On the Feasibility of Secure Logging for Industrial Control Systems Using Blockchain

Schorradt, Stefan; Bajramovic, Edita; Freiling, Felix C.

doi:10.1145/3360664.3360668

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…Although audit logs help track changes made and ensure correctness in the system, they are vulnerable to a series of attacks that may compromise the system's integrity [3]. Secure logging means that all entries in the log must have a corresponding event that happened, and all events that occurred must have a corresponding log entry [45]. Although blockchain stems from cryptocurrency, many studies have investigated the adoption of blockchain in different application scenarios beyond the financial domain.…”

Section: Using Blockchain To Provide Auditing Capabilitiesmentioning

confidence: 99%

“…Schorradt et al [45] elaborate that blockchain technology offers three security characteristics that make it a secure logging protocol. Firstly, it provides integrity protection via signatures.…”

Section: Using Blockchain To Provide Auditing Capabilitiesmentioning

confidence: 99%

“…They claimed that their design could be adapted to any Blockchain framework with the help of an intermediary. Schorradt et al [45] focused on using blockchain to enable secure logging in industrial control systems. They connected the Syslog functionality of a programmable logic controller to the public Ethereum blockchain network.…”

Section: Using Blockchain To Provide Auditing Capabilitiesmentioning

confidence: 99%

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A Framework for Secure Logging in Precision Healthcare Cloud-based Services

Moghaddam

Iqbal

Traoré

2021

2021 IEEE International Conference on Digital Health (ICDH)

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Precision medicine is an emerging approach for disease treatment and prevention that delivers personalized care to individual patients by considering their genetic makeups, medical histories, environments, and lifestyles. Despite the rapid advancement of precision medicine and its considerable promise, several underlying technological challenges remain unsolved. One such challenge of great importance is the security and privacy of precision health-related data, such as genomic data and electronic health records, which stifle collaboration and hamper the full potential of machine-learning (ML) algorithms. To preserve data privacy while providing ML solutions, this thesis explores the feasibility of machine learning with encryption for precision healthcare datasets. Moreover, to ensure audit logs' integrity, we introduce a blockchain-based secure logging architecture for precision healthcare transactions. We consider a scenario that lets us send sensitive healthcare data into the cloud while preserving privacy by using homomorphic encryption and develop a secure logging framework for this precision healthcare service using Hyperledger Fabric. We test the architecture by generating a considerable volume of logs and show that our system is tamper-resistant and can ensure integrity.

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Section: Using Blockchain To Provide Auditing Capabilitiesmentioning

confidence: 99%

Section: Using Blockchain To Provide Auditing Capabilitiesmentioning

confidence: 99%

Section: Using Blockchain To Provide Auditing Capabilitiesmentioning

confidence: 99%

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A Framework for Secure Logging in Precision Healthcare Cloud-based Services

Moghaddam

Iqbal

Traoré

2021

2021 IEEE International Conference on Digital Health (ICDH)

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“…Schorradt et al [11] proposed a prototype implementation of blockchain-based logging system for ICSs. The authors argue that blockchain immutability and auditability makes it attractive to address security challenges in ICS logging systems.…”

Section: Blockchain In Log Managementmentioning

confidence: 99%

“…The authors employed hyperledger as the underlying blockchain technology and demonstrated the blockchain applicability and feasibility of storing log information in blockchain. Similarly, Schorradt et al [11] studied the feasibility of using blockchain to store logging information for ICSs. The experiment shows that blockchain can potentially serve as a logging infrastructure for ICSs.…”

Section: Introductionmentioning

confidence: 99%

Securing Manufacturing Using Blockchain

Jadidi¹,

Dorri²,

Jurdak³

et al. 2020

Preprint

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Due to the rise of Industrial Control Systems (ICSs) cyberattacks in the recent decade, various security frameworks have been designed for anomaly detection. While advanced ICS attacks use sequential phases to launch their final attacks, existing anomaly detection methods can only monitor a single source of data. Therefore, analysis of multiple security data can provide comprehensive and system-wide anomaly detection in industrial networks. In this paper, we propose an anomaly detection framework for ICSs that consists of two stages: i) blockchain-based log management where the logs of ICS devices are collected in a secure and distributed manner, and ii) multi-source anomaly detection where the blockchain logs are analysed using multi-source deep learning which in turn provides a system wide anomaly detection method. We validated our framework using two ICS datasets: a factory automation dataset and a Secure Water Treatment (SWAT) dataset. These datasets contain physical and network level normal and abnormal traffic. The performance of our new framework is compared with single-source machine learning methods. The precision of our framework is 95% which is comparable with single-source anomaly detectors.

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