Difference between revisions of "SMT483G2: AThings Overview"
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= Project Background = | = Project Background = | ||
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| + | Recent advances on the Internet of Things (IoT) have enabled a myriad of smart applications such as smart home, smart transportation, smart environment, smart healthcare, etc. According to Statista (2017), the number of smart devices around the world is estimated to be 75.44 billion in 2025. These devices are typically equipped with sophisticated sensors, such as temperature, humidity, light, face, and motion. The amount of data these devices generated and the kind of operations these devices could perform tend to be privacy-, security-, and safety-sensitive. Thus, applications operating and interacting with these devices could have become a highly attractive attack surface for attackers. Kaspersky (2019) reported that there have been more than 100 million cybersecurity attacks on IoT devices and applications in the first six months of year 2019 alone. | ||
| + | Security issues in IoT applications could easily lead to serious physical, financial, and psychological harms. For example, a malicious IoT app can take over the control of a smart car and threaten peoples’ lives. This project contributes to the advancement of information technology in terms of detecting anomalies in IoT applications that could cause such catastrophic affects. | ||
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| + | After detecting anomalous behaviors of IoT applications and generating random test cases, it is important to find the sequence of events to systematically deal with inter-dependencies and diverse nature of IoT ecosystem. | ||
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Revision as of 15:02, 26 September 2020
Project Background
Recent advances on the Internet of Things (IoT) have enabled a myriad of smart applications such as smart home, smart transportation, smart environment, smart healthcare, etc. According to Statista (2017), the number of smart devices around the world is estimated to be 75.44 billion in 2025. These devices are typically equipped with sophisticated sensors, such as temperature, humidity, light, face, and motion. The amount of data these devices generated and the kind of operations these devices could perform tend to be privacy-, security-, and safety-sensitive. Thus, applications operating and interacting with these devices could have become a highly attractive attack surface for attackers. Kaspersky (2019) reported that there have been more than 100 million cybersecurity attacks on IoT devices and applications in the first six months of year 2019 alone.
Security issues in IoT applications could easily lead to serious physical, financial, and psychological harms. For example, a malicious IoT app can take over the control of a smart car and threaten peoples’ lives. This project contributes to the advancement of information technology in terms of detecting anomalies in IoT applications that could cause such catastrophic affects.
After detecting anomalous behaviors of IoT applications and generating random test cases, it is important to find the sequence of events to systematically deal with inter-dependencies and diverse nature of IoT ecosystem.
About Our Data
Abstract
Phase I
Phase II
- week 1 - week 7
- week 8 - week 13
