scholarly journals Acceptance of Smart Electronic Monitoring at Work as a Result of a Privacy Calculus Decision

Informatics ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 40
Author(s):  
Evgenia Princi ◽  
Nicole C. Krämer
Keyword(s):  
Electronic Monitoring ◽  
Detection System ◽  
Monitoring Systems ◽  
The Internet ◽  
Privacy Concerns ◽  
User Data ◽  
Privacy Calculus ◽  
System Acceptance ◽  
Emergency Detection ◽  
The Internet Of Things

Smart technology in the area of the Internet of Things (IoT) that extensively gathers user data in order to provide full functioning has become ubiquitous in our everyday life. At the workplace, individual’s privacy is especially threatened by the deployment of smart monitoring technology due to unbalanced power relations. In this work we argue that employees’ acceptance of smart monitoring systems can be predicted based on privacy calculus considerations and trust. Therefore, in an online experiment (N = 661) we examined employees’ acceptance of a smart emergency detection system, depending on the rescue value of the system and whether the system’s tracking is privacy-invading or privacy-preserving. We hypothesized that trust in the employer, perceived benefits and risks serve as predictors of system acceptance. Moreover, the moderating effect of privacy concerns is analyzed.

Sustainable Security for the Internet of Things Using Artificial Intelligence Architectures

2021 ◽  
Vol 21 (3) ◽  
pp. 1-22
Author(s):  
Celestine Iwendi ◽  
Saif Ur Rehman ◽  
Abdul Rehman Javed ◽  
Suleman Khan ◽  
Gautam Srivastava
Keyword(s):  
Internet Of Things ◽  
Detection System ◽  
Experimental Testing ◽  
Cyber Attacks ◽  
Internet Technology ◽  
The Internet ◽  
Business Operations ◽  
Private Data ◽  
The Internet Of Things ◽  
Better Than

In this digital age, human dependency on technology in various fields has been increasing tremendously. Torrential amounts of different electronic products are being manufactured daily for everyday use. With this advancement in the world of Internet technology, cybersecurity of software and hardware systems are now prerequisites for major business’ operations. Every technology on the market has multiple vulnerabilities that are exploited by hackers and cyber-criminals daily to manipulate data sometimes for malicious purposes. In any system, the Intrusion Detection System (IDS) is a fundamental component for ensuring the security of devices from digital attacks. Recognition of new developing digital threats is getting harder for existing IDS. Furthermore, advanced frameworks are required for IDS to function both efficiently and effectively. The commonly observed cyber-attacks in the business domain include minor attacks used for stealing private data. This article presents a deep learning methodology for detecting cyber-attacks on the Internet of Things using a Long Short Term Networks classifier. Our extensive experimental testing show an Accuracy of 99.09%, F1-score of 99.46%, and Recall of 99.51%, respectively. A detailed metric representing our results in tabular form was used to compare how our model was better than other state-of-the-art models in detecting cyber-attacks with proficiency.

Sistem Keamanan Gedung Menggunakan Kinect Xbox 360 Dengan Metode Skeletal Tracking

2021 ◽  
Vol 5 (6) ◽  
pp. 1137-1142
Author(s):  
Hamdi Alchudri ◽  
Zaini
Keyword(s):  
Optical Data ◽  
Visual Images ◽  
The Internet ◽  
Transmission Method ◽  
Sensor Reading ◽  
Loss Of Life ◽  
Analog To Digital ◽  
Cloud Server ◽  
User Data ◽  
The Internet Of Things

The incidence of fire and theft is very threatening and causes disruption to people's lifestyles, both due to natural and human factors resulting in loss of life, damage to the environment, loss of property and property, and psychological impacts. The purpose of this study is to create a building security system using Kinect Xbox 360 which can be used to detect fires and loss of valuable objects. The data transmission method uses the Internet of Things (IoT) and skeletal tracking. Skeletal detection uses Arduino Uno which is connected to a fire sensor and Kinect to detect suspicious movements connected to a PC. Kinect uses biometric authentication to automatically enter user data by recognizing objects and detecting skeletons including height, facial features and shoulder length. The ADC (Analog to Digital Converter) value of the fire sensor reading has a range between 200-300. The fire sensor detects the presence of fire through optical data analysis containing ultraviolet, infrared or visual images of fire. The data generated by Kinect by detecting the recognition of the skeleton of the main point of the human body known as the skeleton, where the reading point is authenticated by Kinect from a range of 1.5-3 meters which is declared the optimal measurement, and if a fire occurs, the pump motor will spray water randomly. to extinguish the fire that is connected to the internet via the wifi module. The data displayed is in the form of a graph on the Thingspeak cloud server service. Notification of fire and theft information using the delivery system from input to database

The Internet of Things and its impact on the library

2016 ◽  
Vol 117 (3/4) ◽  
pp. 289-292 ◽  
Author(s):  
Bruce Massis
Keyword(s):  
Internet Of Things ◽  
Literature Review ◽  
Design Methodology ◽  
Security And Privacy ◽  
The Internet ◽  
Content Type ◽  
Privacy Concerns ◽  
Potential Impact ◽  
The Internet Of Things

Purpose – The purpose of this paper is to consider the Internet of Things (IOT) and its potential impact on libraries. Design/methodology/approach – This paper presents a literature review and a commentary on this topic that have been addressed by professionals, researchers and practitioners. Findings – In communicating the issues when comprehending the scope of the IOT, libraries need not succumb to the sometimes near-hysteria that surrounds the rhetoric regarding security and privacy. But, librarians must actively engage in the conversation and its subsequent actions to respond to patrons who use library networks and devices with calm, logical and transparent answers to those questions concerning what they are doing to ensure that security and privacy vulnerabilities are regularly addressed. Originality/value – The value in concentrating on this topic is to provide background and suggest several approaches to security and privacy concerns regarding the IOT.

scholarly journals Internet of things (IoT) based I-V curve tracer for photovoltaic monitoring systems

2019 ◽  
Vol 13 (3) ◽  
pp. 1022 ◽  
Author(s):  
H. B. Chi ◽  
M. F. N. Tajuddin ◽  
N. H. Ghazali ◽  
A. Azmi ◽  
M. U. Maaz
Keyword(s):  
Internet Of Things ◽  
Low Cost ◽  
Experimental Tests ◽  
Monitoring Systems ◽  
The Internet ◽  
Control Software ◽  
Curve Tracer ◽  
Current Voltage ◽  
The Internet Of Things

<span>This paper presents a low-cost PV current-voltage or <em>I-V</em> curve tracer that has the Internet of Things (IoT) capability. Single ended primary inductance converter (SEPIC) is used to develop the <em>I-V</em> tracer, which is able to cope with rapidly changing irradiation conditions. The <em>I-V</em> tracer control software also has the ability to automatically adapt to the varying irradiation conditions. The performance of the <em>I-V</em> curve tracer is evaluated and verified using simulation and experimental tests.</span>

scholarly journals Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1977 ◽  
Author(s):  
Geethapriya Thamilarasu ◽  
Shiven Chawla
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Learning Algorithm ◽  
Detection System ◽  
Cyber Attacks ◽  
The Internet ◽  
Critical Systems ◽  
The Internet Of Things

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively.

Research on the Intelligent Monitoring System of Indoor Electrical Safety Based on the Internet of Things

2014 ◽  
Vol 986-987 ◽  
pp. 1569-1573 ◽  
Author(s):  
Chen Jiang ◽  
Lei Zhou ◽  
Xiao Ju Liu ◽  
Xiao Liang Xu
Keyword(s):  
Real Time ◽  
Internet Technology ◽  
Electrical Safety ◽  
Monitoring Systems ◽  
The Internet ◽  
Intelligent Monitoring ◽  
Safety Risks ◽  
Embedded Microprocessor ◽  
Microprocessor Technology ◽  
The Internet Of Things

This paper presents a set of schemes of centralized indoor electrical safety intelligent monitoring systems which are more intelligent, real-time and reliable based on the internet technology of things. Integrated use of wireless sensor networks, embedded microprocessor technology is realized. Hall sensor is used to collect the real-time current on the power grid. As well, This system utilizes the method of the subspace pattern recognition to identify electrical appliances and eliminate some safety risks of the domestic distribution network through the fault arc detection.

scholarly journals Optical-electronic monitoring system of biomedical indicators

2020 ◽  
Vol 21 (4) ◽  
pp. 779-784
Author(s):  
G.I. Barylo ◽  
M.S. Ivakh ◽  
Z.M. Mykytiuk ◽  
I.P. Kremer
Keyword(s):  
Optical Radiation ◽  
Electronic Monitoring ◽  
The Internet ◽  
Medical Systems ◽  
Biological Objects ◽  
Wide Range ◽  
Signal Path ◽  
Measurement Transformation ◽  
The Internet Of Things ◽  
Methods Of Measurement

The work is devoted to the development of medical systems for monitoring biomedical indicators. The problem of developing a universal hardware software-controlled control system for the diagnosis of biological objects is solved. The main requirements for such a system are a wide range of functionality for combining different methods of measurement transformation and compliance with modern trends in the development of microelectronic sensors. Given the requirements for modern microcircuitry, in particular for sensing devices of the Internet of Things, the signal path of the sensors is implemented on the basis of PSoC family 5LP Family Cypress. Approbation of the developed system is carried out in the course of research of the character of optical radiation in the course of measurement of biomedical indicators.

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