An Advanced Methodology to Analyse Data Stored on Mobile Devices

摘要: Nowadays computer and mobile devices, such as phones, smartphones, smartwatches, tablets, etc., represent the multimedia diary of each us. Thanks to technological evolution advent an infinite number applications, mainly aimed at socialization entertainment, they have become containers personal professional information. For this reason, optimizing performance systems able detect intrusions (IDS - Intrusion Detection System) is a goal common interest. This paper presents methodology classify hacking attacks taking advantage generalization property neural networks. In particular, in work we adopt multilayer perceptron (MLP) model with back-propagation algorithm sigmoidal activation function. We analyse results obtained using different configurations for network, varying hidden layers training epochs order obtain low false positives. The will be presented terms type show that best classification carried out DOS Probe attacks.