RPPTD: Robust Privacy-Preserving Truth Discovery Scheme

Chen, Jingxue; Liu, Yining; Xiang, Yong; Sood, Keshav

doi:10.1109/jsyst.2021.3099103

Cited by 28 publications

(11 citation statements)

References 27 publications

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“…On the other hand, attackers who violate user privacy data are usually service providers themselves or other relevant individual users, which makes it difficult for attackers to identify. Since the founding of the People's Republic of China in 1987, China has been making continuous efforts to establish and improve legal protection policies for various rights, including actively building a judicial protection system for individual privacy [13][14][15][16]. However, the legal protection of minors' privacy rights is still in the initial stage of development.…”

Section: Introductionmentioning

confidence: 99%

Construction and Management of Intelligent Campus Based on Student Privacy Protection under the Background of Artificial Intelligence and Internet of Things

2022

Mobile Information Systems

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With the coming of the era of artificial intelligence development and the mobile Internet of things, privacy security will become more and more prominent. As the contemporary college students have gradually developed into one of the main forces of the next generation of network information technology and intelligent terminals of Internet mobile communication, the problem of privacy and protection of college students in the era of artificial intelligence and the Internet of Things has naturally become a practical problem urgently solved by colleges and universities. This paper studies the application of “artificial intelligence + Internet of Things” (AIoT) in the construction and management of intelligent campus for student privacy protection. Firstly, some basic concepts and theories related to artificial intelligence and the Internet of Things are summarized, and the basic technical framework of “Artificial intelligence + Internet of Things” (AIoT) is preliminarily explained and analyzed. Secondly, relevant simulation experiments are carried out, and data support and help are provided for subsequent solutions and management methods by analyzing the simulation results. Through the investigation and analysis of the intelligent campus construction and management based on student privacy protection under the background of artificial intelligence and the Internet of Things, the final research results show that the background of artificial intelligence and the Internet of Things has a great role in promoting the function of student privacy protection, so this research has an important guiding role for student privacy protection in the context of artificial intelligence and the Internet of Things.

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Section: Introductionmentioning

confidence: 99%

Construction and Management of Intelligent Campus Based on Student Privacy Protection under the Background of Artificial Intelligence and Internet of Things

2022

Mobile Information Systems

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“…However, this technology poses severe security and privacy concerns. 98 Because IoT tools contain restricted resources, typical security measures are impracticable. As a result, a small IDS is needed.…”

Section: Discussionmentioning

confidence: 99%

A deep and systematic review of the intrusion detection systems in the fog environment

Yi¹,

Yin²,

Darbandi

2022

Trans Emerging Tel Tech

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Fog computing has arisen to complement cloud computing, offering a cost-effective architecture to power the Internet of things. Fog computing is a network computing and service paradigm that expands cloud computing and services to the network's edge to solve the cloud's fundamental shortcomings, like a lack of location awareness, mobility, and latency. Besides, fog devices may have security issues because fog nodes are near end-users and have limited computational power. As the linked devices in the Internet of things grow exponentially, so does the potential for cyber-attack. Intrusion detection systems have been developed as a feasible tool for detecting and preventing harmful activity in this vein. This work used a systematic literature review to examine intrusion detection system approaches in a fog environment. By categorizing intrusion detection systems in the literature, we produce a review. An intrusion detection system's characteristic is early identification of an attack and the decrease of false alarms as a result. Some of the issues that these systems' designers will face are also discussed. Recall rate, detection rates, detection delay, and detection precision were the parameters that received the most attention. This report will serve as a roadmap for future network intrusion detection studies in fog computing. 1• Numerous fog nodes are managed and controlled by a cloud computing center.

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“…where CD indicates critical distance of appliances, t 1 , t i represents distance between first and end transmission appliance, and δ i denotes total life period of appliances. e second minimization objective is framed using critical distance measurement by considering a reference potential point at the beginning of SCADA connections [21][22][23]. In addition to variations in critical distance measurements, the schedule period of storage for all appliances provides great advantage in the entire process as storage points can be shifted from one end to the other.…”

Section: Scada For Industrial Applications: An Analytical Modelmentioning

confidence: 99%

Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm

Khadidos

Manoharan³

et al. 2022

International Transactions on Electrical Energy Systems

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e process of ensuring automatic operation for industrial appliances using both supervision and control techniques is a challenging task.erefore, this article focuses on implementing Supervisory Control and Data Acquisition (SCADA) for controlling all industrial appliances. e design process of implementation case is performed using an analytical framework by examining the primary energy sources at the initial state; thus, a smart network is supported. e designed mathematical model is integrated with a learning technique that allocates resources at proper quantities. Further, the complex manual tuning of individual appliances is avoided in the projected method as the input variables are driven in a direct way at reduced loss state. In addition, the data processing state of individual appliances is carried out using central data controller where all parametric values are stored. In case any errors are observed, then SCADA network fixes the error in an automated way, reducing end-to-end delays in all appliances. To validate the effectiveness of the proposed method, five scenarios are examined and simulated where outcomes prove that SCADA network using learning models provides optimal results on an average of 84 percent as compared to the existing models without learning algorithm.

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RPPTD: Robust Privacy-Preserving Truth Discovery Scheme

Cited by 28 publications

References 27 publications

Construction and Management of Intelligent Campus Based on Student Privacy Protection under the Background of Artificial Intelligence and Internet of Things

Construction and Management of Intelligent Campus Based on Student Privacy Protection under the Background of Artificial Intelligence and Internet of Things

A deep and systematic review of the intrusion detection systems in the fog environment

Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm

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