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  1. The Internet of Things (IoT) is a vast collection of interconnected sensors, devices, and services that share data and information over the Internet with the objective of leveraging multiple information sources to optimize related systems. The technologies associated with the IoT have significantly improved the quality of many existing applications by reducing costs, improving functionality, increasing access to resources, and enhancing automation. The adoption of IoT by industries has led to the next industrial revolution: Industry 4.0. The rise of the Industrial IoT (IIoT) promises to enhance factory management, process optimization, worker safety, and more. However, the rollout of the IIoT is not without significant issues, and many of these act as major barriers that prevent fully achieving the vision of Industry 4.0. One major area of concern is the security and privacy of the massive datasets that are captured and stored, which may leak information about intellectual property, trade secrets, and other competitive knowledge. As a way forward toward solving security and privacy concerns, we aim in this paper to identify common input-output (I/O) design patterns that exist in applications of the IIoT. These design patterns enable constructing an abstract model representation of data flow semantics used by such applications, and therefore better understand how to secure the information related to IIoT operations. In this paper, we describe communication protocols and identify common I/O design patterns for IIoT applications with an emphasis on data flow in edge devices, which, in the industrial control system (ICS) setting, are most often involved in process control or monitoring. 
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  2. The Internet of Things (IoT) offers immense benefits by enabling devices to leverage networked resources thereby making intelligent decisions. The numerous heterogeneous connected devices that exist throughout the IoT system creates new security and privacy concerns. Some of these concerns can be overcome through trust, transparency, and integrity, which can be achieved with data provenance. Data provenance, also known as data lineage, provides a history of transformations that occurs on a data object from the time it was created to its current state. Data provenance has been explored in the areas of scientific computing, business, forensic analysis, and intrusion detection. Data provenance can help in detecting and mitigating malicious cyber attacks. In this paper, we explore the integration of provenance within the IoT. We introduce Provenance Aware Internet of Things System (PAIoTS), a provenance collection framework for IoT devices. We evaluate the effectiveness of our framework by developing a prototype system for proof of concept. 
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