scholarly journals Research on Key Technology of Security and Privacy Protection of Distribution Network Information Physical Fusion System

2021 ◽  
Vol 2136 (1) ◽  
pp. 012014
Author(s):  
Donghui Tong ◽  
Zhuo Di ◽  
Yi Ding ◽  
Xianhui Zhai
Keyword(s):  
Trust Management ◽  
Distribution Network ◽  
Human Interaction ◽  
Security And Privacy ◽  
Fusion System ◽  
Security Threat ◽  
State Monitoring ◽  
Research Information ◽  
Network Information ◽  
Guarantee System

Abstract As one of the most critical contents in the field of modern interdisciplinary research, information physical fusion not only changes the way of human interaction, but also promotes the development of modern information processing and development. Therefore, on the basis of making clear the current operation situation of distribution network information physical fusion system, this paper makes a simple understanding of the key technologies to guarantee system security and privacy from four aspects: security threat and response, crisis state and access control, reputation and trust management, and idle state monitoring algorithm.

scholarly journals STHM: A Secured and Trusted Healthcare Monitoring Architecture Using SDN and Blockchain

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1787
Author(s):  
Ezedin Barka ◽  
Sofiane Dahmane ◽  
Chaker Abdelaziz Kerrache ◽  
Mohamad Khayat ◽  
Farag Sallabi
Keyword(s):  
Monitoring System ◽  
Trust Management ◽  
Software Defined Networking ◽  
The Elderly ◽  
Optimal Level ◽  
Security And Privacy ◽  
Patient Privacy ◽  
Security Technologies ◽  
Blockchain Technology ◽  
Healthcare Monitoring

Healthcare professionals and scholars have emphasized the need for IoT-based remote health monitoring services to track the health of the elderly. Such systems produce a large amount of data, necessitating the security and privacy of that data. On the other hand, Software Defined Networking (SDN) integration could be seen as a good solution to guarantee both flexibility and efficiency of the network which is even more important in the case of healthcare monitoring. Furthermore, Blockchain has recently been proposed as a game-changing tool that can be integrated into the Internet of Things (IoT) to have the optimal level of security and privacy. However, incorporating Blockchain into IoT networks, which rely heavily on patients’ health sensors, is extremely difficult. In this paper, a secure Healthcare Monitoring System (HMS) is proposed with a focus on trust management issues. The architecture seeks to protect multiple healthcare monitoring system components and preserves patient privacy by developing a security interface where separate security modules can be integrated to run side by side to ensure reliable HMS. The security framework architecture we propose takes advantage of the blockchain technology as a secure and timely information back-end. STHM is a proposal that uses Software-Defined Networking (SDN) as the communication medium that allows users to access SDN’s different functional and security technologies and services. Simulation results show that the use of Blockchain for the SDN-based healthcare monitoring can ensure the desired flexibility and security for a very lightweight additional overhead.

EdgeTrust - A Lightweight Data-centric Trust Management Approach for Green Internet of Edge Things

2021 ◽  
Author(s):  
Kamran Ahmad Awan ◽  
Ikram Ud Din ◽  
Ahmad Almogren ◽  
Hasan Ali Khattak ◽  
Joel J.P.C. Rodrigues
Keyword(s):  
Trust Management ◽  
Data Centers ◽  
Threshold Value ◽  
Security And Privacy ◽  
Management Approach ◽  
Heterogeneous Environment ◽  
Local Data ◽  
Extensive Simulation ◽  
Daily Life Activities ◽  
Exchange Information

Abstract Internet of Things (IoT) is bringing revolution into today’s world where devices in our surroundings become smart and perform daily-life activities and operations with more precision. The architecture of IoT is heterogeneous as it provides autonomy to nodes that they can communicate among other nodes and can also exchange information at any period. Due to the heterogeneous environment, IoT faces numerous security and privacy challenges, and one of the most significant challenges is the identification of malicious and compromised nodes. In this article, we have proposed a Machine Learning-based trust management approach for edge nodes. The proposed approach is a lightweight process to evaluate trust because edge nodes cannot perform complex computations. To evaluate trust, the proposed mechanism utilizes the knowledge and experience component of trust where knowledge is further based on several parameters. To eliminate the triumphant execution of good and bad-mouthing attacks, the proposed approach utilizes edge clouds, i.e., local data centers, to collect recommendations to evaluate indirect and aggregated trust. The trustworthiness of nodes is ranked between a certain limit where only those that satisfy the threshold value can participate in the network. To validate the performance of a proposed approach we have performed an extensive simulation in comparison with the existing approaches and the result shows the effectiveness of the proposed approach against several potential attacks.

scholarly journals Economic Security Threat Modelling of a Commercial Bank in a Globalized Economy

2020 ◽  
pp. 142-151
Author(s):  
О.V. Dymchenko ◽  
О.О. Rudachenko ◽  
P. Gazzola
Keyword(s):  
Commercial Bank ◽  
Fuzzy Inference ◽  
A Priori ◽  
Economic Security ◽  
Security Threat ◽  
Research Information ◽  
Inference System ◽  
Security Research ◽  
Threat Modelling

In the paper, one develops a set of models for diagnosing threats to the economic security of a commercial bank, which allows improving the quality of decisions forming and making on managing the safe functioning and development of the bank. The bank's economic security research system has been developed, it includes 3 main blocks: research information space creation; assessment and analysis of the security of a commercial bank; generalization, and formation of decisions on the economic security of a commercial bank. The research made it possible to draw an inference of a theoretical, methodological, and applied nature that reflects the solution of the tasks set following the purpose of the study. A set of models has been built with modern tools of economic and mathematical modelling to improve the quality of decisions made to manage the bank's security and reduce the risks of threats. A model for calculating the bank's economic security indicator has been developed, which includes the following main stages: the construction of a structural scheme taking into account the rules of the theory of banking functioning security, then the terms and their membership functions are set for each input and output variable of the fuzzy inference system under consideration. Results of the response surface for the model are shown in the figure on the graphs of the dependence of the bank's economic security indicator on various input components. The paper requires that it is convenient to diagnose the state of economic security of a bank using fuzzy logic, this allows getting a clear quantitative representation of economic security state of the bank, as the indicators used for diagnostics may be indistinct and approximate and this a priori cannot give an adequate result when accurately calculated.

Intelligent Malware Detection Using Deep Dilated Residual Networks for Cyber Security

2021 ◽  
pp. 1085-1099
Author(s):  
S. Abijah Roseline ◽  
S. Geetha
Keyword(s):  
Machine Learning ◽  
Cyber Security ◽  
Machine Learning Algorithms ◽  
Human Interaction ◽  
Machine Learning Techniques ◽  
Detection Methods ◽  
Security Threat ◽  
Signature Detection ◽  
Learning Techniques ◽  
Feature Based

Malware is the most serious security threat, which possibly targets billions of devices like personal computers, smartphones, etc. across the world. Malware classification and detection is a challenging task due to the targeted, zero-day, and stealthy nature of advanced and new malwares. The traditional signature detection methods like antivirus software were effective for detecting known malwares. At present, there are various solutions for detection of such unknown malwares employing feature-based machine learning algorithms. Machine learning techniques detect known malwares effectively but are not optimal and show a low accuracy rate for unknown malwares. This chapter explores a novel deep learning model called deep dilated residual network model for malware image classification. The proposed model showed a higher accuracy of 98.50% and 99.14% on Kaggle Malimg and BIG 2015 datasets, respectively. The new malwares can be handled in real-time with minimal human interaction using the proposed deep residual model.

Data Security and Privacy-Preserving in Edge Computing

2021 ◽  
pp. 188-202
Author(s):  
Manoranjini J. ◽  
Anbuchelian S.
Keyword(s):  
Trust Management ◽  
Edge Computing ◽  
Security And Privacy ◽  
Promising Technology ◽  
Research Areas ◽  
Massive Growth ◽  
Security Models ◽  
Current Scenario ◽  
Cryptographic Techniques ◽  
Privacy Issues

The rapid massive growth of IoT and the explosive increase in the data used and created in the edge networks led to several complications in the cloud technology. Edge computing is an emerging technology which is ensuring itself as a promising technology. The authors mainly focus on the security and privacy issues and their solutions. There are a lot of important features which make edge computing the most promising technology. In this chapter, they emphasize the security and privacy issues. They also discuss various architectures that enable us to ensure safe technologies and also provide an analysis on various designs that enable strong security models. Next, they make a detailed study on different cryptographic techniques and trust management systems. This study helps us to identify the pros and cons that led us to promising implementations of edge computing in the current scenario. At the end of the chapter, the authors discuss on various open research areas which could be the thrust areas for the next era.

scholarly journals AgriTrust—A Trust Management Approach for Smart Agriculture in Cloud-based Internet of Agriculture Things

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6174 ◽  
Author(s):  
Kamran Ahmad Awan ◽  
Ikram Ud Din ◽  
Ahmad Almogren ◽  
Hisham Almajed
Keyword(s):  
Trust Management ◽  
Service Providers ◽  
Base Station ◽  
Security And Privacy ◽  
Management Approach ◽  
Time Interval ◽  
Management Mechanism ◽  
Trust Degree ◽  
Smart Agriculture ◽  
Compromised Nodes

Internet of Things (IoT) provides a diverse platform to automate things where smart agriculture is one of the most promising concepts in the field of Internet of Agriculture Things (IoAT). Due to the requirements of more processing power for computations and predictions, the concept of Cloud-based smart agriculture is proposed for autonomic systems. This is where digital innovation and technology helps to improve the quality of life in the area of urbanization expansion. For the integration of cloud in smart agriculture, the system is shown to have security and privacy challenges, and most significantly, the identification of malicious and compromised nodes along with a secure transmission of information between sensors, cloud, and base station (BS). The identification of malicious and compromised node among soil sensors communicating with the BS is a notable challenge in the BS to cloud communications. The trust management mechanism is proposed as one of the solutions providing a lightweight approach to identify these nodes. In this article, we have proposed a novel trust management mechanism to identify malicious and compromised nodes by utilizing trust parameters. The trust mechanism is an event-driven process that computes trust based on the pre-defined time interval and utilizes the previous trust degree to develop an absolute trust degree. The system also maintains the trust degree of a BS and cloud service providers using distinct approaches. We have also performed extensive simulations to evaluate the performance of the proposed mechanism against several potential attacks. In addition, this research helps to create friendlier environments and efficient agricultural productions for the migration of people to the cities.

A WSN-Oriented Key Agreement Protocol in Internet of Things

2013 ◽  
Vol 401-403 ◽  
pp. 1792-1795 ◽  
Author(s):  
Tao Liu ◽  
Ya Wen Guan ◽  
Yi Qun Yan ◽  
Li Liu ◽  
Qi Chao Deng
Keyword(s):  
Internet Of Things ◽  
Trust Management ◽  
Key Agreement ◽  
Bilinear Pairing ◽  
Negotiation Process ◽  
Third Party ◽  
Security And Privacy ◽  
The Internet ◽  
Key Agreement Protocol ◽  
The Internet Of Things

Aimed to the security and privacy issues which restrict the construction and development of the Internet of Things, a WSN-oriented key agreement protocol in the Internet of Things ( IOT) has been proposed . Trust management was introduced the security mechanism of IOT, the use of bilinear pairing technology, the identity-based key agreement was realized. Using the protocol not only can effectively prevent attacks from outside the network and can recognize the abnormal nodes which were captured or lapsed efficacy. Thus it can reduce communication with abnormal nodes to improve network security, extending the lifetime of the network. The distributed self-organizing key negotiation process without credible third-party management can enhance the survivability of IOT, and the network has a good scalability.

scholarly journals Transient brain networks underlying interpersonal strategies during synchronized action

2020 ◽  
Author(s):  
Ole Adrian Heggli ◽  
Ivana Konvalinka ◽  
Joana Cabral ◽  
Elvira Brattico ◽  
Morten L Kringelbach ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Network ◽  
Human Interaction ◽  
Action Perception ◽  
Network Information ◽  
Mutual Adaptation ◽  
Underlying Mechanisms ◽  
The Brain

Abstract Interpersonal coordination is a core part of human interaction, and its underlying mechanisms have been extensively studied using social paradigms such as joint finger-tapping. Here, individual and dyadic differences have been found to yield a range of dyadic synchronization strategies, such as mutual adaptation, leading–leading, and leading–following behaviour, but the brain mechanisms that underlie these strategies remain poorly understood. To identify individual brain mechanisms underlying emergence of these minimal social interaction strategies, we contrasted EEG-recorded brain activity in two groups of musicians exhibiting the mutual adaptation and leading–leading strategies. We found that the individuals coordinating via mutual adaptation exhibited a more frequent occurrence of phase-locked activity within a transient action–perception-related brain network in the alpha range, as compared to the leading–leading group. Furthermore, we identified parietal and temporal brain regions that changed significantly in the directionality of their within-network information flow. Our results suggest that the stronger weight on extrinsic coupling observed in computational models of mutual adaptation as compared to leading–leading might be facilitated by a higher degree of action–perception network coupling in the brain.

scholarly journals Shadow Pricing of Electric Power Interruptions for Distribution System Operators in Finland

2018 ◽  
Author(s):  
Sinan Küfeoğlu ◽  
Niyazi Gündüz ◽  
Hao Chen ◽  
Matti Lehtonen
Keyword(s):  
Electric Power ◽  
Distribution System ◽  
Distribution Network ◽  
Extreme Weather Events ◽  
Distribution Grid ◽  
Electric Power Supply ◽  
Network Information ◽  
Shadow Pricing ◽  
Weather Events ◽  
The Cost

Increasing distributed generation and intermittency, along with the increasing frequency of extreme weather events, impose a serious challenge for the electric power supply security. Understanding the costs of interruption is vital in terms of enhancing the power system infrastructure and planning the distribution grid. On the other hand, customer rights and demand response techniques are further reasons to study the worth of power reliability. In this paper, the authors make use of directional distance function and shadow pricing method for a case study from Finland. The aim is to calculate the cost of one minute of power interruption from the distribution network operator perspective. The sample consists of 78 distribution network operators from Finland with cost and network information between 2013 and 2015.

scholarly journals Mobile edge computing for internet of things (IoT): security and privacy issues

2020 ◽  
Vol 18 (3) ◽  
pp. 1486
Author(s):  
Atiqur Rahman ◽  
Guangfu Wu ◽  
Ali Md Liton
Keyword(s):  
Internet Of Things ◽  
Edge Computing ◽  
Security And Privacy ◽  
Mobile Edge Computing ◽  
Security Threat ◽  
Protection Mechanism ◽  
Challenges And Opportunities ◽  
Privacy Issues ◽  
Computing Structure

Nowadays, the masonry for environment-friendly and protected network structure designs, for example, the Internet of Things and gigantic data analytics are increasing at a faster pace compared to an earlier state. Mobile edge computing for an Internet of Things widget is information processing that is achieved at or close to the collectors of information in an Internet of Things system. Herein, we are proposing to temporarily evaluation the concepts, features, protection, and privacy applications of Internet of Things authorized mobile edge computing with its data protection view in our data-driven globe. We focus on illuminating one of kind components that need to be taken into consideration whilst creating a scalable, consistent, impenetrable and disseminated mobile edge computing structure. We also sum up the fundamental ideas regarding security threat alleviation strategies. After that, we walk around the existing challenges and opportunities in the area of mobile edge computing. In conclusion, we analyze a case study, in which a security protection mechanism can be hardened to lift out everyday jobs.

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