|
1. Private Planning-&-Coordination Among Drones Equipped with Resource-Constrained Devices. One of the major challenges in any distributed computing system is the availability of proper computing devices. This issue might be resolved if the system is not a target of physical or cyber attacks and if it is supposed to be static. However, if the distributed setting is highly dynamic, it becomes extremely difficult to deploy heavy computing devices. This will be even more challenging if computations are expected to be performed in real-time and if the privacy of the input data are critical. In this project, we focus on design and fast implementation of privacy-preserving protocols on resource-constrained devices that are utilized in autonomous systems such as drones.
|
|
|
2. Human-Inspired Trust Controllers for Adaptive Autonomous Systems. Most of the recent studies indicate that people have negative attitudes to utilize autonomous systems. These interesting discoveries highlight the necessity and urgency of conducting research to better understand the evolution of trust between humans and growing autonomous technologies such as self-driving cars and care-giving robots. In this project, we explore how to establish, sustain and rebuild - in the case of incidental failures - trust between humans and autonomous systems. Furthermore, we utilize human-inspired trust modeling to understand human perception of (un)trustworthy actions in autonomous systems so that adversarial activities of intelligent adversaries can be detected as early as possible. IRBNET ID #: 1187756-1.
|
|
|
3. Impacts of Malicious Attacks on Perception of Trust, Satisfaction, and Frustration. Modern prosthetic limbs have the potential to greatly improve amputees' lives; however, these artificial limbs are susceptible to hackers. In this project, malicious attacks on a prosthetic arm system are simulated to adversely affect the operation of the prosthetic system while the perceptions of human subjects are measured. In other words, these metrics are negatively impacted by system malfunctions resembling a malicious attack on the control functionality. We are interested in ways to rebuild these human factors after they are affected by adversarial activities. IRBNET ID #: 1187761-1. This is a joint project with Dr. Erik Engeberg.
|
|
|
4. Trust, Satisfaction and Frustration Measurements in Human-Robot Teaming. In this project, we investigate the impacts of assistant-robot operation on human trust, satisfaction, and frustration through self-reported human metrics. We study how proper operations lead to human trust escalation, and consequently, satisfiable interactions with robotic systems. We also explore how the task performance of the human-robot team varies as human level of trust, satisfaction, and frustration fluctuate. We are mainly interested in care-giving robotic assistants that help veterans, disabled and elderly people in their daily life tasks. IRBNET ID #: 1187761-1. This is a joint project with Dr. Erik Engeberg.
|
|
|
5. Reputation-Based Cryptocurrency Mining Paradigm and Its Game-Theoretical Analysis. Verification of transactions in digital currencies is very resource intensive, therefore, miners form mining pools to verify each block of transactions in return for a reward where only the first mining pool that accomplishes the process will be rewarded. This leads to intense competitions among miners, and consequently, dishonest mining strategies, e.g., block withholding attack or selfish mining. As such, it is necessary to regulate the mining process to make the miners accountable for dishonest behaviors. We therefore design a new reputation-based mining paradigm in which the miners not only are incentivized to conduct honest mining but also disincentivized to commit any malicious activities against other mining pools.
|
|
|
6. Privacy-Preserving Market Mechanisms: From Sealed-Bid Auctions to Strategic Negotiations. The growth of e-technology and intense competition in markets and economic contexts have created a remarkable opportunity to remodel some of the existing market mechanisms and, as a result, define a new set of fascinating applications for cryptographic tools. As privacy and the resulting risk of economic fraud are major concerns in many markets, in this project, we transform a specific class of market mechanisms into a new privacy-preserving framework under the following two conditions: these protocols can be better utilized in the financial sectors if the privacy of certain parameters are preserved, and the elements and structures of these protocols are aligned with the characteristics of certain cryptographic tools.
|
|
|
7. Assessment of Attacks and Countermeasures in Post-Quantum Cryptography. In this project, we focus on comprehensive assessment of attacks and countermeasures in PQC algorithms. There has been a rise in side channel attacks against PQC schemes while the NIST standardization process is moving forward, i.e., round three was recently finished. As a result, there is a gap in the current literature on assessment of these attacks against final NIST candidates. We therefore aim to tackle this issue. More specifically, we assess the side channel attacks and countermeasures in Isogeny, Lattice, and Multivariate based post-quantum cryptography.
|
|
