Biblio

With the proliferation of Mobile Internet, handheld devices are facing continuous threats from apps that contain malicious intents. These malicious apps, or malware, have the capability of dynamically changing their intended code as they spread. Moreover, the diversity and volume of their variants severely undermine the effectiveness of traditional defenses, which typically use signature-based techniques, and make them unable to detect the previously unknown malware. However, the variants of malware families share typical behavioral patterns reflecting their origin and purpose. The behavioral patterns, obtained either statically or dynamically, can be exploited to detect and classify unknown malware into their known families using machine learning techniques. In this paper, we propose a new approach for detecting and analyzing a malware. Mainly focused on android apps, our approach adopts the two following steps: (1) performs a transformation of an APK file into a lightweight RGB image using a predefined dictionary and intelligent mapping, and (2) trains a convolutional neural network on the obtained images for the purpose of signature detection and malware family classification. The results obtained using the Androzoo dataset show that our system classifies both legacy and new malware apps with high accuracy, low false-negative rate (FNR), and low false-positive rate (FPR).

The Software Defined Networks (SDN) paradigm, often referred to as a radical new idea in networking, promises to dramatically simplify network management by enabling innovation through network programmability. However, notable security issues, such as app-to-control threats, remain a significant concern that impedes SDN from being widely adopted. To cope with those app-to-control threats, this paper proposes a solution to securely deploy valid network applications while protecting the SDN controller against the injection of the malicious application. This problem is mitigated by proposing a novel SDN architecture, dubbed SENAD, which splits the well-known SDN controller into: (1) a data plane controller (DPC), and (2) an application plane controller (APC), to secure this latter by design. The role of the DPC is dedicated for interpreting the network rules into OpenFlow entries and maintaining the communication with the data plane. The role of the APC, however, is to provide a secured runtime for deploying the network applications, including authentication, access control, resource isolation, control, and monitoring applications. We show that this approach can easily shield against any deny of service, caused for instance by the resource exhaustion attack or the malicious command injection, that is caused by the co-existence of a malicious application on the controller's runtime. The evaluation of our architecture shows that the packet\_in messages take less than 5 ms to be delivered from the data plane to the application plane on the long range.