Dr. Yu Cai, Applied Computing, is seeking motivated students to help with this summer’s GenCyber Teacher Camp, which takes place on campus July 19-23, 2021.
Twenty K-12 teachers attending the camp.
Students will work as teaching assistants and camp helpers. They will set up the lab, help during hands-on activities and games, manage the website, and help the assessment. Students will be paid for 3 weeks of work during July.
The multi-day virtual event involved 200 students on 40 teams. It opened for answer submission Friday, January 8, at 8:00 p.m., and closed Sunday, January 10, at 8 p.m.
The 3rd Place team, GoBlue!, trailed the 2nd Place team by only 14 points. RedTeam members are Michigan Tech undergraduates Dakoda Patterson, Computer Science, and Trevor Hornsby, Cybersecurity, and three University of Michigan students from the RedTeam’s partnership with that institution.
Michigan Tech RedTeam faculty advisors are Professor Yu Cai, Applied Computing, and Assistant Professor Bo Chen, Computer Science.
“We were lucky to be one of the 40 teams invited,” said Cai. “This was no small task, as the CTF included a large number of points in Reversing and “pwning” challenges, which proved to be fairly difficult. Other challenges were Cryptography, Stegonography, Web Exploitation, and miscellaneous challenges.”
CTF competitions place hidden “flags” in various computer systems, programs, images, messages, network traffic and other computing environments. Each individual or team is tasked with finding these flags. Participants win prizes while learning how to defend against cybersecurity attacks in a competitive and safe arena.
Bo Chen, Computer Science, has been awarded a Fall 2020 REF Research Seed Grant (REF-RS) for his project, “Towards Secure and Reliable Decentralized Cloud Storage.” Funding for the 12-month, $25,800 award begins on January 1, 2021.
“This grant will provide significant help to advance my current research,” says Chen. “This is really exciting news for me.”
As a recipient of the REF seed grant, which is awarded by the Michigan Tech Office of the Vice President for Research, Chen will participate in review and feedback for the next round of REF proposals. View the full list of Fall 2020 REF award recipients here.
A decentralized cloud storage system eliminates the need of dedicated computing infrastructures by allowing peers which have spare storage space to join the network and to provide storage service. Compared to the conventional centralized cloud storage system, it can bring significant benefits including cheaper storage cost, better fault tolerance, greater scalability, as well as more efficient data storing and retrieval, making it well fit the emerging Internet of things (IoT) applications.
While bringing immense benefits, the decentralized cloud storage system also raises significant security concerns, since the storage peers are much less reputable than the traditional data centers and may more likely misbehave.
This project thus aims to build a secure and reliable decentralized cloud storage system which can serve as the cloud infrastructure for future IoT applications. The project will actively investigate two fundamental security issues faced by the decentralized cloud storage system: 1) How can we prevent the malicious storage peers from stealing the data? 2) How can we ensure that once the data are stored into the system, they are always retrievable even if the storage peers misbehave?
To address the aforementioned issues in an untrusted p2p environment, the PI will integrate efficient integrity checking with the blockchain, as well as the broadly equipped secure hardware like Intel SGX. The PI will also broaden the educational impact of the proposed project by actively involving both graduate and undergraduate students from the MTU cybersecurity programs.
The Vice President for Research Office announces the Fall 2020 REF awards. Thanks to the individual REF reviewers and the REF review panelists, as well as the deans and department chairs, for their time spent on this important internal research award process.
Associate Professor Guy Hembroff, director of Michigan Tech’s Health Informatics graduate program, presented an invited virtual talk to physicians, residents, and medical students at the Bahiana Medical School, Salvador, Brazil, on September 25, 2020.
Hembroff spoke about, “The Challenges and Opportunities of Artificial Intelligence in Disease Prevention and Monitoring.”
BAHIANA (Bahia School of Medicine and Public Health) is a private, nonprofit, educational, cultural, scientific and healthcare institution. Its main purpose is “teaching, research and the spread of knowledge and special services in the fields of health, science and culture in general.” Learn more here.
A paper authored by Michigan Tech Assistant Professor Bo Chen, Computer Science, and Data Science master’s student Shashank Reddy Danda, has been accepted for publication in the IEEE Internet of Things Magazine special issue on Smart IoT Solutions for Combating COVID-19 Pandemic. The special issue will be published in September 2020.
The paper focuses on Chen’s research of COVID-19 prevention through the leveraging of computing technology. The project is currently supported by a Michigan Tech College of Computing seed grant, and external funding for further development is being pursued.
Chen is a member of the ICC’s Center for Cybersecurity.
Abstract: Recently, the impact of coronavirus has been witnessed by almost every country around the world. To mitigate spreading of coronavirus, a fundamental strategy would be reducing the chance of healthy people from being exposed to it. Having observed the fact that most viruses come from coughing/sneezing/runny nose of infected people, in this work we propose to detect such symptom events via mobile devices (e.g., smartphones, smart watches, and other IoT devices) possessed by most people in modern world and, to instantly broadcast locations where the symptoms have been observed to other people. This would be able to significantly reduce risk that healthy people get exposed to the viruses. The mobile devices today are usually equipped with various sensors including microphone, accelerometer, and GPS, as well as network connection (4G, LTE, Wi-Fi), which makes our proposal feasible. Further experimental evaluation shows that coronavirus-like symptoms (coughing/sneezing/runny nose) can be detected with an accuracy around 90%; in addition, the dry cough (more likely happening to COVID-19 patients) and wet cough can also be differentiated with a high accuracy.
Bo Chen is an assistant professor in the Department of Computer Science. His areas of expertise include mobile device security, cloud computing security, named data networking security, big data security, and blockchain.
Shashank Reddy Danda is an MS student in Data Science. He is currently working as a research assistant in MTU Security and Privacy (SnP) Lab under the supervision of Dr. Bo Chen.
IEEE Internet of Things Magazine (IEEE IoTM) is a publication of the IEEE Internet of Things Initiative, a Multi-Society Technical Group.
Professor Yu Cai, Applied Computing, a member of the ICC’s Center for Cybersecurity, is the principal investigator on a two-year project that has received a $99,942 grant from the National Security Agency (GenCyber). The project is titled, “GenCyber Teacher Camp at Michigan Tech. “
Lecturer Tim Van Wagner (AC) and Assistant Professor Bo Chen (CS, DataS) are Co-PIs. Cai will serve as the camp director, Tim Van Wagner as lead instructor.
This GenCyber project aims to host a week-long, residential summer camp for twenty K-12 STEM teachers in 2021 at Michigan Tech. Target educators are primarily from Michigan and surrounding states.
The objectives of the camp are to teach cybersecurity knowledge and safe online behavior, develop innovative teaching methods for delivering cybersecurity content, and provide professional development opportunities so participants will return to their home schools with contagious enthusiasm about teaching cybersecurity.
The GenCyber camp will be offered at no cost to camp participants. Room and board will be provided. Teacher participants will receive a stipend of $500 for attending and completing camp activities.
Read about the 2019 Michigan Tech GenCyber camps for teachers and students here.
The MTU RedTeam ranked 13th out of 162 teams in a recent 24-hour Cybar OSINT Capture The Flag (CTF) cybersecurity competition. The team finished tied for 5th place, having completed all the challenges presented by the competition.
Students on the team were Trevor Hornsby (Software Engineering), Shane Hoppe (Computer Science), Matthew Chau (Cybersecurity), Steven Whitaker (Electrical Engineering), and Sankalp Shastry (Electrical Engineering).
Professor Yu Cai, Applied Computing, and Assistant Professor Bo Chen, Computer Science, are advisor and co-advisor of RedTeam, respectively. Both are members of the ICC’s Center for Cybersecurity.
RedTeam promotes a security-driven mindset among Michigan Tech students and provides a community and resource for those wishing to learn more about information security. The RedTeam competes in National Cyber League (NCL) competitions, a great way for students to gain competency in cybersecurity tools and boost their resumes.
RedTeam is on Slack at mturedteam.slack.com. Interested students can sign up with a Michigan Tech email. View past RedTeam presentations here.
This OSINT CTF is non-theoretical and contestants work in teams of up to four members to crowdsource the collection of OSINT to assist law enforcement in generating new leads on missing persons.
The contest runs as a Capture the Flag (CTF) format where contestants must collect various “flags” which equate to points. Since the each flag submitted is treated as potential “net new intelligence”, Trace Labs has a team of volunteers known as “Judges” who validate each submission and award points if the flag meets the category requirements. At the end of each CTF, the team with the most points on the scoreboard wins.
College of Computing Assistant Professor Bo Chen, Computer Science, and his graduate students presented two posters at the 41st IEEE Symposium on Security and Privacy, which took place online May 18 to 21, 2020.
Since 1980, the IEEE Symposium on Security and Privacy has been the premier forum for presenting developments in computer security and electronic privacy, and for bringing together researchers and practitioners in the field.
Chen leads the Security and Privacy (SnP) lab at Michigan Tech. He is a member of Michigan Tech’s Institute of Computing and Cybersystems (ICC) Center for Cybersecurity (CyberS).
Chen’s research focuses on applied cryptography and data security and he investigates novel techniques to protect sensitive data in mobile devices/flash storage media and cloud infrastructures. Chen is also interested in designing novel techniques to ensure security and privacy of big data.
Chen will serve as general chair for the First EAI International Conference on Applied Cryptography in Computer and Communications (AC3), which will be held in Xiamen, China, in May 2021.
Poster: A Secure Plausibly Deniable System for Mobile Devices against Multi-snapshot Adversaries Authors:Bo Chen, Niusen Chen Abstract: Mobile computing devices have been used broadly to store, manage and process critical data. To protect confidentiality of stored data, major mobile operating systems provide full disk encryption, which relies on traditional encryption and requires keeping the decryption keys secret. This however, may not be true as an active attacker may coerce victims for decryption keys. Plausibly deniable encryption (PDE) can defend against such a coercive attacker by disguising the secret keys with decoy keys. Leveraging concept of PDE, various PDE systems have been built for mobile devices. However, a practical PDE system is still missing which can be compatible with mainstream mobile devices and, meanwhile, remains secure when facing a strong multi- snapshot adversary. This work fills this gap by designing the first mobile PDE system against the multi-snapshot adversaries.
Poster: Incorporating Malware Detection into Flash Translation Layer Authors: Wen Xie, Niusen Chen, Bo Chen Abstract: OS-level malware may compromise OS and obtain root privilege. Detecting this type of strong malware is challeng- ing, since it can easily hide its intrusion behaviors or even subvert the malware detection software (or malware detector). Having observed that flash storage devices have been used broadly by computing devices today, we propose to move the malware detector to the flash translation layer (FTL), located inside a flash storage device. Due to physical isolation provided by the FTL, the OS-level malware can neither subvert our malware detector, nor hide its access behaviors from our malware detector.