally, bat algorithm (BA) is designed to allocate cost on a fog server group for significant energy cost reduction. Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme.

scholarly journals SUSTAINABLE DEVELOPMENT OF EDUCATIONAL INSTITUTIONS IN THE CONTEXT OF THE INTRODUCTION OF ELEMENTS OF DISTANCE EDUCATION IN THE LEARNING PROCESS

2019 ◽  
Vol 16 (33) ◽  
pp. 404-422
Author(s):  
B. M. AITBAYEVA ◽  
A. M. MAULENOVA ◽  
Z. B AKHMETZHANOVA ◽  
Z. A. KENZHEBEKOVA ◽  
B. O. RAKHIMBAYEVA
Keyword(s):  
Distance Education ◽  
Distance Learning ◽  
Learning Process ◽  
Professional Education ◽  
Postgraduate Education ◽  
Learning Technologies ◽  
Educational Process ◽  
Practical Significance ◽  
Educational Institutions ◽  
Global Trends

Distance education is essentially the basis for the development of educational institutions that provide innovative services, which cannot be obtained elsewhere. It is believed that distance education is a substitute for the traditional as part of simplifying and cheapening the learning process. At the same time, the leading global trends suggest the need for the development of elements of self-education and the expansion of the geographical nature of educational offers. The relevance of the study is that it is necessary to distinguish between the use of distance education methods in the traditional sphere and the sphere of training professionals. The paper presents the concept of the need to integrate elements of distance education in the process of preparing university teachers. The authors believe that teachers in drawing up courses and applying learning technologies use the same techniques as in distance learning. Therefore, the use of distance learning technologies can be shown as the basis for the development of advanced training programs and additional professional education. The authors proposed a study on the need and sufficiency of the use of distance education technologies and the possibilities for their integration into the process of postgraduate education. The practical significance of the work is determined by the fact that the possibilities of self-development of teachers are fully disclosed, not only as subjects of the educational process but also as subjects of training.

scholarly journals Personalized Recommendation Model of High-Quality Education Resources for College Students Based on Data Mining

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chaohua Fang ◽  
Qiuyun Lu
Keyword(s):  
Learning Process ◽  
Data Science ◽  
Recommendation System ◽  
Information Overload ◽  
Rapid Development ◽  
Learning Ability ◽  
Personalized Recommendation ◽  
Learning Resources ◽  
Learner Model ◽  
Internet Education

With the rapid development of information technology and data science, as well as the innovative concept of “Internet+” education, personalized e-learning has received widespread attention in school education and family education. The development of education informatization has led to a rapid increase in the number of online learning users and an explosion in the number of learning resources, which makes learners face the dilemma of “information overload” and “learning lost” in the learning process. In the personalized learning resource recommendation system, the most critical thing is the construction of the learner model. Currently, most learner models generally have a lack of scientific focus that they have a single method of obtaining dimensions, feature attributes, and low computational complexity. These problems may lead to disagreement between the learner’s learning ability and the difficulty of the recommended learning resources and may lead to the cognitive overload or disorientation of learners in the learning process. The purpose of this paper is to construct a learner model to support the above problems and to strongly support individual learning resources recommendation by learning the resource model which effectively reduces the problem of cold start and sparsity in the recommended process. In this paper, we analyze the behavioral data of learners in the learning process and extract three features of learner’s cognitive ability, knowledge level, and preference for learning of learner model analysis. Among them, the preference model of the learner is constructed using the ontology, and the semantic relation between the knowledge is better understood, and the interest of the student learning is discovered.

scholarly journals Digital Student Conference Platform Implementation: The case study of the “Research Project” course

2016 ◽  
Vol 12 (2) ◽  
pp. 5 ◽  
Author(s):  
Vasileios Orfanakis ◽  
Stamatios Papadakis ◽  
Michail Kalogiannakis ◽  
Maria Ampartzaki ◽  
Kostas Vassilakis
Keyword(s):  
Distance Learning ◽  
Learning Process ◽  
Teaching And Learning ◽  
Industrial Revolution ◽  
Rapid Development ◽  
Research Project ◽  
Digital Platform ◽  
Educational Methods ◽  
Active Involvement ◽  
Digital Ecosystem

Today, during the ‘fourth industrial revolution’ which is led by the Internet and the digital ecosystem it creates, schools are expected to achieve the development of not only the functional skills of literacy and numeracy but also of general knowledge. The apparent inadequacy of the standardized education system to respond to the needs and interests of 21st-century students urges researchers to adopt new forms of teaching as meaningful and high-quality teaching requires a more active use of innovative educational methods and tools. With the rapid development of IT globally, there is a tendency to utilize the capabilities of e-learning as a mode of distance learning since itcan function both independently of and in conjunction with conventional teaching. The varied applications of Web 2.0 tools create new possibilities in the educational sector. It provides the ability to develop innovative educational methods that transform students from passive recipients of information to knowledge creators through an active involvement in the learning process often within a modern interactive environment. This study presents the results of the implementation of a teaching intervention, with the use of a flexible and student-centered web system developed and used as complementary to the ‘Research Project’ course during the first term of the 2015-2016 school year. The ultimate goal of this effort was to highlight and consequently incorporate the use of a digital platform for student conferences which we implemented in schools as a means to research, learning, and skill development. The students had the opportunity to participate in a digital community which employed distance learning tools for communication, cooperation, and learning during a digital conference in which they had leading roles as writers and reviewers. The initial results of the pilot study indicated that the use of the digital platform increased the interest of students, supported the development of various skills and contributed to the overall improvement of the teaching and learning process.

scholarly journals PhET: SIMULASI INTERAKTIF DALAM PROSES PEMBELAJARAN FISIKA

2020 ◽  
Vol 5 (1) ◽  
pp. 10-14
Author(s):  
Dedi Riyan Rizaldi ◽  
A. Wahab Jufri ◽  
Jamal Jamal
Keyword(s):  
Data Collection ◽  
Learning Process ◽  
Physics Education ◽  
Rapid Development ◽  
Physics Learning ◽  
Library Research ◽  
Teachers And Students ◽  
Verbal Data ◽  
Education And Technology ◽  
Interactive Simulations

Abstrak: Perkembangan dunia teknologi dan informasi yang semakin pesat dapat memberikan alternatif bagi pendidik untuk menggunakan berbagai media pembelajaran salah satunya yaitu Physics Education and Technology (PhET). Tujuan penulisan artikel ini untuk menjelaskan tentang 1). Efektivitas penerapan media simulasi PhET dalam proses pembelajaran fisika, 2) Strategi penerapan media simulasi PhET dalam proses pembelajaran fisika, serta 3) Kelebihan dan kekurangan media simulasi PhET dalam proses pembelajaran fisika. Penulisan artikel ini menggunakan metode kualitatif berdasarkan filosofi post positivisme dengan teknik pengumpulan data berupa tri-anggulasi (gabungan), yaitu penelitian kepustakaan melalui pengumpulan data, terutama data verbal seperti buku, artikel, catatan, dan berbagai literatur ilmiah lainnya. Data yang dikumpulkan kemudian dianalisis secara induktif. Berdasarkan hasil tinjauan pustaka, analisis data, dan diskusi dapat disimpulkan bahwa 1). Media simulasi PhET secara efektif digunakan untuk membantu guru dan siswa dalam mempelajari konsep fisika, 2) media simulasi PhET sangat baik dikombinasikan dengan model pembelajaran inkuiri, dan 3) media simulasi PhET memiliki keuntungan yaitu efektif dalam menjelaskan konsep fisika yang sifatnya abstrak, sedangkan kekurangannya adalah bahwa implementasi di sekolah sangat tergantung pada unit komputer yang tersedia.Kata kunci: Simulasi Interaktif PhET, Inkuiri Terbimbing, Pembelajaran FisikaAbstract: The rapid development of technology and information world can provide an alternative for educators to use various learning media, one of which is Physics Education and Technology (PhET). The purpose of this review is to explain 1). The effectiveness of the application of PhET simulation media in the physics learning process, 2) The strategy of applying the PhET simulation media in the physics learning process, and 3) The anvantages and disanvantages of the PhET simulation media in the physics learning process. The writing of this article uses a qualitative method based on a post positivisme philosophy with data collection techniques in the form of tri-anggulation (combined), namely library research through data collection, especially verbal data such as books, articles, notes, and various other scientific literature. The data collected is then analyzed inductively. Based on the results of literature review, data analysis, and discussion it can be concluded that 1). PhET simulation media are effectively used to help teachers and students in learning physics concepts, 2) PhET simulation media are very well combined with inquiry learning models, and 3) PhET simulation media has the advantages of being effective in explaining abstract physical concepts, while the disadvantages is that the implementation in schools is very dependent on the computer units available.Keywords: PhET Interactive Simulations, Guided Inquiry, Physics Learning

scholarly journals An intelligence optimization method based on crowd intelligence for IoT devices

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ke Wang ◽  
Zheming Yang ◽  
Bing Liang ◽  
Wen Ji
Keyword(s):  
Genetic Algorithm ◽  
Design Methodology ◽  
Rapid Development ◽  
Optimization Method ◽  
The Internet ◽  
Content Type ◽  
Communication Capacity ◽  
Iot Devices ◽  
Crowd Intelligence ◽  
The Internet Of Things

Purpose The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in management. This study aims to optimize the member structure of the IoT so the members in it can work more efficiently. Design/methodology/approach In this paper, the authors consider from the perspective of crowd science, combining genetic algorithms and crowd intelligence together to optimize the total intelligence of the IoT. Computing, caching and communication capacity are used as the basis of the intelligence according to the related work, and the device correlation and distance factors are used to measure the improvement level of the intelligence. Finally, they use genetic algorithm to select a collaborative state for the IoT devices. Findings Experimental results demonstrate that the intelligence optimization method in this paper can improve the IoT intelligence level up to ten times than original level. Originality/value This paper is the first study that solves the problem of device collaboration in the IoT scenario based on the scientific background of crowd intelligence. The intelligence optimization method works well in the IoT scenario, and it also has potential in other scenarios of crowd network.

The Role Of Interactive Educational Technologies In Improving The Effectiveness Of Music Education

2020 ◽  
Vol 02 (12) ◽  
pp. 205-208
Author(s):  
Toshmatov Gulomjon ◽  
◽  
Goziyev Jobirkhan ◽  
Keyword(s):  
Music Education ◽  
Learning Process ◽  
Music Teachers ◽  
Interactive Learning ◽  
Learning Technologies ◽  
Educational Technologies

In this article the authors discuss the role of interactive and educational technologies and their effectiveness in the process of teaching for music teachers. Furthermore, the article gives information about concepts and information on the content, purpose and application of interactive learning technologies in the learning process.

Sign in / Sign up

Export Citation Format

Share Document