Events

ECE Master of Science Thesis Defense by: Daniel S. Garcia

Topic: A Study of Post Quantum Cipher Suites for Key Exchange ZOOM Teleconference: https://umassd.zoom.us/j/94024358507 Meeting ID: 940 2435 8507 Passcode: 430046 Abstract: Current cryptographic solutions used in information technologies today like Transport Layer Security (TLS) utilize algorithms with underlying computationally difficult problems to solve. With the ongoing research and development of quantum computers, these same computationally difficult problems become solvable within reasonable (polynomial) time. The emergence of large-scale quantum computers would put the integrity and confidentiality of today's data in jeopardy. It then becomes urgent to develop, implement, and test a new suite of cybersecurity measures against attacks from a quantum computer. This thesis explores, understands, and evaluates this new category of cryptosystems as well as the many tradeoffs among them. All the algorithms submitted to NIST for standardization can be categorized into three major categories, each relating to the new underlying hard problem: namely error code correcting, algebraic lattices (including ring learning with errors), and supersingular isogenies. These new mathematical hard problems have shown to be resistant to the same type of quantum attack. Utilizing hardware clock cycle registers such as RDTSC on x86 architecture and CCNT on ARM architectures, the work sets up the benchmarks of the four Round 3 NIST algorithms in two environments: cloud computing and embedded system. In addition, security levels of each algorithm is analyzed with varying key sizes to highlight tradeoffs. Results show a significant decrease in performance on embedded systems, revealing the aspects of each algorithm such as key pair generation that should be reduced due to performance. As expected, there are many tradeoffs and advantages for certain applications in each algorithm. Saber and Kyber are exceedingly fast but have larger ciphertext size for transmission over a wire. McEliece key size and key generation are the largest drawbacks but having the smallest ciphertext size and only slightly decreased performance allow a use case where key reuse is prioritized. NTRU finds a middle ground in these tradeoffs, being better than McEliece performance wise and better than Kyber and Saber in ciphertext size allows for a use case of highly varied environments, which need to value speed and ciphertext size equally. Going forward, the benchmarking system developed could be applied to digital signature, another vital aspect to a cryptosystem. NOTE: All ECE Graduate Students are ENCOURAGED to join the zoom teleconference. All interested parties are invited to join. Advisor: Dr. Hong Liu Committee Members: Dr. Honggang Wang and Dr. Liudong Xing, Department of Electrical & Computer Engineering, UMass Dartmouth *For further information, please contact Dr. Hong Liu via email at hliu@umassd.edu.

Joint MNE-EAS Seminar by Dr. Peiman Naseradinmousavi

Joint Mechanical Engineering (MNE) and Engineering and Applied Sciences (EAS) SEMINAR DATE: April 16, 2021 TIME: 2:00 p.m. - 3:00 p.m. LOCATION: https://umassd.zoom.us/j/97680493591 SPEAKER: Peiman Naseradinmousavi, Associate Professor Dynamic Systems and Control Lab, Mechanical Engineering Department, San Diego State University TOPIC: Experimental Decentralized Adaptive Control and Delay Compensation for a High-DOF Robotic System ABSTRACT: Dealing with high-DOF robotic systems undoubtedly needs highly computationally efficient control algorithms to be implemented in real time. Many shortcomings of centralized control methods, either adaptive or nonadaptive, emerge for when the scale of such multiagent systems increases. This problem becomes more crucial in the presence of highly nonlinear dynamic interconnections among agents, here the robot's links. Through the first part of this seminar, I thoroughly present both analytical and experimental efforts for a novel decentralized adaptive control scheme to efficiently learn the coupled uncertainties vs. the centralized adaptive one for a 7-DOF Baxter robot. Mentioning the computational burden, typically leading to the operational failure, promptly reveals a challenging problem of delay compensation for such a coupled dynamical system. Within the second part, I discuss the cumbersome analytical formulation of the delay compensator, for the first time, to be experimentally implemented for the robotic system. BIO: Dr. Peiman Naseradinmousavi earned his PhD at Villanova University in 2012 and was presented with the College's Outstanding PhD Student Award. Today he is an Associate Professor of Mechanical Engineering at San Diego State University. Before joining San Diego State, he was a Visiting Assistant Professor at Purdue University. Dr. Naseradinmousavi's research interests include robotics, smart flow distribution networks, nonlinear dynamics, control theory, optimization, magnetic bearings, and mathematical modeling. He serves as Associate editor for the ASME Letters in Dynamic Systems and Control, and the Journal of Vibration and Control. His robotic research work has been publicized on NPR (KPBS) news. He was the recipient of the John J. Gallen Alumni Award 2021. Dr. Naseradinmousavi earned his B.Sc. in Mechanical Engineering (dynamics and control) from Tabriz University in 2002. For more information please contact Dr. Caiwei Shen, MNE Seminar Coordinator (cshen2@umassd.edu). All are welcome. Students taking MNE-500 are REQUIRED to attend! All other MNE BS and MS students are encouraged to attend. EAS students are also encouraged to attend. Thank you, Sue Cunha, Administrative Assistant scunha@umassd.edu 508-999-8492

Patriots' Day Holiday: no classes

Patriots' Day holiday, no classes today.

Follow Monday's class schedule

Follow Monday's schedule.

ECE Doctor of Philosophy Dissertation Defense by: Guilin Zhao

Topic: Competing Failure Analysis in Dynamic Internet of Things Systems Considering Random Propagation and Isolation Time Zoom Teleconference: https://umassd.zoom.us/j/94138501516 Abstract: The Internet of Things (IoT) has developed rapidly with the aim to improve the quality of modern life. Despite its considerable benefits, the IoT system poses many design challenges, among which assessing an IoT system's reliability is critical for assuring the success rate of IoT service delivery. As a cyber-physical system consisting of physical and communication subsystems, an IoT system exhibits various dependent and dynamic behaviors that significantly complicate its reliability modeling and analysis. Particularly, functional dependence (FDEP) exists in IoT systems, where the failure of one component (trigger) causes other components (dependent components) to become isolated (inaccessible or unusable). When such an isolation effect occurs with a certain probability, it is referred to as the probabilistic functional dependence (PDEP) behavior. The FDEP or PDEP behavior can cause deterministic or probabilistic competitions in the time domain between failure isolation and failure propagation effects, making reliability analysis of IoT systems challenging. Existing works addressing the competing failure effects have assumed that any failure propagation originating from a component instantaneously takes effect, which is often not true in real-world scenarios. Moreover, the existing works have assumed non-cascading FDEP or PDEP, where each system component can be a trigger or a dependent component, but not both. However, in practical systems with hierarchical configurations, cascading FDEP or PDEP can take place where a component plays a dual role as both a trigger and a dependent component simultaneously. Such a component causes correlations among different FDEP or PDEP groups, further complicating the reliability analysis of IoT systems. This dissertation makes contributions by proposing combinatorial methodologies for evaluating the reliability of IoT systems subject to cascading competing failures and random propagation time. This dissertation also contributes by addressing realistic random isolation time for IoT systems subject to the FDEP behavior. The suggested methodologies are flexible without limitation on distribution types of component lifetime, failure propagation time, or isolation time/factors. Detailed case studies on smart home systems and body sensor networks are conducted to illustrate the application and advantages of the proposed approaches. Effects of different model parameters on the reliability of IoT systems are investigated. The correctness of the proposed methods is verified using the continuous-time Markov chain-based method. NOTE: All ECE Graduate Students are ENCOURAGED to join the zoom teleconference. All interested parties are invited to join. Advisor: Dr. Liudong Xing Committee Members: Dr. Lance Fiondella and Dr. Honggang Wang, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Suprasad Amari, BAE Systems. *For further information, please contact Dr. Liudong Xing via email at lxing@umassd.edu.

Last day of Spring classes

Spring classes end today.

Mechanical Engineering Senior Design (Capstone) Presentations

The Mechanical Engineering Department is pleased to announce our Senior Design(Capstone)Presentations on April 29, 2021 from 9:00 a.m. - 5:00 p.m. The tentative agenda is available on our newly created website at: https://capstone2021.sites.umassd.edu/agenda/ Feel free to browse through our website to learn more about this year's projects. This is an all-day event, however as your schedule allows, please feel free to join in on the specific projects you're interested in, and for announcement of awards at the end of the day. This event will be on Zoom, however for the public it will also be live streamed on YouTube live and watched on any smart device. You can find the link for live stream on this page: https://capstone2021.sites.umassd.edu/live-stream/ Feel free to share the live stream link, as no registration is required to watch the You Tube live stream! This is always an exciting and proud day for everyone involved, as Senior students look forward to celebrating their academic achievements! Here is the list of projects: https://capstone2021.sites.umassd.edu/projects/ If you would like further information, please contact: Dr. Hamed Samandari Senior Design Instructor and Full Time Lecturer hsamandari@umassd.edu Sue Cunha Administrative Assistant scunha@umassd.edu Thank you and all the best.

Study Day

Today is study day.

Final exams begin

Examinations begin today.

Final exams end

Examinations end today.

Final grades due

Final grades are due today.

Last Day to Select or Revoke Pass/No Credit

Today is the last day to file Pass/Fail.