The broadly configured smart city network requires a variety of security considerations for a heterogeneous device environment. Because a network of heterogeneous devices facilitates an attacker’s intrusion through a specific device or node, a device management framework is required to manage each node comprehensively. This paper proposes a blockchain-based device management framework for efficient device management, scalable firmware update and resiliences on attacks against smart city network. This framework offers four device management and firmware update mechanisms based on the performance and requirements of each device: bidirectional mechanism of general end node and a unidirectional mechanism of the lightweight end node. This difference optimizes the resource of network and devices in terms of management and security. All management history of each device is stored in the blockchain and transmitting firmware between vendor and management node is conducted through a smart contract of blockchain for security and resilience on the attack. Through the framework proposed in this paper, the confidentiality and availability of device management on smart city network as well as integrity, auditability, adaptability and authentication for each node are ensured and the effectiveness of the proposed framework is presented through the security analysis.
The convergence of fifth-generation (5G) communication and the Internet-of-Things (IoT) has dramatically increased the diversity and complexity of the network. This change diversifies the attacker’s attack vectors, increasing the impact and damage of cyber threats. Cyber threat intelligence (CTI) technology is a proof-based security system which responds to these advanced cyber threats proactively by analyzing and sharing security-related data. However, the performance of CTI systems can be significantly compromised by creating and disseminating improper security policies if an attacker intentionally injects malicious data into the system. In this paper, we propose a blockchain-based CTI framework that improves confidence in the source and content of the data and can quickly detect and eliminate inaccurate data for resistance to a Sybil attack. The proposed framework collects CTI by a procedure validated through smart contracts and stores information about the metainformation of data in a blockchain network. The proposed system ensures the validity and reliability of CTI data by ensuring traceability to the data source and proposes a system model that can efficiently operate and manage CTI data in compliance with the de facto standard. We present the simulation results to prove the effectiveness and Sybil-resistance of the proposed framework in terms of reliability and cost to attackers.
Advanced information technologies have transformed into high-level services for more efficient use of energy resources through the fusion with the energy infrastructure. As a part of these technologies, the energy cloud is a technology that maximizes the efficiency of energy resources through the organic connection between the entities that produce and consume the energy. However, the disruption or destruction of energy cloud systems through cyberattacks can lead to incidents such as massive blackouts, which can lead to national disasters. Furthermore, since the technique and severity of modern cyberattacks continue to improve, the energy cloud environment must be designed to resist cyberattacks. However, since the energy cloud environment has different characteristics from general infrastructures such as the smart grid and the Advanced Metering Infrastructure (AMI), it requires security technology specialized to its environment. This paper proposes a cyber threat intelligence framework to improve the energy cloud environment’s security. Cyber Threat Intelligence (CTI) is a technology to actively respond to advanced cyber threats by collecting and analyzing various threat indicators and generating contextual knowledge about the cyber threats. The framework proposed in this paper analyzes threat indicators that can be collected in the advanced metering infrastructure and proposes a cyber threat intelligence generation technique targeting the energy cloud. This paper also proposes a method that can quickly apply a security model to a large-scale energy cloud infrastructure through a mechanism for sharing and spreading cyber threat intelligence between the AMI layer and the cloud layer. Our framework provides a way to effectively apply the proposed technologies through the CTI architecture, including the local AMI layer, the station layer, and the cloud layer. Furthermore, we show that the proposed framework can effectively respond to cyber threats by showing a 0.822 macro-F1 score and a 0.843 micro-F1 score for cyberattack detection in an environment that simulates a model of an attacker and an energy cloud environment.
The service-based architecture of the Fifth Generation(5G) had combined the services and security architectures and enhanced the authentication process of services to expand the coverage of the network, including heterogeneous devices. This architecture uses the secondary authentication for mutual authentication between the User Equipment (UE) and the Data Network (DN) to authenticate devices and services. However, this authentication mechanism can cause a signaling storm in the Non-Access Stratum (NAS) because the end node needs to communicate with the authentication server of the NAS area. This problem could affect the availability of the network when the network is extended. This research proposes a mutual authentication framework that can efficiently perform a mutual authentication process through secondary authentication between UE and DN. The proposed framework uses newly devised network functions: Secondary Authentication Function (SAF) and the Authentication Data Management Function (ADMF). This framework proposes a methodology at the protocol level for efficient mutual authentication using the mobile edge computing architecture. We analyzed the proposed framework in the point of security considerations, and we evaluated the effect of the framework on the traffic of the NAS layer and user experience. Our simulation results show that the proposed framework can reduce the NAS traffic by 39% and total traffic of the overall network by 10%.
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