We trained several postdocs and students who we hope will take faculty positions at US universities. We have taught them all the tasks they need to execute as faculty by working closely with them on papers, presentations, and instruction on how to teach and write proposals.
The research results have been incorporated into classes at Lehigh University, in summer school classes (IEEE, NSF, others), an IEEE distinguish lecture series (over 10 talks each year all over the world), and in lectures to engineers (local IEEE chapters) and the general public (Lehigh alumni and other interested parties). The research has been published in the best journals, conferences, and IEEE Signal Processing magazine (a top place to publish tutorial papers). Special sessions on the topics studied have been organized at top conferences every year the project has been running. These special sessions gather the top researchers to review the progress we have made and the progress they have made. These special sessions also highlight the work of our students and postdocs to help them obtain faculty positions.
The PIs (Blum and Poor) have both given plenary talks at major conferences, workshops, tutorials, and summer schools on our research. Prof. Blum gave talks each year on the cyber security work done under this project as an IEEE Signal Processing Society Distinguished Lecturer. We (our whole team) have organized outstanding special sessions at the Conference on Information Sciences and Systems (CISS) for each year the project has been running. Some years we organized several sessions.
In 2018, CISS was held in Princeton and our postdoc Yanina Shkel organized an invited session titled `”Theory and Bounds for IoT Security”. The session had talks from top researchers in information theoretic security on topics like physical layer security (e.g. the wiretap channel), secure short packet communication, network secrecy, privacy for large data sets, and many more. The speakers were: Aylin Yener (Penn State) Matthieu Block (Georgia Tech) Aaron Wagner (Cornell University) Sennur Ulukus (University of Maryland) Lalitha Sankar (Arizona State University) Oliver Kosut (Arizona State University) and Yanina Shkel (Princeton).
Our collaborator from Finland, Visa Koivunen, also organized a session on inference processing for IoT at CISS 2018 that included our entire team. For example, our paper at this CISS session was by Ananth Narayan Samudrala, Rick S. Blum, H, V. Poor, and Visa Koivunen, and was titled “On the Estimation and Secrecy Capabilities of Stochastic Encryption for Parameter Estimation in IoT”. The other papers in the session included:
Arpan Chattopadhyay and Urbashi Mitra (USC) “Dynamic Sensor Selection for Time-Varying Stochastic Process Tracking”
Natalia Vesselinova, Visa Koivunen, H. Vincent Poor (Our team), ” Large-Scale Nonparametric Distributed Inference using Bootstrap and FDR ”
Zhixiong Yang and Waheed U. Bajwa (Rutgers), “Distributed machine learning in the age of cyber attacks”
J. Heydari, S. Sihag, and A. Tajer (RPI), ”Quickest Search for Transient Changepoints under Composite Post-change Models”
In 2019, CISS was held at Johns Hopkins University. Prof. Blum organized a session at CISS 2019 with the following papers (including many from our team along with other outstanding researchers):
CISS Invited Session: Security and Inference for Internet of Things Networks
1. Lecture * INVITED *
Parameter Estimation and Secrecy by Design Yanina Shkel, Vincent Poor, Rick Blum
2. Lecture * INVITED Secure Key Generation for Distributed Inference in IoT Henri Hentilä, Visa Koivunen, Vincent Poor, Rick Blum
3. Lecture * INVITED * Cryptographic Side-Channel Signaling and Authentication via Fingerprint Embedding: Security Analysis, Jake Perazzone, Paul Yu, Brian Sadler, Rick Blum
4. Lecture * INVITED * Optimal Sensor Placement for Topology Identification of Smart Power Grids Ananth Narayan Samudrala, Hadi Amini M, Soummya Kar, Rick Blum
5. Lecture * INVITED * Topology Attack Detection in Natural Gas Delivery Networks
Zisheng Wang, Rick Blum
In 2020, our collaborator Visa Koivunen organized another excellent session on Distributed Inference and Learning with the following papers:
Distributed Learning for Remote Estimation
Authors: Xu Zhang, Marcos Vasconcelos, Wei Cui and Urbashi Mitra
An Empirical Bayes Approach to Robust Mean Estimation with Application to Federated Learning
Authors: Jing Liu, Aditya Deshmukh, and Venugopal V. Veeravalli
Deterministic Multiple Change-Point Detection with Limited Communication
Authors: Eyal Nitzan, Topi Halme, H. Vincent Poor and Visa Koivunen
Cybersecurity of Inference in Vehicle Networks
Authors: Zisheng Wang and Rick S. Blum
Sequential Estimation of Network Cascades
Authors: Anirudh Sridhar and H. Vincent Poor
Distributed Joint Detection and Estimation: A Sequential Approach.
Authors: Dominik Reinhard, Michael Fauß and Abdelhak M Zoubir