Software development needs continuous quality control for a timely detection and removal of quality problems. This includes frequent quality assessments, which need to be automated as far as possible to be feasible. One way of automation in assessing the security of software are application scanners that test an executing software for vulnerabilities. At present, common quality assessments do not integrate such scanners for giving an overall quality statement. This paper presents an integration of application scanners into a general quality assessment method based on explicit quality models and Bayesian nets. Its applicability and the detection capabilities of common scanners are investigated in a case study with two open-source web shops.
@cite_6 propose an security assessment method that has similarities to the method in this paper. It also defines metrics and aggregates them to quality attributes. This method, however, uses -ilities'' similar to ISO 9126 that have several well-known problems. Moreover, they concentrate on the architecture of the software (white-box view) whereas this paper focuses on testing by application scanners (black-box view).
@cite_6
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A proper security metrics and measurement process is thus a means to automatize security decisions. Unfortunately, so far automatic security evaluation techniques have failed to achieve the performance of security experts. In this paper we argue security metrics are by nature highly unstable in time. Moreover, their effectiveness depends on specific target of evaluation. In this paper we elaborate this finding and we describe our experimental framework with its results.