An Adaptable and Unsupervised TinyML Anomaly Detection System for Extreme Industrial Environments

Industrial assets often feature multiple sensing devices to keep track of their status by monitoring certain physical parameters. These readings can be analyzed with machine learning (ML) tools to identify potential failures through anomaly detection, allowing operators to take appropriate corrective actions. Typically, these analyses are conducted on servers located in data centers or the cloud. However, this approach increases system complexity and is susceptible to failure in cases where connectivity is unavailable. Furthermore, this communication restriction limits the approach’s applicability in extreme industrial environments where operating conditions affect communication and access to the system. This paper proposes and evaluates an end-to-end adaptable and configurable anomaly detection system that uses the Internet of Things (IoT), edge computing, and Tiny-MLOps methodologies in an extreme industrial environment such as submersible pumps. The system runs on an IoT sensing Kit, based on an ESP32 microcontroller and MicroPython firmware, located near the data source. The processing pipeline on the sensing device collects data, trains an anomaly detection model, and alerts an external gateway in the event of an anomaly. The anomaly detection model uses the isolation forest algorithm, which can be trained on the microcontroller in just 1.2 to 6.4 s and detect an anomaly in less than 16 milliseconds with an ensemble of 50 trees and 80 KB of RAM. Additionally, the system employs blockchain technology to provide a transparent and irrefutable repository of anomalies

Demand-supply matching through auctioning for the circular economy

The circular economy aims to reduce the consumption of resources and energy by exploiting multiple use-cycles of components and materials. The creation of new circular businesses hinges on efficient alignment between market demands of circular products with the supply of End-of-life components and materials. In this paper, we address the digitization of a matchmaking tool for the circular economy by defining demand-supply matching (DSM) in context of business link identification and cross-sectorial matchmaking. We further specify a DSM process and p resent our DSM tool, which facilitates publication and search for supplier offerings and demander needs, selection of auctioning candidates, and digitized auctioning and contract definition. By that, this tool supports the alignment of market demands with matching supply offerings. In particular, it combines the steps of publishing, searching, selecting, auctioning and contract definition into one tool, which we argue can make matchmaking more efficient compared to addressing these steps separately. Finally, we present the design of the tool and discuss its merits in light of the needed acceptance for automating business link identification and contractual interactions

MARTSIA: Enabling Data Confidentiality for Blockchain-based Process Execution

Multi-party business processes rely on the collaboration of various players in a decentralized setting. Blockchain technology can facilitate the automation of these processes, even in cases where trust among participants is limited. Transactions are stored in a ledger, a replica of which is retained by every node of the blockchain network. The operations saved thereby are thus publicly accessible. While this enhances transparency, reliability, and persistence, it hinders the utilization of public blockchains for process automation as it violates typical confidentiality requirements in corporate settings. In this paper, we propose MARTSIA: A Multi-Authority Approach to Transaction Systems for Interoperating Applications. MARTSIA enables precise control over process data at the level of message parts. Based on Multi-Authority Attribute-Based Encryption (MA-ABE), MARTSIA realizes a number of desirable properties, including confidentiality, transparency, and auditability. We implemented our approach in proof-of-concept prototypes, with which we conduct a case study in the area of supply chain management. Also, we show the integration of MARTSIA with a state-of-the-art blockchain-based process execution engine to secure the data flow

FaaS: Federation-as-a-Service

This document is the main high-level architecture specification of the SUNFISH cloud federation solution. Its main objective is to introduce the concept of Federation-as-a-Service (FaaS) and the SUNFISH platform. FaaS is the new and innovative cloud federation service proposed by the SUNFISH project. The document defines the functionalities of FaaS, its governance and precise objectives. With respect to these objectives, the document proposes the high-level architecture of the SUNFISH platform: the software architecture that permits realising a FaaS federation. More specifically, the document describes all the components forming the platform, the offered functionalities and their high-level interactions underlying the main FaaS functionalities. The document concludes by outlining the main implementation strategies towards the actual implementation of the proposed cloud federation solution.Comment: Technical Report Edited by Francesco Paolo Schiavo, Vladimiro Sassone, Luca Nicoletti and Andrea Margher

Enabling Data Confidentiality with Public Blockchains

Blockchain technology is apt to facilitate the automation of multi-party cooperations among various players in a decentralized setting, especially in cases where trust among participants is limited. Transactions are stored in a ledger, a replica of which is retained by every node of the blockchain network. The operations saved thereby are thus publicly accessible. While this aspect enhances transparency, reliability, and persistence, it hinders the utilization of public blockchains for process automation as it violates typical confidentiality requirements in corporate settings. To overcome this issue, we propose our approach named Multi-Authority Approach to Transaction Systems for Interoperating Applications (MARTSIA). Based on Multi-Authority Attribute-Based Encryption (MA-ABE), MARTSIA enables read-access control over shared data at the level of message parts. User-defined policies determine whether an actor can interpret the publicly stored information or not, depending on the actor's attributes declared by a consortium of certifiers. Still, all nodes in the blockchain network can attest to the publication of the (encrypted) data. We provide a formal analysis of the security guarantees of MARTSIA, and illustrate the proof-of-concept implementation over multiple blockchain platforms. To demonstrate its interoperability, we showcase its usage in ensemble with a state-of-the-art blockchain-based engine for multi-party process execution, and three real-world decentralized applications in the context of NFT markets, supply chain, and retail.Comment: arXiv admin note: substantial text overlap with arXiv:2303.1797

FaaS: Federation-as-a-Service

This document is the main high-level architecture specification of the SUNFISH cloud federation solution. Its main objective is to introduce the concept of Federation-as-a-Service (FaaS) and the SUNFISH platform. FaaS is the new and innovative cloud federation service proposed by the SUNFISH project. The document defines the functionalities of FaaS, its governance and precise objectives. With respect to these objectives, the document proposes the high-level architecture of the SUNFISH platform: the software architecture that permits realising a FaaS federation. More specifically, the document describes all the components forming the platform, the offered functionalities and their high-level interactions underlying the main FaaS functionalities. The document concludes by outlining the main implementation strategies towards the actual implementation of the proposed cloud federation solution

Cybersecurity issues in software architectures for innovative services

The recent advances in data center development have been at the basis of the widespread success of the cloud computing paradigm, which is at the basis of models for software based applications and services, which is the "Everything as a Service" (XaaS) model. According to the XaaS model, service of any kind are deployed on demand as cloud based applications, with a great degree of flexibility and a limited need for investments in dedicated hardware and or software components. This approach opens up a lot of opportunities, for instance providing access to complex and widely distributed applications, whose cost and complexity represented in the past a significant entry barrier, also to small or emerging businesses. Unfortunately, networking is now embedded in every service and application, raising several cybersecurity issues related to corruption and leakage of data, unauthorized access, etc. However, new service-oriented architectures are emerging in this context, the so-called services enabler architecture. The aim of these architectures is not only to expose and give the resources to these types of services, but it is also to validate them. The validation includes numerous aspects, from the legal to the infrastructural ones e.g., but above all the cybersecurity threats. A solid threat analysis of the aforementioned architecture is therefore necessary, and this is the main goal of this thesis. This work investigate the security threats of the emerging service enabler architectures, providing proof of concepts for these issues and the solutions too, based on several use-cases implemented in real world scenarios