Censorship is becoming increasingly pervasive on the Internet, with the Open Net Initiative reporting nearly 50 countries practicing some form of censorship. Previous work has reported the existence of many forms of Internet censorship (e.g., DNS tampering, packet filtering, connection reset, content filtering), each of which may be composed to build a more comprehensive censorship system. Automated monitoring of censorship represents an important and challenging research problem, due to the continually evolving nature of the content that is censored and the means by which censorship is implemented. UBICA, User-based Internet Censorship Analysis, is a platform we implemented to solve this task leveraging crowdsourced data collection. By adopting an integrated and multi-step analysis, UBICA provides simple but effective means of revealing censorship events over time. UBICA has revealed the effect of several censorship techniques including DNS tampering and content filtering. Using UBICA, we demonstrate evidence of censorship in several selected countries (Italy, Pakistan, and South Korea), for which we obtained help from local users and manually validated the automated analysis. This work has been carried out thanks to a Google Faculty Research Award for the project UBICA (User-Based Internet Censorship Analysis).
With technological advancement, implanted medical devices can treat a wide range of chronic diseases such as cardiac arrhythmia, deafness, diabetes, etc. Cardiac pacemakers are used to maintain normal heart rhythms. The next generation of these pacemakers is expected to be completely wireless, providing new security threats. Thus, it is critical to secure pacemaker transmissions between legitimate nodes from a third party or an eavesdropper. This work estimates the eavesdropping risk and explores the potential of securing transmissions between leadless capsules inside the heart and the subcutaneous implant under the skin against external eavesdroppers by using physical-layer security methods. In this work, we perform phantom experiments to replicate the dielectric properties of the human heart, blood, and fat for channel modeling between in-body-to-in-body devices and from in-body-to-off-body scenario. These scenarios reflect the channel between legitimate nodes and that between a legitimate node and an eavesdropper. In our case, a legitimate node is a leadless cardiac pacemaker implanted in the right ventricle of a human heart transmitting to a legitimate receiver, which is a subcutaneous implant beneath the collar bone under the skin. In addition, a third party outside the body is trying to eavesdrop the communication. The measurements are performed for ultrawide band (UWB) and industrial, scientific, and medical (ISM) frequency bands. By using these channel models, we analyzed the risk of using the concept of outage probability and determine the eavesdropping range in the case of using UWB and ISM frequency bands. Furthermore, the probability of positive secrecy capacity is also determined, along with outage probability of a secrecy rate, which are the fundamental parameters in depicting the physical-layer security methods. Here, we show that path loss follows a log-normal distribution. In addition, for the ISM frequency band, the probability of successful eavesdropping for a data rate of 600 kbps (Electromyogram (EMG)) is about 97.68% at an eavesdropper distance of 1.3 m and approaches 28.13% at an eavesdropper distance of 4.2 m, whereas for UWB frequency band the eavesdropping risk approaches 0.2847% at an eavesdropper distance of 0.22 m. Furthermore, the probability of positive secrecy capacity is about 44.88% at eavesdropper distance of 0.12 m and approaches approximately 97% at an eavesdropper distance of 0.4 m for ISM frequency band, whereas for UWB, the same statistics are 96.84% at 0.12 m and 100% at 0.4 m. Moreover, the outage probability of secrecy capacity is also determined by using a fixed secrecy rate.
Secure communication is considered as an integral part of next generation wireless implantable medical devices. In this work, we provide the symmetric cryptographic key generating approach by exploiting the randomness in received signal strength (RSS) for data encryption in an in-body network. The application of concern is the wireless modules for next generation leadless cardiac pacemaker with two units. For RSS based key generation method, both the units probe the wireless channel for RSS measurements within the coherence time and outputs the encryption key bits based on available randomness and quantization algorithm. To evaluate the available randomness in RSS measurements, the methodology of phantom experiments is adapted to emulate the cardiac cycle. It has been found that the measurements emulating the cardiac cycle can be approximated to follow the log-Normal distribution. Moreover, a high correlation of RSS measurements is observed across the pacemaker units to generate a symmetric key whereas the eavesdropper link is found to be highly de-correlated. Based on the available randomness, the quantization algorithm generates 2-bits per cardiac cycle and requires 64 cardiac cycles to generate a 128-bit binary key string with an average mismatch percentage of 1 % over 1000 key runs.
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