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Takeshi Yagi

Publications and source records attributed to Takeshi Yagi.

3 recordsLinked to original sources

Canary in Twitter Mine: Collecting Phishing Reports from Experts and Non-experts

The rise in phishing attacks via e-mail and short message service (SMS) has not slowed down at all. The first thing we need to do to combat the ever-increasing number of phishing attacks is to collect and characterize more phishing cases that reach end users. Without understanding these characteristics, anti-phishing countermeasures cannot evolve. In this study, we propose an approach using Twitter as a new observation point to immediately collect and characterize phishing cases via e-mail and SMS that evade countermeasures and reach users. Specifically, we propose CrowdCanary, a system capable of structurally and accurately extracting phishing information (e.g., URLs and domains) from tweets about phishing by users who have actually discovered or encountered it. In our three months of live operation, CrowdCanary identified 35,432 phishing URLs out of 38,935 phishing reports, 31,960 (90.2%) of these phishing URLs were later detected by the anti-virus engine. We analyzed users who shared phishing threats by categorizing them into two groups: experts and non-experts. As a results, we discovered that CrowdCanary extracts non-expert report-specific information, like company brand name in tweets, phishing attack details from tweet images, and pre-redirect landing page information.

cs.CR

User Blocking Considered Harmful? An Attacker-controllable Side Channel to Identify Social Accounts

This paper presents a practical side-channel attack that identifies the social web service account of a visitor to an attacker's website. Our attack leverages the widely adopted user-blocking mechanism, abusing its inherent property that certain pages return different web content depending on whether a user is blocked from another user. Our key insight is that an account prepared by an attacker can hold an attacker-controllable binary state of blocking/non-blocking with respect to an arbitrary user on the same service; provided that the user is logged in to the service, this state can be retrieved as one-bit data through the conventional cross-site timing attack when a user visits the attacker's website. We generalize and refer to such a property as visibility control, which we consider as the fundamental assumption of our attack. Building on this primitive, we show that an attacker with a set of controlled accounts can gain a complete and flexible control over the data leaked through the side channel. Using this mechanism, we show that it is possible to design and implement a robust, large-scale user identification attack on a wide variety of social web services. To verify the feasibility of our attack, we perform an extensive empirical study using 16 popular social web services and demonstrate that at least 12 of these are vulnerable to our attack. Vulnerable services include not only popular social networking sites such as Twitter and Facebook, but also other types of web services that provide social features, e.g., eBay and Xbox Live. We also demonstrate that the attack can achieve nearly 100% accuracy and can finish within a sufficiently short time in a practical setting. We discuss the fundamental principles, practical aspects, and limitations of the attack as well as possible defenses.

cs.CR

A Study on the Vulnerabilities of Mobile Apps associated with Software Modules

This paper reports a large-scale study that aims to understand how mobile application (app) vulnerabilities are associated with software libraries. We analyze both free and paid apps. Studying paid apps was quite meaningful because it helped us understand how differences in app development/maintenance affect the vulnerabilities associated with libraries. We analyzed 30k free and paid apps collected from the official Android marketplace. Our extensive analyses revealed that approximately 70%/50% of vulnerabilities of free/paid apps stem from software libraries, particularly from third-party libraries. Somewhat paradoxically, we found that more expensive/popular paid apps tend to have more vulnerabilities. This comes from the fact that more expensive/popular paid apps tend to have more functionality, i.e., more code and libraries, which increases the probability of vulnerabilities. Based on our findings, we provide suggestions to stakeholders of mobile app distribution ecosystems.

cs.CR