TC: Small: In-Cloud Security Services for Mobile Devices

现代移动平台，如Google Android和Apple iPhone，通过开放第三方开发并提供复杂的工作效率、通信和应用套件，正在重塑移动环境。此外，移动设备越来越多地被用于存储敏感的个人信息，如财务和医疗数据。移动环境面临一系列独特的安全挑战。首先，新兴移动平台拥有截然不同的安全和信任模式。其次，保护桌面安全的技术不能很好地过渡到移动环境，因为移动设备受到高度的资源限制。最后，移动设备的可用性模式与影响安全性的传统桌面设备本质上不同。该项目探索了一种新的移动安全模型，其基础是将恶意软件检测的复杂性转移到云内安全服务，而不是在每台移动设备上本地执行分析。我们将基于以下架构调查移动设备的云内安全服务：在移动设备上运行的轻量级代理介入应用程序和数据的访问，以及使用并行签名、行为和基于声誉的检测引擎识别恶意应用程序的网络服务。我们的方法围绕三个目标构建：(1)跨各种移动平台和安全模型的功能，(2)最小的设备上CPU、内存和电源资源，以及(3)适应移动可用性模式的安全性。我们将与我们的行业合作伙伴合作，促进通过这一努力开发的技术和方法在现场运营网络上的部署。

Modern mobile platforms, such as the Google Android and Apple iPhone, are reinventing the mobile landscape by opening up third-party development and by providing sophisticated productivity, communication, and application suites. In addition, mobile devices are increasingly used to store sensitive personal information such as financial and medical data. Mobile environments face a wide range of unique security challenges. First, emerging mobile platforms have vastly different security and trust models. Second, techniques that worked for securing desktops do not transition well to mobile environments because mobile devices are highly resource constrained. Finally, mobile devices have inherently different usability patterns than traditional desktops that impact security.This project explores a new model for mobile security based on moving the complexity of malware detection to an in-cloud security service rather than performing analysis locally on each mobile device. We will investigate in-cloud security services for mobile devices based on an architecture that consists of a lightweight agent that runs on mobile devices interposing on access of applications and data, and a network service that identifies malicious applications using parallel signature, behavioral, and reputation-based detection engines. Our approach is structured around three objectives: (1) functionality across a wide variety of mobile platforms and security models, (2) minimal on-device CPU, memory, and power resources, and (3) security that adapts to mobile usability patterns. We will work with our industry partners to facilitate the deployment of the techniques and methods developed through this effort on live operational networks.