A Client/Server Malware Detection Model Based on Machine Learning for Android Devices

The rapid adoption of Android devices comes with the growing prevalence of mobile malware, which leads to serious threats to mobile phone security and attacks private information on mobile devices. In this paper, we designed and implemented a model for malware detection on Android devices to protect private and financial information, for the mobile applications of the ATISCOM project. This model is based on client/server architecture, to reduce the heavy computations on a mobile device by sending data from the mobile device to the server for remote processing (i.e., offloading) of the predictions. We then gradually optimized our proposed model for better classification of the newly installed applications on Android devices. We at first adopted Naive Bayes to build the model with 92.4486% accuracy, then the classification method that gave the best accuracy of 93.85% for stochastic gradient descent (SGD) with binary class (i.e., malware and benign), and finally the regression method with numerical values ranging from −100 to 100 to manage the uncertainty predictions. Therefore, our proposed model with random forest regression gives a good accuracy in terms of performance, with a good correlation coefficient, minimum computation time and the smallest number of errors for malware detection.

Threats and Vulnerabilities of Mobile Applications

Smart devices like mobile phones, tablets, and laptops have become necessities in our lives due to the services they provide. However, in recent days, mobile applications have become a major threat for an attack. One of the most attractive features of smartphones is the availability of a large number of apps for users to download and install. However, it also means hackers can easily distribute malware to smartphones, launching various attacks. Each day, a mobile device attack is changing dynamically, and it is very difficult to represent a complete set of threats and vulnerabilities. Mobile phone security has become an important aspect of security issues in wireless multimedia communications. The development of mobile applications has increased drastically; hence, it is our responsibility to protect our devices and the data within them. Being aware is the first step to protect data. Thus, to prevent the mobile from the threats, efforts are required to form the application developer, app market administrator, and user to defend against the malware. This article explores those threats and vulnerabilities of mobile applications.

Threats and Vulnerabilities of Mobile Applications

Smart devices like mobile phones, tablets, and laptops have become necessities in our lives due to the services they provide. However, in recent days, mobile applications have become a major threat for an attack. One of the most attractive features of smartphones is the availability of a large number of apps for users to download and install. However, it also means hackers can easily distribute malware to smartphones, launching various attacks. Each day, a mobile device attack is changing dynamically, and it is very difficult to represent a complete set of threats and vulnerabilities. Mobile phone security has become an important aspect of security issues in wireless multimedia communications. The development of mobile applications has increased drastically; hence, it is our responsibility to protect our devices and the data within them. Being aware is the first step to protect data. Thus, to prevent the mobile from the threats, efforts are required to form the application developer, app market administrator, and user to defend against the malware. This article explores those threats and vulnerabilities of mobile applications.

Light Weight Defense Mechanism Against Camera Based Attacks

A number of android security and privacy vulnerabilities have been exposed in past several years. However, the mobile malware and privacy leakage remain a big threat to mobile phone security and privacy. It has been observed that phone camera would become a traitor in such attacks by capturing photos or videos secretly. Secret photography is not only immoral but also illegal due to invasion of privacy. Phone users themselves could also become victims and if the phone camera is exploited by malicious spy camera app, it may cause serious security and privacy problems. Most of the existing mobile antivirus apps are unable to monitor such camera based attacks. Hence, we demonstrate two camera based attacks through our proposal namely, Remote controlled real time monitoring Attack like Screen unlocking Attack, SMS Attack. We also propose a light weight defense scheme as a countermeasure for the camera attacks that can protect android phones against harmful spy Camera attacks.