Accepted Research Papers

1. "Differential Privacy for Protecting Private Patterns in Data Streams"
   He Gu (University of Oslo), Thomas Plagemann (University of Oslo), Maik Benndorf (University of Oslo), Vera Goebel (University of Oslo), Boris Koldehofe (University of Groningen)
2. "Preserving Privacy in Image Database through Bit-planes Obfuscation"
   Vishesh Kumar Tanwar (Missouri University of Science and Technology), Ashish Gupta (Missouri University of Science and Technology, Rolla), Sanjay Kumar Madria (Missouri University of Science & Technology), Sajal K. Das (Missouri University of Science and Technology)
3. "Locally Private Streaming Data Release with Shuffling and Subsampling"
   Xiaoyu Li (Kyoto University), Yang Cao (Hokkaido University), Masatoshi Yoshikawa (Kyoto University)
4. "Toward Compliance Implications and Security Objectives: A Qualitative Study"
   Dmitry Prokhorenkov (Technical University of Munich)

Accepted Undergrad/K-12 Competition Papers

1. "How to Use Blockchain for IoT Data Preservation"
   
   Rick Lin (Morrison Academy), Verna Fu (Taipei European School)
2. "The Private Key Sharing of Blockchain and Its Applications for Digital Assets"
   
   Elisha Tseng (Wagor International School), Kate Tseng (Wagor International School)
3. "PuPrChain: A Public-Private Cluster-Based Distributed Blockchain System"
   
   Lalithsai Posam (Evergreen Valley High School), Faisal Nawab (University of California, Irvine)
4. "Robust Occupancy Computation Based on WiFi Connectivity Events"
   
   Rithwik Kerur (University of California, Irvine), Yiming Lin (University of California, Irvine)
5. "Live Space Modeling and Location Tracking For Emergency Evacuations: Application of TIPPERS Builder"
   
   Ishan Varshney (University of California, Irvine), Nada Lahjouji (University of California, Irvine), Modeste Kenne (University of California, Irvine)
6. "Application of BadNets in Spam Filters"
   
   Swagnik Roychoudhury (New York University), Akshaj Kumar Veldanda (New York University)
7. "SMILE: Smartphone Based Isolation Analysis for Older Adults"
   
   Raghav S Mehrotra-Venkat (University High School), Siddhanth Kumar (Northwood High School), Subhash Prasad (Irvine High School), Rithwik Kerur (University of California, Irvine)
8. "S3ORAM: A Demonstration with a Real Dataset"
   
   Salvatore G Spena (New Jersey Institute of Technology)

Invited Talks:

Explainable Learning from Time-Series Data

Jyotirmoy V. Deshmukh (University of Southern California)

Abstract

With advances in machine learning (ML) for time-series data, IoT designers now have several tools at hand to classify and cluster data, identify anomalies, and forecast physical quantities in their system. However, a key drawback of ML is that typical algorithms, especially those relying on deep and recurrent neural networks, are not generally interpretable. To address this issue, we propose the use of a set of techniques that use temporal logic to solve some of the above problems. We also introduce a new language called shape expressions that allow us to express interesting patterns in signals and discuss algorithms to monitor shape expressions in real-time and learn these expressions from data. We show the efficacy of our techniques on real-world data gathered from IoT systems in the autonomy and healthcare domains.

About the Speaker

Jyotirmoy (Jyo) Deshmukh is an associate professor in the Department of Computer Science at the Viterbi School of Engineering, University of Southern California. Before joining USC, Jyo worked as a principal research engineer at Toyota R&D. He was a Computing Innovation postdoctoral fellow at the University of Pennsylvania. He received his Ph.D. from the University of Texas at Austin. Jyo is the recipient of the 2021 NSF CAREER award and the 2021 Amazon Faculty Research Award.

The Path Towards a Blockchain Substrate for IoT Applications

Faisal Nawab (University of California, Irvine)

Abstract

The computing paradigms that support data-intensive edge and IoT applications have been radically transformed many times in the past few decades. In this talk, we will take a closer look at these transformations to have a better understanding of the patterns that drive them. With this understanding, we project how computing evolves to shape the new transformation in computing. We will observe how cloud computing is evolving to be more distributed and decentralized beyond traditional data centers and how many emerging technologies -- such as blockchain and serverless -- are precursors to this new computing paradigm. Getting ready for this transformation in computing requires reevaluating and redesigning current data management principles. I will talk about some of our work at UCI EdgeLab to achieve this goal. This includes our work on AnyLog to build a distributed and decentralized data infrastructure for the Global-Scale Edge.

About the Speaker

Faisal Nawab is an assistant professor in the computer science department at the University of California, Irvine. He is the founder and director of EdgeLab, which is dedicated to building Big Data and distributed systems for blockchain and Internet of Things (IoT) applications. His research focuses on developing data infrastructure for edge and IoT applications through various distributed data management projects, working closely with industry leaders such as Meta (formerly known as Facebook) and Roblox, as well as startups such as AnyLog. Prof. Nawab has received recognition for his work, winning the prestigious "Next-Generation Data Infrastructure" award from Facebook and being named the runner-up for the IEEE TEMS Blockchain Early-Career Award. He has also published his research in top-tier conferences and journals in his field.

Topics of Interest

Topics of interest include, but are not limited to:

* Secure hardware for IoT data management
* Model-based security systems engineering
* Understanding dependencies among security, reliability,and safety in CPS/IoT
* High-assurance security architectures
* Intrusion and anomaly detection
* Secure and privacy-preserving sensor data outsourcing
* Privacy-by-design of IoT data management systems
* Differentially private computing
* Privacy-preserving machine learning and federated learning and analytics
* Privacy regulations (GDPR, CCPA, CalOPPA) and their impact on IoT systems
* Privacy-Preserving Data Analysis in IoT Systems
* Inference control and access control policies
* Authentication
* Blockchain-based systems
* Identity and access management
* Security, privacy, and utility metrics
* Application/use-cases in healthcare, environment, transportation, energy, etc.

Submission Guidelines