Biblio

There is a need for new tools and techniques to aid automotive engineers performing cybersecurity testing on connected car systems. This is in order to support the principle of secure-by-design. Our research has produced a method to construct useful automotive security tooling and tests. It has been used to implement Controller Area Network (CAN) fuzz testing (a dynamic security test) via a prototype CAN fuzzer. The black-box fuzz testing of a laboratory vehicle's display ECU demonstrates the value of a fuzzer in the automotive field, revealing bugs in the ECU software, and weaknesses in the vehicle's systems design.

This paper studies the principle of vulnerability generation and mechanism of cross-site scripting attack, designs a dynamic cross-site scripting vulnerabilities detection technique based on existing theories of black box vulnerabilities detection. The dynamic detection process contains five steps: crawler, feature construct, attacks simulation, results detection and report generation. Crawling strategy in crawler module and constructing algorithm in feature construct module are key points of this detection process. Finally, according to the detection technique proposed in this paper, a detection tool is accomplished in Linux using python language to detect web applications. Experiments were launched to verify the results and compare with the test results of other existing tools, analyze the usability, advantages and disadvantages of the detection method above, confirm the feasibility of applying dynamic detection technique to cross-site scripting vulnerabilities detection.

According to a 2011 survey in healthcare, the most commonly reported breaches of protected health information involved employees snooping into medical records of friends and relatives. Logging mechanisms can provide a means for forensic analysis of user activity in software systems by proving that a user performed certain actions in the system. However, logging mechanisms often inconsistently capture user interactions with sensitive data, creating gaps in traces of user activity. Explicit design principles and systematic testing of logging mechanisms within the software development lifecycle may help strengthen the overall security of software. The objective of this research is to observe the current state of logging mechanisms by performing an exploratory case study in which we systematically evaluate logging mechanisms by supplementing the expected results of existing functional black-box test cases to include log output. We perform an exploratory case study of four open-source electronic health record (EHR) logging mechanisms: OpenEMR, OSCAR, Tolven eCHR, and WorldVistA. We supplement the expected results of 30 United States government-sanctioned test cases to include log output to track access of sensitive data. We then execute the test cases on each EHR system. Six of the 30 (20%) test cases failed on all four EHR systems because user interactions with sensitive data are not logged. We find that viewing protected data is often not logged by default, allowing unauthorized views of data to go undetected. Based on our results, we propose a set of principles that developers should consider when developing logging mechanisms to ensure the ability to capture adequate traces of user activity.