Byzantine Resilient Protocol for the IoT

Fröhlich, Antônio Augusto; Scheffel, Roberto Milton; Kozhaya, David; Verı́ssimo, Paulo

doi:10.1109/jiot.2018.2871157

Cited by 19 publications

(9 citation statements)

References 24 publications

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“…The scenarios represent different aspects of Wireless CPS deployment, such as node distances and placements, based on monitoring environments and industry floor. The scenarios are similar to the ones used in other works [16][17][18]. Scenario 1 represents a typical monitoring environment, like a solar field monitoring or a soil moisture irrigation system.…”

Section: Methodsmentioning

confidence: 99%

Modeling Time Requirements of CPS in Wireless Networks

Richa

Lucena

Horstmann

et al. 2020

Sensors

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In this paper, we present an approach to assess the schedulability and scalability of Cyber-Physical Systems (CPS) Networks through an algorithm that is capable of estimating the load of the network as its utility grows. Our approach evaluates both the network load and the laxity of messages, considering its current topology and real-time constraints while abstracting environmental specificities. The proposed algorithm also accounts for the network unreliability by applying a margin-of-safety parameter. This approach enables higher utilities as it evaluates the load of the network considering a margin-of-safety that encapsulates phenomena such as collisions and interference, instead of performing a worst-case analysis. Furthermore, we present an evaluation of the proposed algorithm over three representative scenarios showing that the algorithm was able to successfully assess the network capacity as it reaches a higher use.

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Section: Methodsmentioning

confidence: 99%

Modeling Time Requirements of CPS in Wireless Networks

Richa

Lucena

Horstmann

et al. 2020

Sensors

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“…In a data-driven economy, WSN privacy must be ensured [127]. WSNs must confront these privacy attacks that arise from the spoofing of identity, the examination of traffic and routing data, and attacks on reliability assurance, such as the Byzantine routing data attack and modification attacks [128]. Information reliability in a centralized WSN configuration is challenging in applications where decisions are based on the received information due to possible injection attacks, resulting in information modification, downtime, and information stealing.…”

Section: Security Problems Of Centralized Wsn Modelsmentioning

confidence: 99%

Blockchain-Based Wireless Sensor Networks for Malicious Node Detection: A Survey

et al. 2021

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Wireless Sensor Networks (WSNs) are broadly applied for various applications in tracking and surveillance due to their ease of use and other distinctive characteristics compelled by real-time cooperation among the sensor nodes. In WSNs, security is becoming a critical issue, as the techniques for malicious node detection adopt a one-time, centralized decision-making approach. With this paradigm, errors are difficult to avoid, and reproducibility and traceability are challenging. Hence, malicious node discovery technologies in conventional WSNs cannot assure traceability and fairness of the detection method. Herein, this paper discusses an in-depth survey of a blockchain-based approach for malicious node detection, an exhaustive examination of the integration of blockchain techniques with WSNs (BWSN), and insights into this novel concept. This survey discusses the architecture, sector-wise applications, and uses of BWSN. Moreover, this survey describes malicious node detection based on BWSN in two parts: 1) the BWSN architecture for detecting the malicious nodes and 2) the smart contract aspects in malicious node detection. Next, this survey explains the contributions of blockchain for WSN data management, which involves online information aggregation and may include auditing, event logs, and storage for information analysis and offline query processing. This survey first presents the conventional WSN solutions then the blockchain-based WSN solutions for data management. Additionally, this survey discusses the contributions of blockchain for WSN security management. It first examines the centralized WSN models for security problems, followed by a discussion of the blockchain-based WSN solutions for security management, such as offering access control, preserving information integrity, guaranteeing privacy, and ensuring WSNs' node longevity.

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“…The Fault-Tolerant Trustful Space-Time Protocol (FT -TSTP) (Fröhlich et al 2019;Scheffel and Fröhlich 2018a) transports data from devices (e.g. sensors, actuators, machines) to multiple gateways connected to an IT infrastructure.…”

Section: Ft-tstpmentioning

confidence: 99%

Automated fault detection for additive manufacturing using vibration sensors

Scheffel

Fröhlich

Silvestri

2021

International Journal of Computer Integrated Manufacturing

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Online process control is a crucial task in modern production systems that use digital twin technology. The data acquisition from machines must provide reliable and on-the-fly data, reflecting the exact status of the ongoing process. This work presents an architecture to acquire data for an Additive Manufacturing (3D printer) process, using a set of consolidated Internet of Things (IoT) technologies to collect, verify and store these data in a trustful and secure way. The need for online monitoring and fault detection is addressed by the development of a classifier using Convolutional Neural Networks. This deep learning approach, using temporally aligned vibration data provided by the underlying architecture, allows raw data processing to detect patterns without signal preprocessing and without domain-specific knowledge for model building.

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Byzantine Resilient Protocol for the IoT

Cited by 19 publications

References 24 publications

Modeling Time Requirements of CPS in Wireless Networks

Modeling Time Requirements of CPS in Wireless Networks

Blockchain-Based Wireless Sensor Networks for Malicious Node Detection: A Survey

Automated fault detection for additive manufacturing using vibration sensors

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