Services on the public Internet are frequently scanned, then subject to brute-force and denial-of-service attacks. We would like to run such services stealthily, available to friends but hidden from adversaries. In this work, we propose a moving target defense named “Chhoyhopper” that utilizes the vast IPv6 address space to conceal publicly available services. The client and server hop to different IPv6 addresses in a pattern based on a shared, pre-distributed secret and the time of day. By hopping over a /64 prefix, services cannot be found by active scanners, and passively observed information is useless after two minutes. We demonstrate our system with the two important applications—SSH and HTTPS.
This work is supported, in part, by DHS HSARPA Cyber Security Division via contract number HSHQDC-17-R-B0004-TTA.02-0006-I, and by DARPA under Contract No. HR001120C0157.
As the field of big data analytics matures, workflows are increasingly complex and often include components that are shared by different users. Individual workflows often include multiple stages, and when groups build on each other’s work it is easy to lose track of computation that may be shared across different groups.
The contribution of this poster is to provide an organization-wide processing substrate Plumb that can be used to solve commonly occurring problems and to achieve a common goal. Plumb makes multi-user sharing a first-class concern by providing pipeline-graph abstraction. This abstraction is simple and based on fundamental model of input-processing-output but is powerful to capture processing and data duplication. Plumb then employs best available solutions to tackle problems of large-block processing under structural and computational skew without user intervention.
We expect to release the Plumb software this fall; please contact us if you have questions or interest in using it.
Increasing use of Internet banking and shopping by a broad spectrum of users results in greater potential profits from phishing attacks via websites that masquerade as legitimate sites to trick users into sharing passwords or financial information. Most browsers today detect potential phishing with URL blacklists; while effective at stopping previously known threats, blacklists must react to new threats as they are discovered, leaving users vulnerable for a period of time. Alternatively, whitelists can be used to identify “known-good” websites so that off-list sites (to include possible phish) can never be accessed, but are too limited for many users. Our goal is proactive detection of phishing websites with neither the delay of blacklist identification nor the strict constraints of whitelists. Our approach is to list known phishing targets, index the content at their correct sites, and then look for this content to appear at incorrect sites. Our insight is that cryptographic hashing of page contents allows for efficient bulk identification of content reuse at phishing sites. Our contribution is a system to detect phish by comparing hashes of visited websites to the hashes of the original, known good, legitimate website. We implement our approach as a browser extension in Google Chrome and show that our algorithms detect a majority of phish, even with minimal countermeasures to page obfuscation. A small number of alpha users have been using the extension without issues for several weeks, and we will be releasing our extension and source code upon publication.
End-to-end reachability is a fundamental service of the Internet. We study network outages caused by natural disasters, and political upheavals. We propose a new approach to outage detection using active probing. Like prior outage detection methods, our method uses ICMP echo requests (“pings”) to detect outages, but we probe with greater density and ner granularity, showing pings can detect outages without supplemental probing. The main contribution of our work is to dene how to interpret pings as outages: defining an outage as a sharp change in block responsiveness relative to recent behavior. We also provide preliminary analysis of outage rate in the Internet edge. Space constrains this poster abstract to only sketches of our approach; details and validation are in our technical report. Our data is available at no charge, see http://www.isi.edu/ant/traces/internet_outages/.