This paper proposes a new clock offset estimation that mitigates unwanted link asymmetry for precise clock synchronization. The main contribution is to address the primary and traditional design issue of the IEEE 1588 standard precision time protocol (PTP), which estimates clock offset under the assumption that the delays of exchanged packets are symmetric. To mitigate the issue, we focus on the fact that PTP measures asymmetry variation through the derivatives of its timestamps with respect to the time step. By exploiting the measurement of the variation, the proposed approach defines the asymmetry in the form of a linear differential equation (LDE) and leverages the LDE to define and exclude asymmetry-induced errors. Additionally, we clearly derive the state transition of the asymmetry. Subsequently, we derive a novel state-space model from our approach. The model describes PTP clock offset estimation perfectly, allowing optimal clock offset estimation. We verify the theoretical validity of the proposed method with real data. Our approach improves PTP accuracy by more than thousand times and achieves an accuracy at the level of tens to hundreds of nanoseconds on an asymmetric communication link. Our approach realizes an accuracy comparable to that of PTPv2, without the cost of specialized hardware.

Every year, the U.S. economy loses more than $411 billion because of work performance reduction, injuries, and traffic accidents caused by microsleep. To mitigate microsleeps consequences, an unobtrusive, reliable, and socially acceptable microsleep detection solution throughout the day, every day is required. Unfortunately, existing solutions do not meet these requirements. In this paper, we propose WAKE, a novel behind-the-ear wearable device for microsleep detection. By monitoring biosignals from the brain, eye movements, facial muscle contractions, and sweat gland activities from behind the user's ears, WAKE can detect microsleep with a high temporal resolution. We introduce a Three-fold Cascaded Amplifying (3CA) technique to tame the motion artifacts and environmental noises for capturing high fidelity signals. Through our prototyping, we show that WAKE can suppress motion and environmental noise in real-time by 9.74-19.47 dB while walking, driving, or staying in different environments ensuring that the biosignals are captured reliably. We evaluated WAKE using gold-standard devices on 19 sleep-deprived and narcoleptic subjects. The Leave-One-Subject-Out Cross-Validation results show the feasibility of WAKE in microsleep detection on an unseen subject with average precision and recall of 76% and 85%, respectively.

Although the IEEE Wireless Access in Vehicular Environment (WAVE) and 3GPP Cellular V2X deployments are imminent, their standards do not yet cover an important security aspect; the message content plausibility check. In safety-critical driving situations, vehicles cannot blindly trust the content of received safety messages, because an attacker may have forged false values in it in order to cause unsafe response from the receiving vehicles. In particular, the attacks mounted from remote, well-hidden positions around roads are considered the most apparent danger. So far, there have been three approaches to validating V2X message content: checking based on sensor fusion, behavior analysis, and communication constraints. This paper discusses the three existing approaches. In addition, it discusses a communication-based checking scheme that supplements the existing approaches. It uses low-power transmission of vehicle identifiers to identify remote attackers. We demonstrate its potential address in the case of an autonomous vehicle platooning application.