Division of Computer and Network Systems (CNS)
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Submitted by Qiang Zeng on Fri, 03/08/2019 - 5:38pm
During the past decade, middleware on mobile platforms (such as the Application Framework in Android and the Core Services layer in iOS) has been flourishing, but the insecurity analysis of such middleware has been lagging behind. For example, while comprehensive studies have been conducted at the application layer of the Android system, there is very limited work analyzing the Android Application Framework (Android Framework, for short), a middleware layer in the Android system.
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Submitted by Abhishek Jain on Fri, 03/08/2019 - 5:01pm
Today, vast amounts of private datasets are stored by individuals and institutions on personal electronic devices and cloud servers. Many applications of tremendous societal impact can benefit from the ability to perform joint computations on these datasets. However, in the presence of malicious actors -- whether it be the entities performing the computation or external processes -- this benefit is associated with a significant risk of losing data privacy.
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Submitted by Ana Milanova on Fri, 03/08/2019 - 4:55pm
Cloud service providers offer a wide range of data storage and computation products. Customers increasingly outsource data and computation to third-party cloud providers. However, when customers upload their data to the cloud provider, they relinquish data confidentiality. As countless recent events attest, securing data and computation is a problem of tremendous importance.
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Submitted by Adam Lee on Fri, 03/08/2019 - 4:46pm
High-fidelity, and often privacy-invasive, sensors are now becoming pervasive in our everyday environments. At home, digital assistants can constantly listen for instructions and security cameras can be on the lookout for unusual activity. Whereas once an individual's physical actions, in their own home, were private, now networked cameras and microphones can give rise to electronic privacy concerns for one's physical behaviors. Casual conversations and encounters, once thought to be private and ephemeral, now may be captured and disseminated or archived digitally.
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Submitted by Kiran Balagani on Fri, 03/08/2019 - 4:41pm
Modern smartphones regularly store and access large amounts of personal data, such as e-mails, photos, videos, and banking information. For this reason, securing them is of paramount importance. User authentication is a crucial step towards securing a smartphone. However, current user authentication mechanisms such as graphical passwords, Personal Identification Numbers (PINs), and fingerprint scans offer limited security, and are ineffective after the smartphone has been unlocked.
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Submitted by Shouhuai Xu on Fri, 03/08/2019 - 3:57pm
Classification and clustering are two important classes of machine learning techniques that have been widely used for cyber defense purposes. However, these mechanisms can be defeated by intelligent evasion attacks, such as Adversarial Machine Learning. Currently, there are no effective countermeasures against these sophisticated attacks. The objective of the project is to investigate effective countermeasures to make classification and clustering mechanisms robust against intelligent evasion attacks.
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Submitted by Nicolas Christin on Fri, 03/08/2019 - 3:43pm
Different countries have very different positions concerning freedom of expression, and may be increasingly using online filtering tools for web censorship. While the research community has devoted significant attention to the problem of anonymous communication, many other aspects of censorship and anonymization have not yet been studied in detail. We do not know, for instance, whether it is possible to automatically infer which techniques censors use and which topics censors are after.
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Submitted by Damon McCoy on Fri, 03/08/2019 - 3:39pm
Online social networks (OSNs) have fundamentally transformed how billions of people use the Internet. These users are increasingly discovering books, music bands, TV shows, movies, news articles, products, and other content through posts from trusted users that they follow. All major OSNs have deployed content curation algorithms that are designed to increase interaction and act as the "gatekeepers" of what users see.
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Submitted by Chintan Patel on Fri, 03/08/2019 - 10:48am
Secret keys that are stored and used within physical devices can be extracted by adversaries. The attacks involve measuring the power consumption or electromagnetic radiation emanating from the chip as it carries out encryption, and then analyzing them to deduce the secret key. This project investigates techniques that self-mutate the hardware at runtime as a means of significantly reducing and ideally eliminating signal information leveraged by the adversary.
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Submitted by Nicholas Hopper on Fri, 03/08/2019 - 10:44am
Texting and social media-based messaging applications have become nearly as common as face-to-face communications for conversation between individuals and groups. While it is known how to provide privacy for conversations between two individuals, there is a gap in extending these techniques to group conversations. This project is developing new communication techniques and open-source software for private communication among groups of users.
