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Denial of Service (DoS) is one of the common attempts in security hacking for making computation resources unavailable or to impair geographical networks. In this paper, we detect Denial of Service (DoS) attack from publicly available datasets using Logistic regression, Naive Bayes algorithm and artificial neural networks. The results from our experiments indicate that the accuracy, ROC curve and balanced accuracy of artificial neural network were higher than Naive Bayes algorithm and logistic regression for slightly imbalanced distribution dataset. 

The security threats to mobile application are growing explosively. Mobile app flaws and security defects could open doors for hackers to easily attack mobile apps. Secure software development must be addressed earlier in the development life cycle rather than fixing the security holes after attacking. Early eliminating against possible security vulnerability will help us increase the security of software and mitigate the consequence of damages of data loss caused by potential malicious attacking. In this paper, we present a static security analysis approach with open source FindSecurityBugs plugin for Android Studio IDE. We demonstrate that integration of the plugin enables developers secure mobile application and mitigating security risks during implementation time in Android Studio IDE. We demonstrate that integration of the plugin enables developers secure mobile application and mitigating security risks during implementation time. Secure software development must be addressed earlier in the development lifecycle rather than fixing the security holes after attacking. Early eliminating against possible security vulnerability will help us increase the security of software and mitigate the consequence of damages of data loss caused by potential malicious attacking. In this paper, we present a static security analysis approach with open source FindSecurityBugs plugin for Android Studio IDE. We demonstrate that integration of the plugin enables developers secure mobile application and mitigating security risks during implementation time. 

Insecure data storage may open a door to malicious malware to steal users' and system sensitive information. These problems may due to developer negligence or lack of security knowledge. Android developers use various storage methods to store data. However, Attackers have attacked these vulnerable data storage. Although the developers have modified the apps after knowing the vulnerability, the user's personal information has been leaked and caused serious consequences. As a result, instead of patching and fixing the vulnerability, we should conduct proactive control for secure Android data storage. In this paper, we analyzed Android external storage vulnerability and discussed the prevention solutions to prevent sensitive information in external storage from disclosure.