Abstract for Week of Undergraduate
Excellence
Sarah Malik, Dr. Murugan Anandarajan LeBow College of Business Medical Devices, IoT, and Security
According to Gartner, over 26 billion devices will be connected through the Internet of Things (IoT) and result in $1.9 trillion in global economic value-add through sales by 2020. Furthermore, 40% of IoT-related technology will be health related, more than any other category, making up $117 billion market (Baur et al., 2016). IoT is defined as a collection of identifiable things (or nodes) with the ability to communicate (send and receive commands) over wired or wireless communication medium (Thangavel, 2015). Numerous applications such as heart rate monitors and blood pressure monitors are already in use for the IoT for Medical Devices (IoMT), and poise to revolutionize the function of the healthcare industry (Ameen et al., 2010; Khanna & Misra, 2014). This interconnectivity leaves medical devices vulnerable to security breaches in the same way other networked computing systems are vulnerable and there is an increasing concern that connectivity of these medical devices will directly affect clinical care and patient safety (Williams & Woodward, 2015). Therefore, the focus of this study is to identify potential threats to IoT devices and purpose a control mechanism through the situational crime prevention theory to reduce the impact of such threats.
Sarah Malik, Dr. Murugan Anandarajan LeBow College of Business Medical Devices, IoT, and Security
According to Gartner, over 26 billion devices will be connected through the Internet of Things (IoT) and result in $1.9 trillion in global economic value-add through sales by 2020. Furthermore, 40% of IoT-related technology will be health related, more than any other category, making up $117 billion market (Baur et al., 2016). IoT is defined as a collection of identifiable things (or nodes) with the ability to communicate (send and receive commands) over wired or wireless communication medium (Thangavel, 2015). Numerous applications such as heart rate monitors and blood pressure monitors are already in use for the IoT for Medical Devices (IoMT), and poise to revolutionize the function of the healthcare industry (Ameen et al., 2010; Khanna & Misra, 2014). This interconnectivity leaves medical devices vulnerable to security breaches in the same way other networked computing systems are vulnerable and there is an increasing concern that connectivity of these medical devices will directly affect clinical care and patient safety (Williams & Woodward, 2015). Therefore, the focus of this study is to identify potential threats to IoT devices and purpose a control mechanism through the situational crime prevention theory to reduce the impact of such threats.