Industrial IoT (IIoT) is a novel concept of a fully connected, transparent, automated, and intelligent factory setup improving manufacturing processes and efficiency. To achieve this, existing hierarchical models must transition to a fully connected vertical model. Since IIoT is a novel approach, the environment is susceptible to cyber threat vectors, standardization, and interoperability issues, bridging the gaps at the IT/OT ICS (industrial control systems) level. IIoT M2M communication relies on new communication models (5G, TSN ethernet, self-driving networks, etc.) and technologies which require challenging approaches to achieve the desired levels of data security. Currently there are no methods to assess the vulnerabilities/risk impact which may be exploited by malicious actors through system gaps left due to improper implementation of security standards. The authors are currently working on an Industry 4.0 cybersecurity project and the insights provided in this paper are derived from the project. This research enables an understanding of converged/hybrid cybersecurity standards, reviews the best practices, and provides a roadmap for identifying, aligning, mapping, converging, and implementing the right cybersecurity standards and strategies for securing M2M communications in the IIoT.
Industry 5.0 is projected to be an exemplary improvement in digital transformation allowing for mass customization and production efficiencies using emerging technologies such as universal machines, autonomous and self-driving robots, self-healing networks, cloud data analytics, etc., to supersede the limitations of Industry 4.0. To successfully pave the way for acceptance of these technologies, we must be bound and adhere to ethical and regulatory standards. Presently, with ethical standards still under development, and each region following a different set of standards and policies, the complexity of being compliant increases. Having vague and inconsistent ethical guidelines leaves potential gray areas leading to privacy, ethical, and data breaches that must be resolved. This paper examines the ethical dimensions and dilemmas associated with emerging technologies and provides potential methods to mitigate their legal/regulatory issues.
The Hybrid Cloud Computing model has been growing extensively due to its Infrastructure as a Service (IaaS) architecture, customisation and cost benefits. The hybrid cloud services are measured based on the Quality of Service parameters defined by the public cloud vendors. These parameters (i.e. availability, scalability, latency etc.) vary from vendor-to-vendor, developing complexity and confusion on the grounds of methods of service assessments. A Cloud Service Level Agreement (SLA) lists the QoS provisions to be provided to the tenant, the objectives, and exclusions. Regardless of vendors promised uptimes and service metrics, the tenants are susceptible to the following threats: data governance, Denial of Services, multi-tenancy, etc. Cloud computing has often been compared as a utility, but the basic different between a utility and the cloud is the amount of risk involved with data protection, provisioning and control. Few cloud standards have been developed for standardizing the hybrid cloud model but since each public cloud vendor provides different applications and services, these standards do not resolve the existing cloud QoS issue. Since each enterprise implementing the cloud and vendor supplying the services is diverse, a customized Trio (Cloud-IT-Business) QoS model is required to resolve the business need. The authors have designed a model to resolve this existing cloud QoS issue, the abstraction of the model is detailed in this paper.
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