Zertifizierung im Namen der IT-Sicherheit

Identitäts- und Datendiebstahl, Cyberattacken, Betrug und Spionage bedrohen Bürger, Verwaltung und Wirtschaft. IT-Sicherheit wird somit zu einem immer wichtigeren Thema für die Gesellschaft. Denn Kunden und Bürger fordern von Wirtschaft und Verwaltung nachweislich sichere Produkte und Prozesse. Welche Bedeutung hat in diesem Zusammenhang die Zertifizierung von IT-Produkten und Prozessen

Dynamic reverse engineering of GUI models for testing

A significant challenge in application of model-based testing (MBT) is that manually designing the test models requires considerable amount of effort and deep expertise in formal modeling. Reverse engineering can be used to automate parts of the modeling process but in applications with a graphical user interface (GUI), the dynamic behavior of the GUI is difficult to extract with static reverse engineering. Therefore we propose to use dynamic reverse engineering for automatically generating GUI models suitable for MBT. In this paper we compare various approaches for automated GUI modeling including an empirical tool study, propose a GUI component classification suitable for GUI automation, and present some examples of GUI automation strategies for efficient modeling of GUI applications

Enhancing generated Java GUI models with valid test data

Iterative prototyping process in the development of graphical user interface (GUI) software is a considerable challenge for test automation. The maintenance work required for updating the test suites because of the constant changes in the GUI decreases the benefits gained from test automation and a large part of GUI software is still tested manually. In this paper we present a method and tool support for automatically creating and iteratively enhancing models of Java GUI applications, using the models for test case generation and automatically executing the generated test cases. During the first step the GUI Driver tool generates models presenting the state and behavior of the GUI application that is executed and observed automatically. Then the user can provide valid test data for the input fields of the GUI application and the GUI Driver tool uses the information to automatically enhance the generated GUI models. The enhanced models can be used for model-based testing (MBT) purposes

Sichere mobile Authentifizierung

Während Onlinedienste immer smarter und ausgefeilter werden, scheint eines konstant zu bleiben – die Authentifizierung. 87 Prozent der deutschen Internetnutzer verwenden zum Login Benutzername und Passwort. Während wir überall nach mehr Sicherheit verlangen, verlassen wir uns bei Onlinediensten auf ein Konzept, das mehr als 30 Jahre alt und bekanntermaßen anfällig ist. Welche Alternativen es gibt, wie sie funktionieren sie und wie eine sichere mobile Authentifizierung aussehen kann zeigt dieses White Paper auf

Diagnostic performance of MRI measurements to assess hindfoot malalignment. An assessment of four measurement techniques

OBJECTIVE: To investigate the ability of coronal non-weight-bearing MR images to discriminate between normal and abnormal hindfoot alignment. METHODS: Three different measurement techniques (calcaneal axis, medial/lateral calcaneal contour) based on weight-bearing hindfoot alignment radiographs were applied in 49 patients (mean, 48 years; range 21-76 years). Three groups of subjects were enrolled: (1) normal hindfoot alignment (0°-10° valgus); (2) abnormal valgus (>10°); (3) any degree of varus hindfoot alignment. Hindfoot alignment was then measured on coronal MR images using four different measurement techniques (calcaneal axis, medial/lateral calcaneal contour, sustentaculum tangent). ROC analysis was performed to find the MR measurement with the greatest sensitivity and specificity for discrimination between normal and abnormal hindfoot alignment. RESULTS: The most accurate measurement on MR images to detect abnormal hindfoot valgus was the one using the medial calcaneal contour, reaching a sensitivity/specificity of 86 %/75 % using a cutoff value of >11° valgus. The most accurate measurement on MR images to detect abnormal hindfoot varus was the sustentaculum tangent, reaching a sensitivity/specificity of 91 %/71 % using a cutoff value of <12° valgus. CONCLUSION: It is possible to suspect abnormal hindfoot alignment on coronal non-weight-bearing MR images. KEY POINTS : • Abnormal hindfoot alignment can be identified on coronal non-weight-bearing MR images. • The sustentaculum tangent was the best predictor of an abnormally varus hindfoot. • The medial calcaneal contour was the best predictor of a valgus hindfoot