Context-aware Software Defined Privacy in the Internet of Things

物联网中上下文感知软件定义的隐私

• 批准号: RGPIN-2019-05006
• 负责人: Dara, Rozita
• 金额: $ 1.68万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=750346
• 关键词: Context; aware; Software; Defined; Privacy

The physical and virtual space that we live in are becoming increasing intelligent. Many of the objects that surround us in the so-called Internet of Things (IoT) have some level of intelligence and are capable of communicating, collecting, accessing, and processing information. This intelligent space is accessible ubiquitously from anywhere, at anytime, and by anyone/anything that has the ability to exercise access rights. Such capability depends on processes, regulations, and security and privacy practices that are established by organizations, governments, and societies. The rise in intelligence comes with a price that is an unprecedented growth in complexity and size of objects, users, interactions, and processes. In particular, there is a growing awareness that the current cyberspace provides only basic support for governance of various entities such as data. There is also a global consensus that protecting privacy requires a more proactive and systematic approach at all levels of design: philosophy, software, hardware, user, and operational. A potential solution for this challenging paradigm is development of adaptive and intelligent approaches that can secure and protect data autonomously. This requires proactive mechanisms and procedures for data collection, sharing, aggregation, and protection in the IoT ecosystem. It also requires effective context-aware algorithms that process data in real-time and enable semantic reasoning for decision making. The objective of this research program is to build such capability to advance privacy, transparency, and trust in the IoT. In particular, we aim to build a new trust framework and a data driven software layer in the IoT architecture that enhance privacy management. These will ensure a more effective mechanism for data and asset ownership governance, access control, and intelligent and real-time intrusion detection and response. This program will train privacy engineers with multidisciplinary skills in the areas of privacy, cybersecurity, and artificial intelligence who will address the shortage of such professionals in Canada.

我们生活的物理和虚拟空间正在变得越来越智能化。在所谓的物联网（IoT）中，我们周围的许多对象都具有一定程度的智能，能够通信，收集，访问和处理信息。这个智能空间是无处不在的访问从任何地方，在任何时候，并由任何人/任何有能力行使访问权限。这种能力取决于组织、政府和社会建立的流程、法规以及安全和隐私实践。智能的提升是以对象、用户、交互和流程的复杂性和规模空前增长为代价的。特别是，人们日益认识到，目前的网络空间仅为数据等各种实体的治理提供基本支持。全球也达成了一个共识，即保护隐私需要在设计的各个层面采取更加积极主动和系统化的方法：理念、软件、硬件、用户和操作。 对于这种具有挑战性的范式，一个潜在的解决方案是开发自适应和智能的方法，可以自动保护和保护数据。这需要在物联网生态系统中建立主动的数据收集、共享、聚合和保护机制和程序。它还需要有效的上下文感知算法来实时处理数据，并为决策提供语义推理。该研究计划的目标是建立这种能力，以提高物联网的隐私，透明度和信任。特别是，我们的目标是在物联网架构中建立一个新的信任框架和一个数据驱动的软件层，以增强隐私管理。这将确保数据和资产所有权治理、访问控制以及智能和实时入侵检测和响应的更有效机制。 该计划将培养在隐私，网络安全和人工智能领域具有多学科技能的隐私工程师，他们将解决加拿大此类专业人员的短缺问题。