Project Details
Description
Cyber threats have escalated rapidly over the past decade. "Zero-day
attacks" have become significant, delivered increasingly through
seemingly innocuous means such as web pages, images, and documents.
Malware is rampant, being installed surreptitiously on millions of
computers around the world using a combination of spam, phishing,
malicious shareware and freeware.
Today's defenses use techniques such as signature-based scanning and
file integrity monitoring to detect the presence of malware, and then
remove them. Unfortunately, clever adversaries can quickly develop
malware that conceals itself from these detection mechanisms, and
hence defeat such reactive defenses. In contrast, this project will
develop an approach that dramatically improves defenses against
malware, and put a computer owner back in control over the
attackers. This approach, based on synthesizing and enforcing
low-level information flow properties from generic high level
policies, will be used to identify components of a computer system
that are critical for its trustworthiness, and preserve their
integrity. In doing so, the approach will enable users to continue to
use popular operating systems, applications, and add-on software, while still
assuring system security.
Specifically, this project will develop techniques to protect (a) the OS
and critical applications from untrusted code or data, (b) critical
applications from modules and extensions (e.g., browser plug-ins and media
player codecs) that run within the same address space, and (c) the OS kernel
from damage due to untrusted kernel extensions such as device drivers.
In terms of broader impact, this project will train several graduate
students, the research will be integrated into the teaching activities of
the PIs, and finally, the solutions developed will be distributed as
open-source software and/or tools.
| Status | Finished |
|---|---|
| Effective start/end date | 09/1/08 → 08/31/15 |
Funding
- National Science Foundation: $1,000,000.00
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.