The use of electronic devices to perform privacy intrusion on citizens have been a huge problem. Countless people have encountered blackmailing with their unauthorized audio and video content from hidden electronic devices in hotel rooms.
Existing electronic device detection mechanisms are non-portable, costly, and difficult to operate. To solve the problem, we need the ability to recognize hidden electronic devices under different scenarios in a cost-efficient, user-friendly, and non-invasive manner.'
We propose and develop a novel form of hidden electronic recognition that guards the safety and privacy of civilians. Using a millimeter wave probe to interrogate the environment, we can accurately detect the presence of malicious hidden electronic devices based on their non-linear response. This allows scalable application of non-invasive hidden electronic detection to aid law enforcement and personal privacy.
Hidden electronics possess the risk of both security threat and privacy intrusion. We present a wireless hidden electronic recognition system, through electronic components unique mmWave nonlinear responses to identify the threats. We then evaluate E-Eye's performance and robustness with a controlled experiment and a field study using iconic devices and score the system with metrics. Results prove that E-Eye is an accurate and robust hidden electronic recognition system.
Click on the file below to see the full poster in your browser.
The University at Buffalo is committed to ensuring digital accessibility for people with disabilities. We are continually improving the user experience for everyone, and applying the relevant accessibility standards to ensure we provide equal access to all users. If you experience any difficulty in accessing the content or services on this website, or if you have suggestions about improving the user experience, please contact the Experiential Learning Network via email (firstname.lastname@example.org) or phone (716-645-8177).