Category: News

You are invited to spend one-zero-one-zero—that is, ten—minutes with Dr. Brian Yuan on Thursday, April 29, at 4:30 p.m. EST.

Dr. Yuan is an Assistant Professor in both the Applied Computing and Computer Science departments. His areas of expertise include machine learning, security and privacy, and cloud computing.

Yuan will discuss his research, the Applied Computing and Computer Science departments, and answer questions.

Join the virtual event here.

Dr. Yuan earned his PhD in Computer Science at University of Florida.

We look forward to spending 1010 minutes with you!

Visit the 1010 with … webpage here.

Xinyu Lei, a Ph.D. candidate in the Department of Computer Science and Engineering at Michigan State University, will present a talk on Thursday, April 29, 2021, at 3:00 p.m.

In his talk, “Secure and Efficient Queries Processing in Cloud Computing,” Lei will discuss his work developing new techniques to support secure and efficient queries processing in cloud storage.

Join the virtual talk here.

Title

Secure and Efficient Queries Processing in Cloud Computing

Abstract

With the advent of cloud computing, data owners are motivated to outsource their databases to the commercial public cloud for storage. The public cloud with database-as-a-service (DBaaS) model has many benefits (including lower cost, better performance, and higher flexibility). However, hosting the datasets on the commercial public cloud deprives the data owners’ direct control over their databases, which brings in security concerns. For example, the corrupted cloud employees may spy the data owner’s commercial valuable databases and sell them for money. To protect data privacy, the sensitive database must be encrypted before outsourcing to the cloud. However, it becomes hard to perform efficient queries (e.g., keyword query) processing over the encrypted database.

In this talk, I focus on developing new techniques to support secure and efficient queries processing in cloud storage. An index-aid approach is proposed to address the problem. In my approach, the data items are formally encrypted, and a secure index is generated for efficient queries processing. The cloud can perform queries directly over the secure index rather than the encrypted data items. The secure index is constructed based on a new data structure named random Bloom filter. Then, multiple random Bloom filters are organized into a binary tree structure to support fast query processing. The proposed approach can achieve data privacy, index privacy, search token privacy, and fast query processing simultaneously.

Biography

Xinyu Lei is a Ph.D. candidate in the Department of Computer science and Engineering at Michigan State University. He once worked as a research assistant in Texas A&M University at Qatar and Ford Motor Company. He has research interests in cybersecurity problems in different computer systems (including IoT, blockchain, cloud computing). He has published 20+ papers with 600+ citations. His work has been published on top-tier conferences and journals such as ACM MobiSys, ACM CodaSpy, IEEE ICDE, IEEE ICDCS, etc.

Two College of Computing-affiliated graduate students presented their research at the Graduate Research Colloquium, which took place April 1-2, 2021. View all the research here.

Meara Pellar-Kosbar – Data Science

Simulating the Spread of Infectious Diseases

This simulation is designed to show how a fictional viral illness could spread among people in a virtual room. Over the course of the virtual simulation, a number of automatic simulated people called subjects will move about an adjustable virtual grid. During this time, subjects will come into contact with each other and with item cells in the virtual room. Subjects will be exposed to this fictional virus via contact with other subjects, items, and via the air when within a certain distance of a contagious subject. The viral counts of each subject will be tracked and shown as the simulation

Intelligent.com, a resource for ranking online degree rankings and higher education planning, has placed two Michigan Tech online graduate programs on its lists of the nation’s best.

Michigan Tech is on Intelligent.com’s list of Online Master’s in Civil Engineering Degree programs. The website analyzed 181 schools on a scale of 0 to 100, with 29 making the final list. Michigan Tech’s online Master’s in Civil Engineering ranked #21 on the list.

Michigan Tech was also on Intelligent.com’s list of the Best Online Master’s in Electrical Engineering Degree Programs. The website assessed 190 colleges and universities with 424 education programs compared. Once again, programs were scored on a scale of 0 to 100 with a total of 41 programs making the list. Michigan Tech’s online master’s in electrical engineering program was ranked #28 on the list.

by Graduate Student Government

The Graduate Student Government (GSG) to announced the executive board members for the 2021/22 session:

• President — Nathan Ford, PhD Student in Mechanical Engineering and Engineering Mechanics 
• Vice-President — Ranit Karmakar, PhD Student in Electrical & Computer Engineering 
• Secretary — Divya Pandya, PhD Student in Mechanical Engineering and Engineering Mechanics 
• Treasurer — Michael Conard, PhD Student in Computer Science
• Research Chair — Shreya Joshi, PhD Student in Physics
• Professional Development Chair — Umair Riyas, MS Student in Engineering Management, College of Business
• Social Chair — Eric Pearson, PhD Student in Chemical Engineering
• Public Relations Chair — Laura Vidal Chiesa, PhD Student in Humanities 

The new executive board will begin its term on May 1, 2021.

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.