Earticle

The work presented in this paper proposes a formal model of constraints for testing the conformity of an implementation from its specification. The principal idea of our approach is based on an equivalence partitioning of input domains for each method type in an object oriented (OO) paradigm for detecting the different classes of errors. The main contribution of our approach is the use of invalid data which do not satisfy the precondition constraints for testing the robustness of entities in an OO model. Indeed, the first objective of the proposed work is to develop a theoretical model of constraint in order to test the conformity of classes. The second objective of our approach is to detect anomalies in invalid input data which induce valid output constraints. The implementation of this approach is based on a random generation of test data and analysis by formal proof.

This paper presents an approach for extending the constraint model defined for conformity testing of a given method of class to its overriding method in subclass using inheritance principle. The main objective of the proposed work is to find the relationship between the test model of an overriding method and its overridden method using the constraint propagation. Our approach shows that the test cases developed for testing an original method can be used for testing its overriding method in a subclass and then the number of test cases can be reduced considerably. The implementation of this approach is based on a random generation of test data and analysis by formal proof.

스마트폰의 대중화로 다양한 애플리케이션이 증가하면서, Third party App Market 이나 블랙마켓을 통한 악성 애플리케이션 또한 급격한 증가세에 있다. 본 논문에서는 APK파일의 변조여부를 효과적으로 검출할 수 있는 검사 필터인 Androfilter를 제안한다. Androfilter는 대부분의 안티바이러스 소프트웨어들이 사용하는 수집, 분석, 업데이트 서버등을 사용하지 않고, Google Play를 신뢰 기관으로 가정하여 대응되는 애플리케이션의 조회만으로 애플리케이션의 변조여부를 판단 한다. 실험 결과에 따르면 변조된 애플리케이션을 감지함으로 보고되지 않은 신종 악성코드를 차단할 수 있다.

As the popularization of smartphone increases the number of various applications, the number of malicious applications also grows rapidly through the third party App Market or black market. This paper suggests an investigation filter, Androfilter, that detects the fabrication of APK file effectively. Whereas the most of antivirus software uses a separate server to collect, analyze, and update malicious applications, Androfilter assumes Google Play as the trusted party and verifies integrity of an application through a simple query to Google Play. Experiment results show that Androfilter blocks brand new malicious applications that have not been reported yet as well as known malicious applications.