An Exploration of the Factors Influencing Home Users' Cybersecurity Behaviours

<p>Cybersecurity has been a concern for businesses and governments since their initial uptake of the Internet in the 1970s. As more and more people started using the internet for personal use, cybersecurity has become an important concern for home users as well. However, most research on cybersecurity has been undertaken at an organisational rather than at the individual level. Individual behaviours online have became increasingly important as the line between home and business use has blurred and users’ actions on their home computers has begun to have more wide ranging implications. There appears to be a lack of agreement on how to approach the topic of internet security outside of an organisational perspective. This research focuses on the individual home user perspective and seeks to (1) identify factors relate to users’ cybersecurity behaviours, and (2) examine how the identified factors relate to users' cybersecurity behaviours. A conceptual framework was developed based on the literature to guide the data collection. To identify the relevant factors relating to home users’ security behaviours, a qualitative study comprised of three focus groups and 20 individual interviews was carried out. From the data, a revised model was developed. In the revised model, awareness threats was identified as a necessary first cybersecurity step before users can form opinions about the danger of threats. Awareness of threats was influenced by users' characteristics, opinions, and experiences as well as by factors in their external environments. The combination of internal factors, external factors, and awareness led to users’ perceptions about the danger of threats online. This perception of danger led to users’ intentions to engage in protective behaviours. However, these intentions were strengthened or weakened based on users’ perceptions about the barriers to and enablers of security. By applying the revised model, it was possible to identify different types of security users. Through the identification of these user types, eight factors emerged as being particularly important in influencing users' perceptions of threats and dangers: knowledge, perceived self-efficacy, trust, threat awareness, safeguard awareness, prior experience, reliance, and security orientation. These factors from the model are used as a starting point to understanding how users make decisions about what they will do to protect themselves online. Further, through the identification of these user types suggestions are made about how to promote security for different types of individuals.</p>

An Exploration of the Factors Influencing Home Users' Cybersecurity Behaviours

<p>Cybersecurity has been a concern for businesses and governments since their initial uptake of the Internet in the 1970s. As more and more people started using the internet for personal use, cybersecurity has become an important concern for home users as well. However, most research on cybersecurity has been undertaken at an organisational rather than at the individual level. Individual behaviours online have became increasingly important as the line between home and business use has blurred and users’ actions on their home computers has begun to have more wide ranging implications. There appears to be a lack of agreement on how to approach the topic of internet security outside of an organisational perspective. This research focuses on the individual home user perspective and seeks to (1) identify factors relate to users’ cybersecurity behaviours, and (2) examine how the identified factors relate to users' cybersecurity behaviours. A conceptual framework was developed based on the literature to guide the data collection. To identify the relevant factors relating to home users’ security behaviours, a qualitative study comprised of three focus groups and 20 individual interviews was carried out. From the data, a revised model was developed. In the revised model, awareness threats was identified as a necessary first cybersecurity step before users can form opinions about the danger of threats. Awareness of threats was influenced by users' characteristics, opinions, and experiences as well as by factors in their external environments. The combination of internal factors, external factors, and awareness led to users’ perceptions about the danger of threats online. This perception of danger led to users’ intentions to engage in protective behaviours. However, these intentions were strengthened or weakened based on users’ perceptions about the barriers to and enablers of security. By applying the revised model, it was possible to identify different types of security users. Through the identification of these user types, eight factors emerged as being particularly important in influencing users' perceptions of threats and dangers: knowledge, perceived self-efficacy, trust, threat awareness, safeguard awareness, prior experience, reliance, and security orientation. These factors from the model are used as a starting point to understanding how users make decisions about what they will do to protect themselves online. Further, through the identification of these user types suggestions are made about how to promote security for different types of individuals.</p>

Precision Farming and Smart Irrigation using IoT

Agriculture is the spine of Indian Economy. It mainly depends on Irrigation. The Internet Of Things is used to farmers are easier to monitor and control water possessions. This paper proposed, IoT architecture customized for smart irrigation application. Arduino board is used to communicate a variety of sensors like ultrasonic, soil moistur and light sensors. This work managed to decrease the expenditure, diminish devastate water and diminish substantial individual edge. Relay is developed to organize the switching of solenoid. Also, the scheme preserved to measure the soil moisture. It controls the solenoid valve according to human. Graphical User Interface (GUI) connected withAndroid application to motivate watering movement. SMS alert moreover sent to the home user in critical situations.

A Multi-Objective Approach for Optimal Energy Management in Smart Home Using the Reinforcement Learning

Maintaining a fair use of energy consumption in smart homes with many household appliances requires sophisticated algorithms working together in real time. Similarly, choosing a proper schedule for appliances operation can be used to reduce inappropriate energy consumption. However, scheduling appliances always depend on the behavior of a smart home user. Thus, modeling human interaction with appliances is needed to design an efficient scheduling algorithm with real-time support. In this regard, we propose a scheduling algorithm based on human appliances interaction in smart homes using reinforcement learning (RL). The proposed scheduling algorithm divides the entire day into various states. In each state, the agents attached to household appliances perform various actions to obtain the highest reward. To adjust the discomfort which arises due to performing inappropriate action, the household appliances are categorized into three groups i.e., (1) adoptable, (2) un-adoptable, (3) manageable. Finally, the proposed system is tested for the energy consumption and discomfort level of the home user against our previous scheduling algorithm based on least slack time phenomenon. The proposed scheme outperforms the Least Slack Time (LST) based scheduling in context of energy consumption and discomfort level of the home user.

Performance of nurses/nursing team in the dispensing of materials for users of home care services

ABSTRACT Objective: To contextualize the performance of nurses/nursing team in the dispensing of materials to assist users in home visits, in primary care. Methods: Dialectical qualitative study conducted between March and April 2018 in which 24 nurses from primary health care units in the Gloria/Cruzeiro/Cristal District of Porto Alegre, Rio Grande do Sul, completed the self-administered questionnaire, whose data were treated by thematic content analysis. The study was approved by the Research Ethics Committee. Results: Two categories emerged from the empirical corpus: logistic chain of material management for home user assistance; production of services and capacity of the team. Conclusion: The work processes related to materials management for home user assistance and the resulting health services production require a look at specificities such as workload and technologies involved, as they move the performance of the nurse/nursing staff.

Using online third party geolocation services to improve smart home user experience

This paper presents one approach to improve smart home user experience, by providing location-based services. Within the cloud of the existing smart home solution, the geolocation micro-service is first implemented. This micro-service communicates with third party online geolocation service to obtain latitude and longitude values from physical address and vice versa. The geolocation micro-service is used by different services to provide location-based experience. For example, weather micro-service uses the geolocation information, to provide weather content, while the traffic service monitors traffic conditions in the vicinity of the household. This information can be used to setup different automation rules in the system.