اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدBlockchain-based Security Framework for Critical Industry 4.0 Cyber-physical System
119
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
There has been an intense concern for security alternatives because of the recent rise of cyber attacks, mainly targeting critical systems such as industry, medical, or energy ecosystem. Though the latest industry infrastructures largely depend on AI-driven maintenance, the prediction based on corrupted data undoubtedly results in loss of life and capital. Admittedly, an inadequate data-protection mechanism can readily challenge the security and reliability of the network. The shortcomings of the conventional cloud or trusted certificate-driven techniques have motivated us to exhibit a unique Blockchain-based framework for a secure and efficient industry 4.0 system. The demonstrated framework obviates the long-established certificate authority after enhancing the consortium Blockchain that reduces the data processing delay, and increases cost-effective throughput. Nonetheless, the distributed industry 4.0 security model entails cooperative trust than depending on a single party, which in essence indulges the costs and threat of the single point of failure. Therefore, multi-signature technique of the proposed framework accomplishes the multi-party authentication, which confirms its applicability for the real-time and collaborative cyber-physical system.
قيم البحث
اقرأ أيضاً
The proliferation of digitization and complexity of connectivity in Cyber-Physical Systems (CPSs) calls for a mechanism that can evaluate the functionality and security of critical infrastructures. In this regard, Digital Twins (DTs) are revolutioniz
ing the CPSs. Driven by asset-centric data, DTs are virtual replicas of physical systems that mirror every facet of a product or process and can provide actionable insights through monitoring, optimization, and prediction. Furthermore, replication and simulation modes in DTs can prevent and detect security flaws in the CPS without obstructing the ongoing operations of the live system. However, such benefits of DTs are based on an assumption about data trust, integrity, and security. Data trustworthiness is considered to be more critical when it comes to the integration and interoperability of multiple components or sub-components among different DTs owned by multiple stakeholders to provide an aggregated view of the complex physical system. Moreover, analyzing the huge volume of data for creating actionable insights in real-time is another critical requirement that demands automation. This article focuses on securing CPSs by integrating Artificial Intelligence (AI) and blockchain for intelligent and trusted DTs. We envision an AI-aided blockchain-based DT framework that can ensure anomaly prevention and detection in addition to responding against novel attack vectors in parallel with the normal ongoing operations of the live systems. We discuss the applicability of the proposed framework for the automotive industry as a CPS use case. Finally, we identify challenges that impede the implementation of intelligence-driven architectures in CPS.
The salient features of blockchain, such as decentralisation and transparency, have allowed the development of Decentralised Trust and Reputation Management Systems (DTRMS), which mainly aim to quantitatively assess the trustworthiness of the network
participants and help to protect the network from adversaries. In the literature, proposals of DTRMS have been applied to various Cyber-physical Systems (CPS) applications, including supply chains, smart cities and distributed energy trading. In this chapter, we outline the building blocks of a generic DTRMS and discuss how it can benefit from blockchain. To highlight the significance of DTRMS, we present the state-of-the-art of DTRMS in various field of CPS applications. In addition, we also outline challenges and future directions in developing DTRMS for CPS.
As the industrial cyber-infrastructure become increasingly important to realise the objectives of Industry~4.0, the consequence of disruption due to internal or external faults become increasingly severe. Thus there is a need for a resilient infrastr
ucture. In this paper, we propose a contract-based methodology where components across layers of the cyber-infrastructure are associated with contracts and a light-weight resilience manager. This allows the system to detect faults (contract violation monitored using observers) and react (change contracts dynamically) effectively.
We introduce deceptive signaling framework as a new defense measure against advanced adversaries in cyber-physical systems. In general, adversaries look for system-related information, e.g., the underlying state of the system, in order to learn the s
ystem dynamics and to receive useful feedback regarding the success/failure of their actions so as to carry out their malicious task. To this end, we craft the information that is accessible to adversaries strategically in order to control their actions in a way that will benefit the system, indirectly and without any explicit enforcement. Under the solution concept of game-theoretic hierarchical equilibrium, we arrive at a semi-definite programming problem equivalent to the infinite-dimensional optimization problem faced by the defender while selecting the best strategy when the information of interest is Gaussian and both sides have quadratic cost functions. The equivalence result holds also for the scenarios where the defender can have partial or noisy measurements or the objective of the adversary is not known. We show the optimality of linear signaling rule within the general class of measurable policies in communication scenarios and also compute the optimal linear signaling rule in control scenarios.
Fog computing is a paradigm for distributed computing that enables sharing of resources such as computing, storage and network services. Unlike cloud computing, fog computing platforms primarily support {em non-functional properties} such as location
awareness, mobility and reduced latency. This emerging paradigm has many potential applications in domains such as smart grids, smart cities, and transport management. Most of these domains collect and monitor personal information through edge devices to offer personalized services. A {em centralized} server either at the level of cloud or fog, has been found ineffective to provide a high degree of security and privacy-preserving services. Blockchain technology supports the development of {em decentralized} applications designed around the principles of immutability, cryptography, consistency preserving consensus protocols and smart contracts. Hence blockchain technology has emerged as a preferred technology in recent times to build trustworthy distributed applications. The chapter describes the potential of blockchain technology to realize security services such as authentication, secured communication, availability, privacy and trust management to support the development of dependable fog services.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
