With the number of connected smart devices expected to constantly grow in the next years, Internet of Things (IoT) solutions are experimenting a booming demand to make data collection and processing easier. The ability of IoT appliances to provide pervasive and better support to everyday tasks, in most cases transparently to humans, is also achieved through the high degree of autonomy of such devices. However, the higher the number of new capabilities and services provided in an autonomous way, the wider the attack surface that exposes users to data hacking and lost. In this scenario, many critical challenges arise also because IoT devices have heterogeneous computational capabilities (i.e., in the same network there might be simple sensors/actuators as well as more complex and smart nodes). In this paper, we try to provide a contribution in this setting, tackling the non-trivial issues of equipping smart things with a strategy to evaluate, also through their neighbors, the trustworthiness of an object in the network before interacting with it. To do so, we design a novel and fully distributed trust model exploiting devices' behavioral fingerprints, a distributed consensus mechanism and the Blockchain technology. Beyond the detailed description of our framework, we also illustrate the security model associated with it and the tests carried out to evaluate its correctness and performance.

翻译：随着联网智能设备数量在未来数年预计持续增长，物联网解决方案正经历蓬勃需求，以简化数据采集与处理流程。物联网设备在大多数情况下以对用户透明的方式，为日常任务提供普适且更优支持的能力，亦通过此类设备的高度自治得以实现。然而，以自主方式提供的新功能与服务数量越多，使用户面临数据泄露与丢失风险的攻击面就越广。在此情境下，诸多关键挑战随之涌现，其原因还在于物联网设备具备异构计算能力（即同一网络中可能同时存在简单传感器/执行器与更复杂的智能节点）。本文旨在为该领域做出贡献，应对一个非平凡问题：为智能设备配备一种策略，使其在与其他网络对象交互前，能通过自身及邻节点评估该对象的可信度。为此，我们设计了一种新型完全分布式信任模型，该模型利用设备行为指纹、分布式共识机制及区块链技术。除详细描述框架外，我们还阐述了其关联的安全模型，以及为评估其正确性与性能所开展的测试。