Mobile devices carry a number of vulnerabilities that, when exploited, can result in proprietary-data leakage, data alteration, fraudulent transactions and, in extreme cases, physical damage to the user and surroundings. Such attacks can be instigated by both outsiders and insiders, and can leverage vulnerabilities embedded in the hardware and software components of the device, as well as risky behavioral actions undertaken by the legitimate user of the device. Existing mobile security management solutions offer a wide range of configuration, tracking, and management features via device and container management, policy-based configuration, single sign-on, application whitelisting and/or blacklisting, as well as reputation and anti-malware services. A primary feature that none of the existing solutions has is context-aware anomaly detection. We propose a novel cognitive solution for mobile security based on context awareness. Our solution focuses on mobile management tools that understand long-term context-aware behavior anomalies on multiple devices.