Data-Carving: A Data Scavenger Hunt
The Internet is not the only place to lose your privacy or identity. Although more and more personal data is stored on the Internet servers, it is still written to hard-disks.
In this two-part workshop, explore the contents of old hard-drives, SD-cards, public wifi-signals and other found data. Using methods borrowed from computer digital forensics participants will peek into the lives of others – users and owners of scavenged data. Deductively, we will try to discuss and recreate ‘psyche’ portraits of those strangers and restore the contexts that otherwise would have faded away. In the process, learn and collect wi-fi signals. By the end of the workshop all data will be destroyed!
Knowledge of command line is advantageous, but not required.
– an old data storage device, i.e. hard drives, SD cards (your own or find one at a flea market or eBay; the older the better. Disks don’t need to be of large capacity)
– laptop capable of running Virtualbox (OS X, GNU/Linux, Windows)
(please email [email protected] if you cannot secure either item. Eyebeam can provide computers; and harddrives first come, first serve)
ABOUT THE INSTRUCTOR
Danja Vasiliev is a Critical Engineer born in Saint-Petersburg, currently living and working in Berlin. He studies Systems and Networks through anti-disciplinary experimentation with hardware, firmware and software. Using computational platforms he engages in examination and exploitation of System and Network paradigms in both the physical and digital realms. Based on these findings, Vasiliev creates and exhibits works of Critical Engineering. Since 1999 Vasiliev has been involved in computer-technology events, media-art exhibitions and seminars around the world. He has received a number of awards and mentions at Ars Electronica, Japan Media Art Festival, and Transmediale, among others. In October 2011, together with his colleagues Julian Oliver and Gordan Savičić, Vasiliev coauthored The Critical Engineering Manifesto.
Research: Education, Open Culture
Tags: data, data carving, hardware hacking