Role-based access control is an important access control method for securing computer systems. A role-based access control policy can be implemented incorrectly due to various reasons, such as programming errors. Defects in the implementation may lead to unauthorized access and security breaches. To reveal access control defects, this paper presents a model-based approach to automated generation of executable access control tests using predicate/transition nets. Role-permission test models are built by integrating declarative access control rules with functional test models or contracts (preconditions and postconditions) of the associated activities (the system functions). The access control tests are generated automatically from the test models to exercise the interactions of access control activities. They are transformed into executable code through a model-implementation mapping that maps the modeling elements to implementation constructs. The approach has been implemented in an industry-adopted test automation framework that supports the generation of test code in a variety of languages. The full model-based testing process has been applied to three systems implemented in Java. The effectiveness is evaluated through mutation analysis of role-based access control rules. The experiments show that the model-based approach is highly effective in detecting the seeded access control defects.

The world's increased dependence on software-enabled systems has raised major concerns about software reliability and security. New cost-effective tools for software quality assurance are needed. This paper presents an automated test generation technique, called Model-based Integration and System Test Automation (MISTA), for integrated functional and security testing of software systems. Given a Model-Implementation Description (MID) specification, MISTA generates test code that can be executed immediately with the implementation under test. The MID specification uses a high-level Petri net to capture both control- and data-related requirements for functional testing, access control testing, or penetration testing with threat models. After generating test cases from the test model according to a given criterion, MISTA converts the test cases into executable test code by mapping model-level elements into implementation-level constructs. MISTA has implemented test generators for various test coverage criteria of test models, code generators for various programming and scripting languages, and test execution environments such as Java, C, C++, C#, HTML-Selenium IDE, and Robot Framework. MISTA has been applied to the functional and security testing of various real-world software systems. Our experiments have demonstrated that MISTA can be highly effective in fault detection.

Access control policies in software systems can be implemented incorrectly for various reasons. This paper presents a model-based approach for automated testing of access control implementation. To feed the model-based testing process, test models are constructed by integrating declarative access control rules and contracts (preconditions and post-conditions) of the associated activities. The access control tests are generated from the test models to exercise the interactions of access control activities. Test executability is obtained through a mapping of the modeling elements to implementation constructs. The approach has been implemented in an industry-adopted test automation framework that supports the generation of test code in a variety of languages, such as Java, C, C++, C#, and HTML/Selenium IDE. The full model-based testing process has been applied to two systems implemented in Java. The effectiveness is evaluated in terms of access-control fault detection rate using mutation analysis of access control implementation. The experiments show that the model-based tests killed 99.7% of the mutants and the remaining mutants caused no policy violations.

Security attacks typically result from unintended behaviors or invalid inputs. Security testing is labor intensive because a real-world program usually has too many invalid inputs. It is highly desirable to automate or partially automate security-testing process. This paper presents an approach to automated generation of security tests by using formal threat models represented as Predicate/Transition nets. It generates all attack paths, i.e., security tests, from a threat model and converts them into executable test code according to the given Model-Implementation Mapping (MIM) specification. We have applied this approach to two real-world systems, Magento (a web-based shopping system being used by many online stores) and FileZilla Server (a popular FTP server implementation in C++). Threat models are built systematically by examining all potential STRIDE (spoofing identity, tampering with data, repudiation, information disclosure, denial of service, and elevation of privilege) threats to system functions. The security tests generated from these models have found multiple security risks in each system. The test code for most of the security tests can be generated and executed automatically. To further evaluate the vulnerability detection capability of the testing approach, the security tests have been applied to a number of security mutants where vulnerabilities are injected deliberately. The mutants are created according to the common vulnerabilities in C++ and web applications. Our experiments show that the security tests have killed the majority of the mutants.

Phishing attack has been a serious concern to online banking and e-commerce Websites. This paper proposes a method to detect and filter phishing emails in dynamic environment by applying a family of weak estimators. Anomaly detection identifies observations that deviate from the normal behavior of a system and is achieved by identifying the phenomena that characterize the “normal” observation. The new observations are classified either a normal or abnormal based on the characteristics of data learnt. Most of the anomaly detection works with the assumption that the underlying distributions of observations are stationary, where this assumption is relevant to many applications. However some detection problem occurs within environments that are non-stationary. One good example to demonstrate the information is by identifying anomalous temperature pattern in meteorology that takes into account the seasonal changes of normal observations. It is necessary that anomalous observations are identified even with the changes or acquire the ability to adapt to the variations in non-stationary environments. Our experimental results show the feasibility and effectiveness of our approach.

Ratings are the prominent factors to decide the fate of any product in the present Internet Market and many people follow the ratings in a genuine sense. Unfortunately, the Sibyl attacks can affect the credibility of the genuine product. Influence limiter algorithms in recommender systems have been used extensively to overcome the Sibyl attacks but the effort could not reach the safe mark. This paper highlights an approach to generating gaming strategies for the attacker and defender in a recommender system. In a given recommender system environment, attackers and defenders play the most crucial part in a gaming strategy. A sequence of decision rules that an attacker or defender may use to achieve their desired goal is represented in these strategies involved in the game theory. The valid approaches to avoid the Sibyl attacks from the attackers are efficiently defended by the defenders. In our approach, we define attack graphs, use cases, and misuses cases in our gaming framework to analyze the vulnerabilities and security measures incorporated in a recommender system.