By 2020, there will be an estimated 40 billion active wireless connected devices (Dickson, 2015) forming the Internet of Things. With the increase in data flows that allow the Internet of Things to bring greater convenience and functionality around the home, there is also the added risk of vulnerabilities if someone can access this data without your knowledge or permission. For example, if you have installed a device such as a smart thermostat or home security camera in your home that monitors your habits, this same information could be used maliciously against you e.g. by someone wanting to assess opportunities to break into your house.
To mitigate these types of risks, products such as DoJo pictured above, itself an IoT device, will patrol other IoT devices, watching out for virtual intruders. Once installed within a home, the DoJo device (designed to look like a pebble) monitors for attacks on the other domestic IoT devices sharing a wi-fi connection within that home via a base unit. When an attack is detected e.g. someone trying to hack into a user’s home security camera data, the pebble glows and a message gets sent to the user’s phone via a phone app prompting them to take action.
YouTube video of the DoJo product, from DoJo Labs (www.dojo-labs.com)
A number of themes relating to the course are brought up in this example:
- an initial idea from Star (1999) was that the ‘normally invisible quality of working infrastructure becomes visible when it breaks’. This product perhaps brings some greater visibility to your home infrastructure but interestingly its own infrastructure, the metadata it stores in the Cloud about the status of your devices is less visible. This Cloud of data from your home and other DoJo user’s homes itself becomes a potential source of vulnerability and gives a recursive quality as the security risk moves up a level. Who is monitoring the monitor?
- the border patrolled by DoJo is not the physical perimeter of your house and instead is based on the coverage of your wifi network and the particular devices connected to that network. It reminds me of Amoore’s (2006) study of biometric borders used to monitor passengers and how they cover data-driven borders rather than physical state borders.
- the idea of the citizen having to take care of their own welfare by installing such a device, to be personally responsible for these security risks. This reminds me of the discussions of the Neoliberal concepts of state and citizen that were explored for example by Von Schnitzler (2008) where homes in an area of South Africa were fitted with pre-paid water meters and individuals were expected to manage their own water consumptions.
- the blurred identity of this IoT product and how it differs from a typical commodity. Here the security threat is due to the value of the data flows circulating through the ‘thing’ in your IoT device rather than the discrete device.
References
Amoore, L. (2006). “Biometric borders: Governing Mobilities in the war on terror”. Political Geography 25 (3), 336-351.
Dickson, B. (2015). ‘Why IoT Security Is So Critical’. TechCrunch.com. Oct 24h 2015. Available from : http://techcrunch.com/2015/10/24/why-iot-security-is-so-critical [Accessed 21st April 2016]
Star, S. L. (1999). The Ethnography of Infrastructure. American Behavioral Scientist 43 (3), 377-391.
von Schnitzler, A. (2008). Citizenship prepaid: Water, calculability, and Techno-Politics in south africa*. Journal of Southern African Studies, 34(4):899-917.
anthropology of infrastructure 