Fall 2020 CS Cyber Security Reading Group
Members: Yashwanth Bandala, Yu Cai, Bo Chen (co-advisor), Niusen Chen, Shashank Reddy Danda, Siva Krishna Kakula, Vishnu Kamaraju, Alex Larkin, Jean Mayo (co-advisor), Joe Muhle, Jagi Rinchin, Jonah Schulte, Sai Venkateswaran, Sankalp Shastry, Shuo Sun, Deepthi Tankasala, Yuchen Wang, Wen Xie, Xiaoyong Yuan
Time: 3:00 – 4:00pm Friday, September 18, 2020
Presenter: Dr. Xiaoyong Yuan (Assistant Professor, Applied Computing and Computer Science)
Title: Beyond Class-Level Privacy Leakage: Breaking Record-Level Privacy in Federated Learning
Federated learning (FL) enables multiple clients to collaboratively build a global learning model without disclosing their own data, such as the virtual keyboard (Gboard), for privacy protection. However, recent research found privacy leakage of FL, especially on image classification tasks, such as the client-level reconstruction of class representative. Nevertheless, such analysis on image classification tasks is not applicable to uncover the privacy threats against natural language processing (NLP) tasks, such as the language modeling used in Gboard, whose records composed of sequential texts cannot be grouped as class representatives. Moreover, due to the finer granularity, it is challenging to distinguishably extract individual records from a specific client, which is a serious threat to leak more precise private information. This paper gives the first attempt to explore the record-level privacy leakage against NLP tasks in FL. We propose a framework to investigate the exposure of the record of interest in federated aggregations based on the perplexity of language modeling. By monitoring the exposure patterns, two correlation attacks are proposed to identify the corresponding clients when extracting their specific records. Extensive experiments demonstrate the effectiveness of the proposed attacks. We then investigate several countermeasures to mitigate the attacks, which, however, are ineffective.
Time: 2:00 – 3:00pm Friday, October 2, 2020
Presenter: Shashank Reddy
Title: Towards Mitigating Spreading of Coronavirus via Mobile Devices
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 possessed by most people in the 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. Implementation using mobile devices is shown along with some demo videos.
Time: 2:00 – 3:00pm Friday, October 23, 2020
Presenter: Niusen Chen
Title and Abstract will be added.
Time: 3:00 – 4:00pm Friday, November 6, 2020
Presenter: Jonah Schulte
Title: Mouse Trap: Forget USB Sticks, Attacks Could Come from Essential Peripheral Devices
In our continually digitizing world, the threat of malware has continued to rear its ugly head, and expand, despite humanity's best efforts. The practice of infecting a USB storage device, and leaving on the ground near a target has become all too common the attempt to compromise a system, and more often than not, it succeeds. This study, and subsequent paper, endeavor to highlight the very real, and potentially very dangerous, act of using peripheral devices, instead of common USB sticks, to carry and execute malware on a device. In this study, the researchers strived to show the weakness of peripheral devices and their liability for malware. They worked on the mouse pictured here, the Logitech G600.
Time: 3:00 – 4:00pm Friday, November 20, 2020
Presenter: Deepthi Tankasala
Title: Blockchain Technology on different platforms
When we say Blockchain, the prominent application we remember is cryptocurrency. There are many more technologies where Blockchain can be applied starting from the Internet of Things, Artificial Intelligence, and many more. This presentation talks about the different applications along with their architectures that are being developed where the inclusion of blockchain can be a game-changer in terms of security and availability. In this talk, I plan to present some of the most prominent applications of Blockchain technology other than the famously known cryptocurrencies.