Yelp reviews and ratings are important source of information to make informed decisions about a venue. We conjecture that further classification of yelp reviews into relevant categories can help users to make an informed decision based on their personal preferences for categories. Moreover, this aspect is especially useful when users do not have time to read many reviews to infer the popularity of venues across these categories.
One of the most difficult tasks in debugging software for a developer is to understand the nature of the fault. Techniques have been proposed by researchers that can help *locate* the fault, but mostly neglected is a way to describe the nature of the fault. We are developing software models, visualizations, and techniques to aid in the diagnosis of the faults in the software.
Bitcoin is a digital currency and payment platform that has been the source of much media attention. The currency is not backed by a government like most conventional currencies but is part of a democratic and dencentralized movement. Bitcoin transactions are pseudo-anonymous in a similar way to cash money. Why do people use this currency? How do their political values align with their usage of bitcoin? Furthermore, how does the community regulate itself in the absence of a formal hierarchical structure? Lastly, how do anonymous users form communities?
DELDroid is an automated system for determination of least privilege architecture in Android and its enforcement at runtime. A key contribution of our approach is the ability to limit the privileges granted to apps without the need to modify them.
DELDroid utilizes static program analysis techniques to extract the exact privileges each component needs for providing its functionality. A Multiple-Domain Matrix representation of the system's architecture is then used to automatically analyze the security posture of the system and derive its least-privilege architecture.
The dynamic nature of markets wherein business relationships are established and dissolved continuously demands systems that can cope with constant change, and do so with security paramount. These relationships are reified as services that are offered by organizations and used within a spectrum of domains and use contexts. Current service technologies fail to meet the requirements, however; interfaces are rigid, non-secure, and “one-size-fits-all solutions” which hardly meet the demands of any of its users.
In the era of big data and personalization, websites and (mobile) applications collect an increasingly large amount of personal information about their users. The large majority of users decide to disclose some but not all information that is requested from them. They trade off the anticipated benefits with the privacy risks of disclosure, a decision process that has been dubbed privacy calculus. Such decisions are inherently difficult though, because they may have uncertain repercussions later on that are difficult to weigh against the (possibly immediate) gratification of disclosure. How can we help users to balance the benefits and risks of information disclosure in a user-friendly manner, so that they can make good privacy decisions?
This research addresses challenges in understanding and developing lightweight, Web-based informal music education environments that bring the complexity and joy of orchestral music to diverse audiences. The challenges span from providing awareness and appreciation of different classical music genres through creation of multi-instrument musical compositions, in ways that are fun and interactive.
ISR
