نمونه متن انگلیسی مقاله
Internet of things (IoT) offer new opportunities for advancement in many domains including healthcare, home automation, manufacturing and transportation. In recent years, the number of IoT devices have exponentially risen and this meteoric rise is poised to continue according to the industry. Advances in the IoT integrated with ambient intelligence are intended to make our lives easier. Yet for all these advancements, IoT also has a dark side. Privacy and security were already priorities when personal computers, devices and work stations were the only point of vulnerability to personal information, however, with the ubiquitous nature of smart technologies has increased data collection points around us exponentially. Beyond that, the massive amount of data collected by IoT devices is relatively unknown and uncontrolled by users thereby exacerbating privacy issues and concerns. This study aims to create better understanding of privacy concerns stemming from most popular smart technologies, categorizing the data collected by them. We investigate how the data collection raises information privacy concerns among users of IoT.
Rapid advancements in electronics and connectivity have enabled users to connect everyday ‘things’ such as home appliances, vehicles and, wearables to each other. As chips get smaller and gain more processing power (Moore’s Law), embedding physical objects with actuators, sensors and, small computers has become easier. Connectivity among these ‘things’ help users better monitor themselves (wearable technologies) and their environments (thermostats and motion sensors), increase convenience in everyday tasks (smart speakers, baby monitors) and, do plethora of other tasks that were not automated before (storefronts, smart locks, smart beds, vacuum cleaner). Internet of Things (IoT) is defined as ‘connectivity of physical objects equipped with sensors and actuators to Internet via data communication technologies’(Oberländer, Röglinger, Rosemann, & Kees, 2018). Advances in IoT integrated with ambient intelligence can assist the elderly in daily living tasks making them more independent (Dohr, Modre-Opsrian, Drobics, Hayn, & Schreier, 2010), help people monitor their health (Yang et al., 2014), automate many tasks around the house (Gubbi, Buyya, Marusic, & Palaniswami, 2013) and, help to make driving safer (Chang et al., 2009). For all the good smart technology is poised to accomplish there can be many unintended consequences. Recent news reports of home security cameras being used in hacking attacks (KYODO, 2018) and physical fitness device data inadvertently showing the location of secret military bases underscore the security consequences (Taylor, 2018).
Our qualitative investigation proposed a device level analysis of data collection abilities of most used IoT devices. This part of study is chosen to be qualitative because there is limited research done on this group of devices. In future, we would consider adding laboratory experiments on these devices to further establish content validity. For our second objective, we are modifying Malhotra et al 2004’s IUIPC scales according to the results of objective 1 in hopes of adding to the body of knowledge about user awareness. At this point of time, the study is a work in progress but we hope it will make significant contribution in IS literature in fields of privacy and user awareness.