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The growing market of the mobile application is overtaking the web application. Mobile application development environment is open source, which attracts new inexperienced developers to gain hands on experience with application development. However, the security of data and vulnerable coding practice is an issue. Among all mobile Operating systems such as, iOS (by Apple), Android (by Google) and Blackberry (RIM), Android dominates the market. The majority of malicious mobile attacks take advantage of vulnerabilities in mobile applications, such as sensitive data leakage via the inadvertent or side channel, unsecured sensitive data storage, data transition and many others. Most of these vulnerabilities can be detected during mobile application analysis phase. In this paper, we explore vulnerability detection for static and dynamic analysis tools. We also suggest limitations of the tools and future directions such as the development of new plugins. 

The majority of malicious mobile attacks take advantage of vulnerabilities in mobile applications, such as sensitive data leakage via inadvertent or side channel, unsecured sensitive data storage, data transmission, and many others. Most of these mobile vulnerabilities can be detected in the mobile software testing phase. However, most development teams often have virtually no time to address them due to critical project deadlines. To combat this, the more defect removal filters there are in the software development life cycle, the fewer defects that can lead to vulnerabilities will remain in the software product when it is released. As part of Secure Mobile Software Development (SMSD) project, we are currently developing capacity to address the lack of pedagogical materials and real world learning environment in secure mobile software development through effective, engaging, and investigative approaches. In this session, we provide details of a new implemented module named data protection. We also share our initial experience and feedback on the developed module. 

Security vulnerabilities in an application open the ways to security dangers and attacks, which can easily jeopardize the system executing that application. Therefore, it is important to develop vulnerability-free applications. The best approach would be to counteract against potential vulnerabilities during the coding with secure programming practices. Software security proactive control education for secure portable and web application advancement is of enormous interests in the Information Technology (IT) fields. In this paper, we proposed and developed innovative learning modules for software security proactive control based on several real-world scenarios to broaden and promote proactive control for secure software development in computing education. 

While the number of mobile applications are rapidly growing, these applications are often coming with numerous security flaws due to the lack of appropriate coding practices. Security issues must be addressed earlier in the development lifecycle rather than fixing them after the attacks because the damage might already be extensive. Early elimination of possible security vulnerabilities will help us increase the security of our software and mitigate or reduce the potential damages through data losses or service disruptions caused by malicious attacks. However, many software developers lack necessary security knowledge and skills required at the development stage, and Secure Mobile Software Development (SMSD) is not yet well represented in academia and industry. In this paper, we present a static analysis-based security analysis approach through design and implementation of a plugin for Android Development Studio, namely DroidPatrol. The proposed plugins can support developers by providing list of potential vulnerabilities early. 

The majority of malicious mobile attacks take advantage of vulnerabilities in mobile software (applications), such as sensitive data leakage, unsecured sensitive data storage, data transmission, and many others. Most of these vulnerabilities can be detected by analyzing the mobile software. In this paper, we describe a tainted dataflow approach to detect mobile software security vulnerability, particularly, SQL Injection.