Cocoon: Emotion psychology meets cyber security in IoT smart homes

在Cocoon中，我们将两个截然不同的学科的创新融合在一起，以理解和提高家庭物联网技术的安全性：情感心理学和网络安全。我们了解物联网用户的心理，评估当前和未来物联网系统的风险，并为未来家庭中以用户为中心的物联网的设计和集成制定规定。家是体验隐私和控制、个人自主和完整性的避风港。物联网技术预计将融合物理和虚拟世界，创造增强健康的智能家居环境。随着物理和虚拟的日益接近，对安全、隐私和信任的担忧也以类似的方式增长。解决这些问题需要与个人相一致的技术部署和干预措施。我们的目标是双重的：1）检查物联网用户在家中舒适度方面的情感投资，这将影响他们的使用技术，在安全受到破坏时推动他们的反应，并将决定他们的恢复能力。大规模的定性和定量研究，以及在20个志愿者家庭中进行的为期四个月的实验，不仅将产生第一个关于物联网用户在正常使用和智能家居受损情况下情绪状态的综合理论框架，而且还将通过将用户重新塑造为系统的一个组成部分，为新型入侵检测系统（IDS）的开发提供信息。2)对主流的现成物联网技术进行测试，并基于对来自此类异构技术集的数据的实时分析，获得创建适合特定居住者配置文件的IDS和数据安全可视化的经验机会。在独立的实验室环境中进行的入侵实验将允许检查典型智能家居中的影响。IDS将基于为资源受限的物联网环境量身定制的实时大数据流挖掘分类技术。

In Cocoon, we interweave innovations in two distinctly different disciplines to understand and improve security of home IoT technology: emotion psychology and cyber security. We produce an understanding of the psychology of IoT users, assess risks in current and future IoT systems, and formulate provisions for the design and integration of user-centric IoT in tomorrow's homes. Home is a safe haven to experience privacy and control, personal autonomy and integrity. IoT technology is expected to merge physical and virtual worlds, creating smart home environments that enhance wellbeing. As the physical and the virtual grow closer, concerns for security, privacy and trust grow in similar measures. Addressing these concerns requires technological dispositions and interventions aligned with the individuals. Our objectives are twofold: 1) To examine the emotional investment of IoT users in the comfort of their home, which will condition their usage technology, drive their reactions when security is breached, and will determine their ability to recover. Large-scale qualitative and quantitative studies, and a four-month experiment conducted in 20 volunteering households will not only yield the first comprehensive theoretical framework of the emotional status of IoT users in cases of both normal usage and when their smart home is compromised, but will also inform the development of a novel intrusion detection system (IDS) by recasting the user as an integral part of the system. 2) To put mainstream off-the- shelf IoT technology to the test, and derive empirical opportunities for creating IDS and data security visualization that are appropriate for given occupants' profiles, based on real-time analytics of data from such a heterogeneous set of technologies. Intrusion experiments in self-contained laboratory environments will permit the examination of the effects in a typical smart home. The IDS will be based on real-time big data stream mining classification techniques tailored for resource-constrained IoT environments.