More Like this

1. Physical Unclonable Function (PUF)-Based e-Cash Transaction Protocol (PUF-Cash)

   https://doi.org/10.3390/cryptography3030018  

   Calhoun, Jeff ; Minwalla, Cyrus ; Helmich, Charles ; Saqib, Fareena ; Che, Wenjie ; Plusquellic, Jim ( September 2019 , Cryptography)

   null (Ed.)

   Electronic money (e-money or e-Cash) is the digital representation of physical banknotes augmented by added use cases of online and remote payments. This paper presents a novel, anonymous e-money transaction protocol, built based on physical unclonable functions (PUFs), titled PUF-Cash. PUF-Cash preserves user anonymity while enabling both offline and online transaction capability. The PUF’s privacy-preserving property is leveraged to create blinded tokens for transaction anonymity while its hardware-based challenge–response pair authentication scheme provides a secure solution that is impervious to typical protocol attacks. The scheme is inspired from Chaum’s Digicash work in the 1980s and subsequent improvements. Unlike Chaum’s scheme, which relies on Rivest, Shamir and Adlemans’s (RSA’s) multiplicative homomorphic property to provide anonymity, the anonymity scheme proposed in this paper leverages the random and unique statistical properties of synthesized integrated circuits. PUF-Cash is implemented and demonstrated using a set of Xilinx Zynq Field Programmable Gate Arrays (FPGAs). Experimental results suggest that the hardware footprint of the solution is small, and the transaction rate is suitable for large-scale applications. An in-depth security analysis suggests that the solution possesses excellent statistical qualities in the generated authentication and encryption keys, and it is robust against a variety of attack vectors including model-building, impersonation, and side-channel variants. 

   more » « less
2. Physical Unclonable Function (PUF)-based e-Cash Transaction Protocol (PUF-Cash)

   Jeff Calhoun, Cyrus Minwalla ( January 2019 , Cryptography)

   Electronic money (e‐money or e‐Cash) is the digital representation of physical banknotes augmented by added use cases of online and remote payments. This paper presents a novel, anonymous e‐money transaction protocol, built based on physical unclonable functions (PUFs), titled PUF‐Cash. PUF‐Cash preserves user anonymity while enabling both offline and online transaction capability. The PUF’s privacy‐preserving property is leveraged to create blinded tokens for transaction anonymity while its hardware‐based challenge–response pair authentication scheme provides a secure solution that is impervious to typical protocol attacks. The scheme is inspired from Chaum’s Digicash work in the 1980s and subsequent improvements. Unlike Chaum’s scheme, which relies on Rivest, Shamir and Adlemans’s (RSA’s) multiplicative homomorphic property to provide anonymity, the anonymity scheme proposed in this paper leverages the random and unique statistical properties of synthesized integrated circuits. PUF‐Cash is implemented and demonstrated using a set of Xilinx Zynq Field Programmable Gate Arrays (FPGAs). Experimental results suggest that the hardware footprint of the solution is small, and the transaction rate is suitable for large‐scale applications. An in‐depth security analysis suggests that the solution possesses excellent statistical qualities in the generated authentication and encryption keys, and it is robust against a variety of attack vectors including model‐building, impersonation, and side‐ channel variants. 

   more » « less
3. SolicitudeSavvy: An IoT-based Edge Intelligent Framework for Monitoring Anxiety in Real-time

   https://doi.org/10.1109/ISQED51717.2021.9424302  

   Sundaravadivel, Prabha ; Wilmoth, Parker ; Fitzgerald, Ashton ( April 2021 , 2021 22nd International Symposium on Quality Electronic Design (ISQED))

   null (Ed.)

   Anxiety disorders affect more than 18 percent of the population and is the most common mental illnesses in the US. There is a great demand to address this emerging epidemic with tools to differentiate and diagnose such disorders, and to create awareness especially in places like NorthEast Texas which is home to 1.5 million people with 58 percent of them living in rural areas. The goal of the proposed device is to diagnose as many anxiety disorders as possible, in real-time using the diagnosing wearable framework, SolicitudeSavvy, which uses technology such as the Internet of Things (IoT), a network of interconnected devices, to accomplish such a task. The proposed IoT-based device has two components: a custom-built wearable necklace that contains sensors to collect data about the user as they go about their day and a low-cost portable system that monitors Electrooculography (EoG) signals using a camera. The partial necklace attaches to the shirt and opens halfway around the wearer's neck and the EoG can be attached to any eyewear. The device monitors the user throughout the day, and even as they go to bed at night. This information is accumulated in the IoT cloud and analyzed to see exactly what type of disorder(s) the patient may suffer from. The authorized personnel i.e. doctor or therapist can use this pattern to find a treatment that best suits them and is most likely to resolve their affliction. 

   more » « less
4. Low-Burden Mobile Monitoring, Intervention, and Real-Time Analysis Using the Wear-IT Framework: Example and Usability Study

   https://doi.org/10.2196/16072  

   Brick, Timothy R ; Mundie, James ; Weaver, Jonathan ; Fraleigh, Robert ; Oravecz, Zita ( January 2020 , JMIR Formative Research)

   null (Ed.)

   Background Mobile health (mHealth) methods often rely on active input from participants, for example, in the form of self-report questionnaires delivered via web or smartphone, to measure health and behavioral indicators and deliver interventions in everyday life settings. For short-term studies or interventions, these techniques are deployed intensively, causing nontrivial participant burden. For cases where the goal is long-term maintenance, limited infrastructure exists to balance information needs with participant constraints. Yet, the increasing precision of passive sensors such as wearable physiology monitors, smartphone-based location history, and internet-of-things devices, in combination with statistical feature selection and adaptive interventions, have begun to make such things possible. Objective In this paper, we introduced Wear-IT, a smartphone app and cloud framework intended to begin addressing current limitations by allowing researchers to leverage commodity electronics and real-time decision making to optimize the amount of useful data collected while minimizing participant burden. Methods The Wear-IT framework uses real-time decision making to find more optimal tradeoffs between the utility of data collected and the burden placed on participants. Wear-IT integrates a variety of consumer-grade sensors and provides adaptive, personalized, and low-burden monitoring and intervention. Proof of concept examples are illustrated using artificial data. The results of qualitative interviews with users are provided. Results Participants provided positive feedback about the ease of use of studies conducted using the Wear-IT framework. Users expressed positivity about their overall experience with the framework and its utility for balancing burden and excitement about future studies that real-time processing will enable. Conclusions The Wear-IT framework uses a combination of passive monitoring, real-time processing, and adaptive assessment and intervention to provide a balance between high-quality data collection and low participant burden. The framework presents an opportunity to deploy adaptive assessment and intervention designs that use real-time processing and provides a platform to study and overcome the challenges of long-term mHealth intervention. 

   more » « less
5. Networkless Wireless Sensing for Bridge Structural Health Monitor

   Afonso, B. ; Liu, H. ; Yu, Z. ( September 2022 , IEEE/MIT Undergraduate Research Technology Conference (URTC))

   The recent report by American Society of Civil Engineers gave the nation's bridges an unimpressive C grade. Across the country, more than 617,000 highway bridges: 46,154 structurally deficient and 42% 50+ years old. Continuous bridge assessment is essential to protect public safety. Federal Highway Administration requires all highway bridges inspected once every 24 months. However, any drastic change on bridges within 24 months will be left undetected. Nonetheless, bridge inspection is time-consuming and labor-intensive. Civil engineers have been using bridge health monitoring (BHM) systems with wired and/or wireless sensors to measure structural response (e.g., displacement, strain, acceleration) of a bridge. The response measurements are then converted to the information related to structural health for assessment. State-of-the-art BHM technology deploys sensor networks to facilitate data connection. Installing cables is expensive and subject to extreme weather. Wireless solutions face challenges such as energy consumption. Sensors are battery-powered. Another not well-publicized problem is security threats inherited in wireless networks. Our approach to wireless BHM is to utilize sensors networkless by collecting data with a drone. Similar to a mail carrier who goes around and picks up the mail, a drone collects data from sensors throughout the bridge. A drone eliminates restrictions for civil engineers on node placement since the drone replaces sink nodes. Networkless makes BHM less prone to attacks such as Jamming and DoS. To secure access, we deploy a Needham-Schroeder authentication protocol for the drone to collect data from sensor nodes securely. Networkless sensing for BHM benefits energy efficiency. It saves battery life as the sensor nodes remain asleep until scheduled transmission or woken up by a drone. It reduces design complexity and operation energy. The system also assures security since there is no vulnerable network to be attacked. 

   more » « less