Abstract-Authentication is the process where claims of identity are verified. Most mechanisms of authentication (e.g., digital signatures and certificates) exist above the physical layer, though some (e.g., spread-spectrum communications) exist at the physical layer often with an additional cost in bandwidth. This paper introduces a general analysis and design framework for authentication at the physical layer where the authentication information is transmitted concurrently with the data. By superimposing a carefully designed secret modulation on the waveforms, authentication is added to the signal without requiring additional bandwidth, as do spread-spectrum methods. The authentication is designed to be stealthy to the uninformed user, robust to interference, and secure for identity verification. The tradeoffs between these three goals are identified and analyzed in block fading channels. The use of the authentication for channel estimation is also considered, and an improved bit-error rate is demonstrated for time-varying channels. Finally, simulation results are given that demonstrate the potential application of this authentication technique.
We consider the combined problem of frontier exploration in a complex indoor environment while seeking a radio source. To do this in an efficient manner, we incorporate radio signal strength (RSS) information into the exploration algorithm by locally sampling the RSS and estimating the 2-D RSS gradient. The algorithm exploits the local motion to collect RSS samples for gradient estimation and seeks to explore in a way that brings the robot to the signal source. This strategy avoids random or exhaustive exploration. An indoor experiment demonstrates the exploration algorithm that uses this information to dynamically prioritize candidate frontiers and traverse to a radio source. Simulations, including radio propagation modeling with a ray-tracing algorithm, enable study of control algorithm tradeoffs and statistical performance.
Operating systems use shared memory to improve performance. However, as shown in recent studies, attackers can exploit CPU cache side-channels associated with shared memory to extract sensitive information. The attacks that were previously attempted typically only detect the presence of a certain operation and require significant manual analysis to identify and evaluate their effectiveness. Moreover, very few of them target graphics libraries which are commonly used, but difficult to attack. In this paper, we consider the execution time of shared libraries as the side-channel, and showcase a completely automated technique to discover and select exploitable side-channels on shared graphics libraries. In essence, we first collect the cache lines accessed by a victim process during different key presses offline, and then use machine learning to infer the best cache lines (e.g., easily measurable, robust to noise, high information leakage) for a flush and reload attack. We are able to discover effective strategies to classify what keys have been pressed. Using this approach, we not only preclude the need for manual analyses of code and tracesthe automated system discovered many previously unknown sidechannels of the type we are interested in, but also achieve high precision in terms of inferring the sensitive information entered on desktop and Android platforms. We show that our approach infers the passwords with lowercase letters and numbers 10,000-1,000,000 times faster than random guessing. For a large fraction of PINs consisting of 4 to 6 digits, we are able to infer them within 20 and 80 guesses respectively. Finally, we suggest ways to mitigate these attacks.
The use of fingerprint embedding at the physical layer enables a receiver to authenticate a transmitter by detecting a low-power authentication tag superimposed upon the message waveform; a theoretical framework for such fingerprinting has been outlined. We carry out single-carrier single-antenna software defined radio (SDR) experiments with a wireless communications link over which we transmit and receive packets with the embedded fingerprinting. We analyze these experimental results and find they match well with theoretical predictions. This paper demonstrates that the method of superimposed fingerprints can deliver high probability of authentication without additional bandwidth and with minimal impact on bit-error rate in SDR systems.
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