The number of IoT devices connected to the global network is expected to be three times more, from 9.7 billion in 2020 to more than 29 billion in 2030. Globally connected IoT devices transmit enormous amounts of facts and figures daily via the internet for various purposes which is about users including important, intimate, or private information. As this data can be utilized for malevolent reasons, these devices constitute a privacy risk. IoT systems involved sensors gathering data from the environment, so known as cyber-physical systems which are highly vulnerable. Hence, user privacy issues such as password stealing, information and identity stealing, intruding, corrupting information, etc. are increasing day by day. Therefore, privacy experts and researchers are very much concerned about preventing user privacy issues and developed many PETs (blind signature, group signature, attribute-based credentials (ABCs), anonymous and pseudonymous data authentication, onion routing, encrypted communications, etc.) to prevent user privacy risks in IoT.
TopIntroduction
IoT (Internet of Things) is a system of connected devices, sensors, humans/animals, and objects provided by a unique identity. These can transfer and share data over the network independently. IoT can be human patient-wearing monitoring devices, animal-implanted chips, vehicles with GPS or sensors, and objects that are used to transfer information on the internet.
IoT has different definitions in different areas. Whitmore et al. (2015) note that IoT has no universal definition. According to IETF (Internet Engineering Task Force), IoT can be defined as the network of electronics, sensors, software, etc. embedded with physical objects that enable them to share and transfer data over the internet and other connected devices or person.
IoT technology is rapidly growing day by day. There were 7 billion IoT devices in 2018, in 2019 this increased to 26.6 million, and by 2013 connected IoT devices cross 31 billion [Statista.com].
This concept first emerges in the 1980s when university students amend Coca-Cola vending machines. They modified it to track its contents from distance. In 1999 Kevin Ashton devised the concept of IoT. During his work at Procter and Gamble, he purposed the concept of placing RFID chips on different products to track them via the supply chain (Aggarwal, 2012). This RFID technology then gained high fame and was adopted by the US Department of Defense and Walmart.
In the upcoming time as new IoT devices are introduced in industry and market, this technology gained a IoT of interest among people. The first smart refrigerator came into the market in 2000, apple launched 1st iPhone in the market in 2008 and the number of IoT devices keep on increasing day by day as technology advanced. Google played a significant role in this area, it tests 1st driverless car in 2009 and introduced Google’s Nest smart thermostat which can control central heating from distance, in 2012. United Nations International Telecommunications Union reported that IoT has grown to be a huge deal (Perera).
In a decade or more, IoT has expanded into a larger spectrum of applications such as house-holds, transport, medical, etc. (Sundmaeker, 2010). IoT has made astride towards fully integrated internet from static internet with the help of wireless tech such as Bluetooth, WiFi etc. according to Gubbi in (Tavares, 2014), creating smart environment by connecting these objects will be the upcoming revolution.
Architecture of IoT
The architecture of IoT (Internet of Things) can be divided into four layers:
- 1.
Perception Layer: This layer is responsible for collecting data from physical objects using sensors and other devices. These sensors may include temperature sensors, motion sensors, cameras, and more.
- 2.
Network Layer: This layer is responsible for transmitting the data collected by the perception layer to the cloud or other remote servers. The network layer may use Wi-Fi, Bluetooth, cellular networks, or other communication protocols to send the data.
- 3.
Application Layer: This layer is responsible for processing the data received from the network layer. The application layer may involve machine learning algorithms or other types of data analysis tools to make sense of the data.
- 4.
Business Layer: This layer is responsible for creating value from the data processed by the application layer. The business layer may involve creating reports, triggering alerts, or taking actions based on the insights gained from the data.
Overall, the IoT architecture is designed to enable communication between physical objects and the digital world. By collecting data from sensors and other devices, processing that data, and creating value from it, IoT systems can enable a wide range of applications, from smart homes to industrial automation (Rajendran, 2020).