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Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve complex real world problems. QML has the potential to address cybersecurity related challenges. Considering the novelty and complex architecture of QML, resources are not yet explicitly available that can pave cybersecurity learners to instill efficient knowledge of this emerging technology. In this research, we design and develop QML-based ten learning modules covering various cybersecurity topics by adopting student centering case-study based learning approach. We apply one subtopic of QML on a cybersecurity topic comprised of pre-lab, lab, and post-lab activities towards providing learners with hands-on QML experiences in solving real-world security problems. In order to engage and motivate students in a learning environment that encourages all students to learn, pre-lab offers a brief introduction to both the QML subtopic and cybersecurity problem. In this paper, we utilize quantum support vector machine (QSVM) for malware classification and protection where we use open source Pennylane QML framework on the drebin 215 dataset. We demonstrate our QSVM model and achieve an accuracy of 95% in malware classification and protection. We will develop all the modules and introduce them to the cybersecurity community in the coming days. 

This Innovative Practice Work in Progress presents a plugin tool named DroidPatrol. It can be integrated with the Android Studio to perform tainted data flow analysis of mobile applications. Most vulnerabilities should be addressed and fixed during the development phase. Computer users, managers, and developers agree that we need software and systems that are “more secure”. Such efforts require support from both the educational institutions and learning communities to improve software assurance, particularly in writing secure code. Many open source static analysis tools help developers to maintain and clean up the code. However, they are not able to find potential security bugs. Our work is aimed to checking of security issues within Android applications during implementation. We provide an example hands-on lab based on DroidPatrol prototype and share the initial evaluation feedback from a classroom. The initial results show that the plugin based hands-on lab generates interests among learners and has the promise of acting as an intervention tool for secure software development. 

This Innovative Practice Work in Progress presents a plugin tool named DroidPatrol. It can be integrated with the Android Studio to perform tainted data flow analysis of mobile applications. Most vulnerabilities should be addressed and fixed during the development phase. Computer users, managers, and developers agree that we need software and systems that are “more secure”. Such efforts require support from both the educational institutions and learning communities to improve software assurance, particularly in writing secure code. Many open source static analysis tools help developers to maintain and clean up the code. However, they are not able to find potential security bugs. Our work is aimed to checking of security issues within Android applications during implementation. We provide an example hands-on lab based on DroidPatrol prototype and share the initial evaluation feedback from a classroom. The initial results show that the plugin based hands-on lab generates interests among learners and has the promise of acting as an intervention tool for secure software development. 

This Innovative Practice Work in Progress presents a plugin tool named DroidPatrol. It can be integrated with the Android Studio to perform tainted data flow analysis of mobile applications. Most vulnerabilities should be addressed and fixed during the development phase. Computer users, managers, and developers agree that we need software and systems that are “more secure”. Such efforts require support from both the educational institutions and learning communities to improve software assurance, particularly in writing secure code. Many open source static analysis tools help developers to maintain and clean up the code. However, they are not able to find potential security bugs. Our work is aimed to checking of security issues within Android applications during implementation. We provide an example hands-on lab based on DroidPatrol prototype and share the initial evaluation feedback from a classroom. The initial results show that the plugin based hands-on lab generates interests among learners and has the promise of acting as an intervention tool for secure software development. 

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.