Blockchain-Based Cyber Threat Intelligence System Architecture for Sustainable Computing

Abstract

Nowadays, the designing of cyber-physical systems has a significant role and plays a substantial part in developing a sustainable computing ecosystem for secure and scalable network architecture. The introduction of Cyber Threat Intelligence (CTI) has emerged as a new security system to mitigate existing cyber terrorism for advanced applications. CTI demands a lot of requirements at every step. In particular, data collection is a critical source of information for analysis and sharing; it is highly dependent on the reliability of the data. Although many feeds provide information on threats recently, it is essential to collect reliable data, as the data may be of unknown origin and provide information on unverified threats. Additionally, effective resource management needs to be put in place due to the large volume and diversity of the data. In this paper, we propose a blockchain-based cyber threat intelligence system architecture for sustainable computing in order to address issues such as reliability, privacy, scalability, and sustainability. The proposed system model can cooperate with multiple feeds that collect CTI data, create a reliable dataset, reduce network load, and measure organizations’ contributions to motivate participation. To assess the proposed model’s effectiveness, we perform the experimental analysis, taking into account various measures, including reliability, privacy, scalability, and sustainability. Experimental results of evaluation using the IP of 10 open source intelligence (OSINT) CTI feeds show that the proposed model saves about 15% of storage space compared to total network resources in a limited test environment.

Decentralized Actionable Cyber Threat Intelligence for Networks and the Internet of Things

“…Literature shows different approaches to the existing gaps in CTI sharing. Blockchain technologies were proposed as a sustainable computing architecture to share computing power for efficiency [23]. Blockchains were also leveraged to address the trust and quality issue to engage participation in CTI contribution [35].…”

“…To better leverage IoT CTI, it is best that the secure methods do not assume central trust while offering equal access and quick propagation and action. A blockchain network is a great candidate for such secure methods, as shown by Cha et al [23]. They proposed a blockchain-based CTI system architecture for sustainable computing and used a blockchain network to provide sensitive data sharing.…”

Machine learning based distributed big data analysis framework for next generation web in IoT

“…Table 3 shows big data analysis methods and IoT applications via machine learning methods such as classification, clustering, association rule, prediction, and time series [45][46][47]. Proposed ELM methods are used in maximum IoT applications such as social networking, bioinformatics, smart energy, smart home, e-government, and others compare to other machine learning methods [48][49][50][51][52]. ELM based framework on the cloud layer provides excellent performance at a high data rate.…”

Security Information Sharing in Smart Grids: Persisting Security Audits to the Blockchain

“…In this sense, it is worth noting current efforts in organizations as the International Association of Trusted Blockchain [28] or the European Telecommunications Standards Institute (ETSI) [29] to align efforts in pursuing standard data models and procedures for a broad set of application contexts, including the energy sector. Regarding incident management, standardization is crucial to ease the sharing, traceability, and trust evaluation of cyber threat intelligence sources [30]. Provenance evaluation is also critical for the identification of threats associated with inadequate software and firmware updates in the ecosystems of smart and micro grids.…”