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    Tara Salman, Washington Univ., to Present Talk April 27

    Tara Salman, a final-year PhD candidate at Washington University in St. Louis, will present a talk on Tuesday, April 27, 2021, at 3:00 p.m.

    In her talk, “A Collaborative Knowledge-Based Security Solution using Blockchains,” she will present her work on redesigning the blockchains and building a collaborative, distributed, intelligent, and hostile solution that can be used for security purposes.

    Join the virtual talk here.

    Talk Title

    A Collaborative Knowledge-Based Security Solution using Blockchains

    Talk Abstract

    Artificial intelligence and machine learning have recently gained wide adaptation in building intelligent yet simple and proactive security solutions such as intrusion identification, malware detection, and threat intelligence. With the increased risk and severity of cyber-attacks and the distributed nature of modern threats and vulnerabilities, it becomes critical to pose a distributed intelligent solution that evaluates the systems’ and networks’ security collaboratively. Blockchain, as a decade-old successful distributed ledger technology, has the potential to build such collaborative solutions. However, to be used for such solutions, the technology needs to be extended so that it can intelligently process the stored information and achieve a collective decision about security risks or threats that might target a system.

    In this talk, I will present our work on redesigning the blockchains and build a collaborative, distributed, intelligent, and hostile solution that can be used for security purposes. In particular, we will discuss our work on (1) extending blockchains for general collaborative decision-making applications, where knowledge should be made out of decisions, risks, or any information stored on the blockchain; (2) applying the proposed extensions to security applications such as malware detection and threat intelligence.

    Biography

    Tara Salman is a final year Ph.D. candidate at Washington University in St. Louis, where she is advised by Raj Jain. She previously received her MS and BSc degrees from Qatar University in 2015 and 2012, respectively. Her research aims to integrate state-of-the-art technologies to provide scalable, collaborative, and intelligent cybersecurity solutions.

    Her recent work focuses on the intersection of artificial intelligence, blockchains, and security applications. The work spans several fields, including blockchain technology, security, machine learning, and deep learning applications, cloud computing, and the Internet of Things. She has been selected for the EECS Rising Star in UC Berkeley 2020. Her research has been published in more than twenty internationally recognized conferences and journals and supported by national and international funds.


    Dr. Qun Li to Present Lecture April 23, 3 pm


    The Department of Computer Science will present a lecture by Dr. Qun Li on Friday, April 23, 2021, at 3:00 p.m. Dr. Li is a professor in the computer science department at William and Mary university. The title of his lecture is, “Byzantine Fault Tolerant Distributed Machine Learning.”

    Join the virtual lecture here.

    Lecture Title

    Byzantine Fault Tolerant Distributed Machine Learning

    Lecture Abstract

    Training a deep learning network requires a large amount of data and a lot of computational resources. As a result, more and more deep neural network training implementations in industry have been distributed on many machines. They can also preserve the privacy of the data collected and stored locally, as in Federated Deep Learning.

    It is possible for an adversary to launch Byzantine attacks to a distributed or federated deep neural network training. That is, some participating machines may behave arbitrarily or maliciously to deflect the training process. In this talk, I will discuss our recent results on how to make distributed and federated neural network training resilient to Byzantine attacks. I will first show how to defend against Byzantine attacks in a distributed stochastic gradient descent (SGD) algorithm, which is the core of distributed neural network training. Then I will show how we can defend against Byzantine attacks in Federated Learning, which is quite different from distributed training.


    GenCyber Teacher Camp Is July 19-23, 2021


    An NSA/NSF GenCyber Cybersecurity Teacher Camp for K-12 teachers will take place at Michigan Tech the week of July 19 – 23, 2021. The residential camp is offered at no cost to all participants.

    Topics include fundamental security knowledge, cyber hygiene, and other topics such as email phishing, password management, and cyber ethics. Participants will also learn how to develop lesson plans to teach cybersecurity in K-12.

    Room and board are included. Each teacher participant will receive a stipend of $500 for attending and completing camp activities. Commuting is also possible. Camp activities will count for 25 State Continuing Education Clock Hours (SCECH).

    Find complete details and apply here.  The application deadline is May 1, 2021.

    Funding of the camp is provided jointly by the National Security Agency (NSA) and the National Science Foundation (NSF) through a grant award led by Professor Yu Cai and Tim Van Wagner, both from the College of Computing Department of Applied Computing.

    Watch a video from the 2019 GenCyber Teacher Camp below.

    Gencyber Teacher Camp @ Michigan Tech 2019


    GenCyber Cybersecurity Teacher Camp Is July 19-23

    by Yu Cai, College of Computing

    A GenCyber Cybersecurity Teacher Camp for K-12 teachers will be held at Michigan Tech during the week of July 19 – 23. Participants will learn cyber hygiene and fundamental security knowledge including email phishing, password management, and cyber ethics. Participants will also learn how to develop lesson plans to teach cybersecurity in K-12.

    This is a residential camp (commuting optional), and is offered at NO COST to all participants. Room and board is included. Each teacher participant will receive a stipend of $500 for attending and completing camp activities. Camp activities will count for 25 State Continuing Education Clock Hours (SCECH).

    Click here for more information and to apply. The application deadline is May.

    Funding for the camp is provided jointly by the National Security Agency (NSA) and the National Science Foundation (NSF) through an award led by Yu Cai and Tim Van Wagner from the College of Computing.


    ECE Master’s Defense: Chinmay Rajaram Kondekar

    by Electrical and Computer Engineering

    Electrical Engineering Master’s candidate Chinmay Kondekar (advisor: Aleksandr Sergeyev), will present his master’s defense at 11 a.m. Tuesday (April 13) via Zoom. 

    The title of his presentation is “Integration of Robotic and Electro-Pneumatic Systems Using Advanced Control and Communication Schemes.”