Research

Image-Centric Social Discovery Using Neural Network under Anonymity Constraint

A common part of social networks is sharing images. Storing and processing these images to provide engaging services to customers is resource intensive and social networks often rely on cloud services to provide these resources. This creates a potential security risk for the users of the social network platform. Simply encrypting the images before uploading …

Benjamin Fung – Kam1n0 Assembly Clone Search for Reverse Engineering

Presented at the Spring 2016 SERENE-RISC Workshop. Assembly code analysis is one of the critical processes for mitigating the exponentially increasing threats from malicious software. It is also a common practice for detecting and justifying software plagiarism and software patent infringements when the source code is unavailable. However, it is a manually intensive and time-consuming …

Privacy Loss in Apple’s Implementation of Differential Privacy on MacOS 10.12

Differential privacy (DP) provides a way to quantify privacy. A privacy budget quantitatively measures by how much the risk to an individual’s privacy may increase due to the inclusion of certain data. The higher the value, the less privacy protection is provided. This paper by Jun Tang, Aleksandra Korolova, Xiaolong Bai, Xueqiang Wang, and Xiaofeng Wang identifies the components …

Mining the Networks of Telecommunication Fraud Groups using Social Network Analysis

Telecommunications fraud groups, the ones running scams over the telephone are a problem around the world. Taiwan is no exception with a number of related arrests in the past decade.  Telecom fraud group. Yi-Chun Chang, Kuan-Ting Lai, Seng-Cho T. Chou and Ming-Syan Chen wanted to learn more about how these fraud groups operate through Social …

Zero Days, Thousands of Nights: The Life and Times of Zero-Day Vulnerabilities and Their Exploits

RAND obtained a dataset of information about zero-day software exploits through a research connection. It is a rich dataset, as some of these exploits have been found by others and some have not. The dataset spans 14 years (2002–2016) and contains information about more than 200 zero-day exploits and the vulnerabilities that they take advantage …