Visible to the public Vulnerability and Resilience Prediction Models - July 2014

Submitted by aehunt on Fri, 06/27/2014 - 5:24pm

Public Audience
Purpose: To highlight project progress. Information is generally at a higher level which is accessible to the interested public. All information contained in the report (regions 1-3) is a Government Deliverable/CDRL.

PI(s):  Mladen Vouk, Laurie Williams
Researchers:  Da Young Lee

 

HARD PROBLEM(S) ADDRESSED

  • Security Metrics and Models -
  • Resilient Architectures -
  • Scalability and Composability -

Resilience of software to attacks is an open problem. Resilience depends on the science behind the approach used, as well as our engineering abilities. The scope of interests includes recognition of attacks through metrics and models we use to describe and recognize software vulnerabilities, and predict resilience to attacks in the field (Security Metrics and Models). It also depends on the software (and system) architecture(s) used (Resilient Architectures), and their scalability (Scalability and Composability). For example, if one has a number of highly attack-resilient components and appropriate attack sensors, is it possible to compose a really resilient system from these parts, and how does that solution scale and age?

PUBLICATIONS
Report papers written as a results of this research. If accepted by or submitted to a journal, which journal. If presented at a conference, which conference.

None in this reporting period.

 

ACCOMPLISHMENT HIGHLIGHTS

- We have several publications in preparation. One is already under review.

- What appears to be emerging from our analyses of hybrid soft sensors is that a combination of back-to-back testing and "classical" acceptance testing is able to detect zero-day attacks (in our case-study on three most popular web-servers over last five years).

 

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