The Internet of Things (IoT) revolution is reshaping how physical devices embedded with software connect to the Internet, facilitating seamless data exchange and driving automation. Industrial IoT (IIoT) extends these capabilities to industrial devices and Cyber-Physical Systems (CPS), driving Intelligent Manufacturing. This integration supports advanced applications like remote monitoring, predictive maintenance, machine learning (ML), and artificial intelligence (AI) optimization, enhancing production efficiency, adaptability, and decisionmaking. However, managing the vast amounts of data generated requires scalable, automated software architectures. Many small and medium-sized enterprises (SME) face challenges in building such systems due to limited resources and expertise, often starting with manual data collection and basic automation.This paper presents a solution: a fully automated, configurable, and scalable software architecture for Intelligent Manufacturing. Our system has been operational for almost one and a half years on 21 plants, processing about 17K tasks, amounting to more than three months of computations. The experimental results show that automation and elasticity have been needed by such systems since the beginning, while scalability is not required during an initial experimentation phase.

Sound static analysis allows one to overapproximate all possible program executions to infer various properties. However, it requires quite some effort to formalize and prove the soundness of program semantics. Most software applications developed nowadays are distributed systems in which different [micro]services communicate through synchronous and asynchronous mechanisms. These applications are composed of programs developed in many programming languages and rely on many technologies. However, sound static analysis might be particularly promising in distributed architectures, where exhaustively (or even partially) testing such systems is often prohibitive. This paper presents our ongoing work on applying LiSA (Library for Static Analysis) to microservices. So far, our effort has focused on one programming language (Python), a few libraries (ROS2, pika, FastAPI, Django), and the architectural reconstruction of distributed applications. However, it already shows some promising results and general patterns that might be followed to develop such analyses.

Cybersecurity in mission-critical robotic applications is a necessity to scale deployments securely. ROS2 builds upon DDS-Security specs in ROS Client Library (RCL) to implement its security features. Utilizing SROS2, developers have access to a set of utilities to help set up security in a way RCL can use. Through SROS2, security deployment is eased for developers. However, while access control is handled by DDS and consequently based on the SROS2-generated permission artifacts, the necessary authorization policies are manually generated by developers. This requires an entire system exercise to be sampled via live extraction and, per each node, list all the necessary Topics, Services, and Actions, which is a daunting and laborious process. Developers first have to generate tests. Then, they obtain a ’snapshot’ of the system for each test. Later, these snapshots must be collected and grouped into a policy by a minimum set of rules. All this procedure is quite error-prone. This paper introduces LiSA4ROS2, a tool for automatically extract the ROS2 computational graph via static analysis to derive a minimal correct configuration for ROS2 security policies. Our approach relies on the abstract interpretation theory to statically overapproximate all possible executions to extract a minimal and complete configuration per node. We evaluate our approach with minimal examples covering all the main communication patterns in ROS2 tutorials and all publicly available real-world ROS2 Python systems extracted from GitHub. The results of the minimal examples show that LiSA4ROS2 precisely supports all the main communication patterns. The extensive evaluation underlines that our prototype implementation of the analysis in LiSA4ROS2 is already able to precisely analyze 66% of existing repositories, automatically producing detailed computational graphs and access policies. All the results of the analysis, as well as a Docker artifact to reproduce them, are publicly available.

Robot Operating System 2 (ROS 2) is the de-facto standard framework for developing distributed robotic applications. However, ensuring the correctness and security of these applications remains a significant challenge. This paper presents a novel approach to statically analyze ROS 2 applications using abstract interpretation. By extracting the architecture graph of the application, our method derives minimal access control policies that can be used to leverage security. We implemented our approach using the Library for Static Analysis (LiSA), providing a toolset that facilitates the development of sound static analyzers for ROS 2. The results demonstrate the effectiveness of our approach in enhancing the security of ROS 2 applications.

ROS 2 is rapidly becoming a standard in the robotics industry. Built upon DDS as its default communication middleware and used in safety-critical scenarios, adding secu-rity to robots and ROS computational graphs is increasingly becoming a concern. The present work introduces SROS2, a series of developer tools and libraries that facilitate adding security to ROS 2 graphs. Focusing on a usability-centric approach in SROS2, we present a methodology for securing graphs systematically while following the DevSecOps model. We also demonstrate the use of our security tools by presenting an application case study that considers securing a graph using the popular Navigation2 and SLAM Toolbox stacks applied in a TurtieBot3 robot. We analyse the current capabilities of SROS2 and discuss the shortcomings, which provides insights for future contributions and extensions. Ultimately, we present SROS2 as usable security tools for ROS 2 and argue that without usability, security in robotics will be greatly impaired.

Security of robotics systems, as well as of the related middleware infrastructures, is a critical issue for industrial and domestic IoT, and it needs to be continuously assessed throughout the whole development lifecycle. The next generation open source robotic software stack, ROS2, is now targeting support for Secure DDS, providing the community with valuable tools for secure real world robotic deployments. In this work, we introduce a framework for procedural provisioning access control policies for robotic software, as well as for verifying the compliance of generated transport artifacts and decision point implementations.