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1. Deep Learning Dataset Generation for Physical Layer Authentication in Wireless Sensor Networks (WSN)

   Dentremont, Christopher; Liu, Hong (May 2024, 2024 International Wireless Communications and Mobile Computing (IWCMC))

   Structural Health Monitoring (SHM) uses wireless sensor network (WSN) to monitor a civil construction’s conditions remotely and constantly for its sustainable usage. Security in WSN for SHM is essential to safeguard critical transportation infrastructure such as bridges. While WSN offers cost-effective solutions for Bridge SHM, its wireless nature expands attack surfaces, making security a significant concern. Despite progress in addressing security issues in WSN for Bridge SHM, challenges persist in device authentication due to the unique placement of sensor nodes and their resource constraints, particularly in energy conservation requirements to extend the system’s lifetime. To overcome these limitations, this paper proposes an innovative authentication scheme with deep learning at the physical layer. Our approach steers away from conventional device authentication methods: no challenge-response protocol with heavy communication overhead and no cryptography of intensive computation. Instead, we use radio frequency (RF) fingerprinting to authenticate sensor nodes. Deep learning is chosen for its ability to discover patterns in large datasets without manual feature engineering. We model our scheme on IEEE 802.11ah, Wi-Fi HaLow of long-range communication and low-power consumption for machine-to-machine (M2M) applications. Simulations and experiments using universal software radio peripheral (USRP) demonstrate the effectiveness of the proposed scheme. By integrating security into Cyber-Physical System/the Internet-of-Things (CPS/IoT) design of WSN for Bridge SHM, our work contributes to critical infrastructure protection. 

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2. On the Accuracy of Network Synchronization Using Persistent Hourglass Clocks

   https://doi.org/10.1145/3362053.3363497  

   Çürük, Eren; Yıldırım, Kasim Sinan; Pawelczak, Przemyslaw; Hester, Josiah (January 2019, Proceedings of the 7th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems)

   Batteryless sensor nodes compute, sense, and communicate using only energy harvested from the ambient. These devices promise long maintenance free operation in hard to deploy scenarios, making them an attractive alternative to battery-powered wireless sensor networks. However, complications from frequent power failures due to unpredictable ambient energy stand in the way of robust network operation. Unlike continuously-powered systems, intermittently-powered batteryless nodes lose their time upon each reboot, along with all volatile memory, making synchronization and coordination difficult. In this paper, we consider the case where each batteryless sensor is equipped with a hourglass capacitor to estimate the elapsed time between power failures. Contrary to prior work that focused on providing a continuous notion of time for a single batteryless sensor, we consider a network of batteryless sensors and explore how to provide a network-wide, continuous, and synchronous notion of time. First, we build a mathematical model that represents the estimated time between power failures by using hourglass capacitors. This allowed us to simulate the local (and continuous) time of a single batteryless node. Second, we show--through simulations--the effect of hourglass capacitors and in turn the performance degradation of the state of the art synchronization protocol in wireless sensor networks in a network of batteryless devices. 

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3. Secure Data Aggregation in Wireless Sensor Networks: Enumeration Attack and Countermeasure

   https://doi.org/10.1109/ICC.2019.8761889  

   Aseeri, Aishah; Zhang, Rui (May 2019, ICC 2019 - 2019 IEEE International Conference on Communications (ICC))

   Data aggregation is a key primitive in wireless sensor networks and refers to the process in which the sensed data are processed and aggregated en-route by intermediate sensor nodes. Since sensor nodes are commonly resource constrained, they may be compromised by attackers and instructed to launch various attacks. Despite the rich literature on secure data aggregation, most of the prior work focuses on detecting intermediate nodes from modifying partial aggregation results with two security challenges remaining. First, a compromised sensor node can report arbitrary reading of its own, which is fundamentally difficult to detect but widely considered to have limited impact on the final aggregation result. Second, a compromised sensor node can repeatedly attack the aggregation process to prevent the base station from receiving correct aggregation results, leading to a special form of Denial-of-Service attack. VMAT [1] (published in ICDCS 2011) is a representative secure data aggregation scheme with the capability of pinpointing and revoking compromised sensor nodes, which relies on a secure MIN aggregation scheme and converts other additive aggregation functions such as SUM and COUNT to MIN aggregations. In this paper, we introduce a novel enumeration attack against VMAT to highlight the security vulnerability of a sensor node reporting an arbitrary reading of its own. The enumeration attack allows a single compromised sensor node to significantly inflate the final aggregation result without being detected. As a countermeasure, we also introduce an effective defense against the enumeration attack. Theoretical analysis and simulation studies confirm the severe impact of the enumeration attack and the effectiveness of the countermeasure. 

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4. Greentooth: Robust and Energy Efficient Wireless Networking for Batteryless Devices

   https://doi.org/10.1145/3649221  

   Babatunde, Simeon; Alsubhi, Arwa; Hester, Josiah; Sorber, Jacob (May 2024, ACM Transactions on Sensor Networks)

   Communication presents a critical challenge for emerging intermittently powered batteryless sensors. Batteryless devices that operate entirely on harvested energy often experience frequent, unpredictable power outages and have trouble keeping time accurately. Consequently, effective communication using today’s low-power wireless network standards and protocols becomes difficult, particularly because existing standards are usually designed to support reliably powered devices with predictable node availability and accurate timekeeping capabilities for connection and congestion management. In this article, we present Greentooth, a robust and energy-efficient wireless communication protocol for intermittently powered sensor networks. It enables reliable communication between a receiver and multiple batteryless sensors using Time Division Multiple Access–style scheduling and low-power wake-up radios for synchronization. Greentooth employs lightweight and energy-efficient connections that are resilient to transient power outages, while significantly improving network reliability, throughput, and energy efficiency of both the battery-free sensor nodes and the receiver—which could be untethered and energy constrained. We evaluate Greentooth using a custom-built batteryless sensor prototype on synthetic and real-world energy traces recorded from different locations in a garden across different times of the day. Results show that Greentooth achieves 73% and 283% more throughput compared to Asynchronous Wake-up on Demand MAC and Receiver-Initiated Consecutive Packet Transmission Wake-up Radios, respectively, under intermittent ambient solar energy and over 2× longer receiver lifetime. 

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5. A Billion Open Interfaces for Eve and Mallory: MitM, DoS, and Tracking Attacks on iOS and macOS Through Apple Wireless Direct Link

   Mariotto, Alex; Heinrich, Alexander; Kreitschmann, David; Noubir, Guevara; Hollick, Matthias (January 2019, Proceedings of the 28th USENIX Security Symposium)

   Apple Wireless Direct Link (AWDL) is a key protocol in Apple’s ecosystem used by over one billion iOS and macOS devices for device-to-device communications. AWDL is a proprietary extension of the IEEE 802.11 (Wi-Fi) standard and integrates with Bluetooth Low Energy (BLE) for providing services such as Apple AirDrop. We conduct the first security and privacy analysis of AWDL and its integration with BLE. We uncover several security and privacy vulnerabilities ranging from design flaws to implementation bugs leading to a man-in-the-middle (MitM) attack enabling stealthy modification of files transmitted via AirDrop, denial-of-service (DoS) attacks preventing communication, privacy leaks that enable user identification and long-term tracking undermining MAC address randomization, and DoS attacks enabling targeted or simultaneous crashing of all neighboring devices. The flaws span across AirDrop’s BLE discovery mechanism, AWDL synchronization, UI design, and Wi-Fi driver implementation. Our analysis is based on a combination of reverse engineering of protocols and code supported by analyzing patents. We provide proof-of-concept implementations and demonstrate that the attacks can be mounted using a low-cost ($20) micro:bit device and an off-the-shelf Wi-Fi card. We propose practical and effective countermeasures. While Apple was able to issue a fix for a DoS attack vulnerability after our responsible disclosure, the other security and privacy vulnerabilities require the redesign of some of their services. 

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