Sharing cyber security data across organizational boundaries brings both privacy risks in the exposure of personal information and data, and organizational risk in disclosing internal information. These risks occur as information leaks in network traffic or logs, and also in queries made across organizations. They are also complicated by the trade-offs in privacy preservation and utility present in anonymization to manage disclosure. In this paper, we define three principles that guide sharing security information across organizations: Least Disclosure, Qualitative Evaluation, and Forward Progress. We then discuss engineering approaches that apply these principles to a distributed security system. Application of these principles can reduce the risk of data exposure and help manage trust requirements for data sharing, helping to meet our goal of balancing privacy, organizational risk, and the ability to better respond to security with shared information.

No abstract

Phishing sites masquerade as copies of legitimate sites ("targets") to fool people into sharing sensitive information that can then be used for fraud. Current phishing defenses can be ineffective, with training ignored, blacklists of discovered, bad sites too slow to pick up new threats, and whitelists of knowngood sites too limiting. We have developed a new technique that automatically builds personalized lists of target sites (candidates that may be copied by phish) and then tests sites as a user browses them. Our approach uses cryptographic hashing of each page's rendered Document Object Model (DOM), providing a zero false positive rate and identifying more than half of detectable phish in a controlled study. Since each user develops a customized list of target sites, our approach presents a diverse defense against phishers. We have prototyped our approach as a Chrome browser plugin called AuntieTuna, emphasizing usability through automated and simple manual addition of target sites and clean reports of potential phish that include context about the targeted site. AuntieTuna does not slow web browsing time and presents alerts on phishing pages before users can divulge information. Our plugin is open-source and has been in use by a few users for months. Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.

No abstract