Many clock synchronization protocols based on message passing, e.g., the Network Time Protocol (NTP), assume symmetric network delays to estimate the one-way packet transmission time as half of the round-trip time. As a result, asymmetric network delays caused by either network congestion or malicious packet delays can cause significant synchronization errors. This article exploits sinusoidal voltage signals of an alternating current (AC) power grid to limit the impact of the asymmetric network delays on these clock synchronization protocols. Our extensive measurements show that the voltage signals at geographically distributed locations in a city are highly synchronized. Leveraging calibrated voltage phases, we develop a new clock synchronization protocol that we call Grid Time Protocol (GTP), which allows direct measurement of one-way packet transmission times between its slave and master nodes, subject to an analytic condition that can be easily verified in practice. The direct measurements render GTP resilient against asymmetric network delays under this condition. A prototype implementation of GTP maintains sub-millisecond synchronization accuracy for two nodes tens of kilometers apart in the presence of malicious packet delays. The result has been demonstrated for both Singapore and Hangzhou, China. Simulations driven by real network delay measurements between Singapore and Hangzhou under both normal and congested network conditions also show the synchronization accuracy improvement by GTP. We believe that GTP is suitable for grid-connected distributed systems that are currently served by NTP but desire higher resilience against unfavorable network dynamics and packet delay attacks.

Desynchronized clocks among network nodes in critical infrastructures can degrade system performance and even lead to safety incidents. Clock synchronization protocols based on network message exchanges, though widely used in current network systems, are susceptible to delay attacks against the packet transmission. This vulnerability cannot be solved by conventional security measures, such as encryption, and remains an open problem. This article proposes to use the sine voltage waveform of a utility power grid to synchronize network nodes connected to the same grid. Our experiments demonstrate that minute fluctuations of the voltage’s cycle length encode fine-grained global time information in Singapore’s utility grid. Based on this key result, we develop a clock synchronization approach that achieves good accuracy and is provably secure against packet-delay attacks. Implementation results show that our approach achieves an average synchronization error of 0.1 ms between two network nodes that are deployed in office and residential buildings 10 km apart. When the proposed system is deployed within the same floor of an office building, the error reduces to 10 μs. When there are heavy industrial loads close to one of the two nodes 10 km apart, the system can still maintain subsecond accuracy. Moreover, when the two nodes are deployed within the same building floor with industrial loads nearby, the average synchronization error is 34 μ

Many clock synchronization protocols based on message passing, e.g., the Network Time Protocol (NTP), assume symmetric network delays to estimate the one-way packet transmission time as half of the round-trip time. As a result, asymmetric network delays caused by either %natural one-way network congestion or malicious packet delays can cause significant synchronization errors. This paper exploits sinusoidal voltage signals of an alternating current (ac) power grid to tame the asymmetric network delays for robust and resilient clock synchronization. Our extensive measurements show that the voltage signals at geographically distributed locations in a city are highly synchronized. Leveraging calibrated voltage phases, we develop a new clock synchronization protocol, which we call Grid Time Protocol (GTP), that allows direct measurement of one-way packet transmission times between its slave and master nodes, under an analytic condition that can be easily verified in practice. The direct measurements render GTP resilient against asymmetric network delays under this condition. A prototype implementation of GTP, based on readily available ac/ac transformers and PC-grade sound cards as voltage signal sampling devices, maintains sub-ms synchronization accuracy for two nodes 30 km apart, in the presence of malicious packet delays. We believe that GTP is suitable for grid-connected distributed systems that are currently served by NTP but desire higher resilience against network dynamics and packet delay attacks.

The continuous fluctuation of electric network frequency (ENF) presents a fingerprint indicative of time, which we call natural timestamp. This live demo demonstrates the accuracy of the natural timestamps obtained by four wired voltage sensors and four wireless electromagnetic radiation (EMR) sensors that are geographically distributed in Singapore. The voltage sensors and the EMR sensors capture the minute fluctuations of the length of each voltage cycle and the average ENF over every 50 voltage cycles, respectively. The evaluation in our prior studies [1, 3] has shown that the natural timestamps recorded by the voltage sensors and the EMR sensors give sub-millisecond and sub-second average time errors, respectively. This demo will also show their time errors.

Energy is required for networking and computation and is a valuable resource for unplugged embedded systems. Energy DoS attack where a remote attacker exhausts the victim's battery by sending networking requests remains a critical challenge for the device availability. While prior literature proposes mitigation- and detection-based solutions, we propose to eliminate the vulnerability entirely by offloading the power requirements to the entity who makes the networking requests. To do so, we build communication channels using wireless charging signals, so that the communication and the power transfer are simultaneous and inseparable, and use the channels to build power-positive networking (PPN). PPN also offloads the computation-based costs to the requester, enabling authentication and other tasks considered too power-hungry for battery-operated devices. Furthermore, because we use the charging signal for bidirectional networking, the design requires no additional hardware beyond that for wireless charging. In this paper, we present PPN, implement a Qi-compatible prototype, and use the prototype to analyze the performance.

Desynchronized clocks among nodes in industrial Internet of Things (IoT) can degrade system performance and even lead to safety incidents. Clock synchronization protocols based on network message exchanges, though widely used in current industrial systems, are susceptible to delay attacks against the packet transmission. This vulnerability cannot be solved by conventional security measures such as encryption, and remains an open problem. This paper proposes to use the sine voltage waveform of a utility power grid to synchronize "things" connected to the same grid. Our experiments demonstrate that minute fluctuations of the voltage's cycle length encode fine-grained global time information in a city-scale utility grid. Based on this key result, we develop a clock synchronization approach that achieves sub-ms accuracy and is provably secure against packet delay attacks. Implementation results show that our approach achieves an average synchronization error of 0.1 ms between two IoT nodes that are 10 km apart. When the proposed system is deployed within the same floor of a building, the error reduces to 10 us.

In this demonstration, we present a working prototype that uses an Anisotropic Magnetoresistive (AMR) sensor array to estimate the electricity usage on individual branches of an electricity panel. Our design enables the general public to retrofit an electricity panel: one simply needs to attach a compact AMR sensor array onto the panel. Our system can then exploit the inherent power patterns of electric loads to automatically infer the system parameters and estimate the per-branch currents accurately. Even for branches carrying small loads (e.g., a 30W fan), the estimation error of our system is below 10%.