Deep-Learning-Based Blockchain Framework for Secure Software-Defined Industrial Networks

Singh, Maninderpal; Aujla, Gagangeet Singh; Singh, Amritpal; Kumar, Neeraj; Garg, Sahil

doi:10.1109/tii.2020.2968946

Cited by 62 publications

(22 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Increased decentralisation and interoperability of Industry 4.0 systems lead to increased (cyber-)security risks [22,37,41,43]. Based on our risk assessment, the potential security issues can be classified into two main categories: (i) direct attacks externally and (ii) indirect attacks from internal vulnerable devices.…”

Section: Security and Continuitymentioning

confidence: 99%

Towards design and implementation of Industry 4.0 for food manufacturing

Konur

Lan

Thakker

et al. 2021

Neural Comput & Applic

View full text Add to dashboard Cite

Today’s factories are considered as smart ecosystems with humans, machines and devices interacting with each other for efficient manufacturing of products. Industry 4.0 is a suite of enabler technologies for such smart ecosystems that allow transformation of industrial processes. When implemented, Industry 4.0 technologies have a huge impact on efficiency, productivity and profitability of businesses. The adoption and implementation of Industry 4.0, however, require to overcome a number of practical challenges, in most cases, due to the lack of modernisation and automation in place with traditional manufacturers. This paper presents a first of its kind case study for moving a traditional food manufacturer, still using the machinery more than one hundred years old, a common occurrence for small- and medium-sized businesses, to adopt the Industry 4.0 technologies. The paper reports the challenges we have encountered during the transformation process and in the development stage. The paper also presents a smart production control system that we have developed by utilising AI, machine learning, Internet of things, big data analytics, cyber-physical systems and cloud computing technologies. The system provides novel data collection, information extraction and intelligent monitoring services, enabling improved efficiency and consistency as well as reduced operational cost. The platform has been developed in real-world settings offered by an Innovate UK-funded project and has been integrated into the company’s existing production facilities. In this way, the company has not been required to replace old machinery outright, but rather adapted the existing machinery to an entirely new way of operating. The proposed approach and the lessons outlined can benefit similar food manufacturing industries and other SME industries.

show abstract

Section: Security and Continuitymentioning

confidence: 99%

Towards design and implementation of Industry 4.0 for food manufacturing

Konur

Lan

Thakker

et al. 2021

Neural Comput & Applic

View full text Add to dashboard Cite

show abstract

“…Particularly, the setup has not been tested for DDoS resilience [60]. Similar data transfer at the OF level was reported in [61]. Blockchain networks at application level and device level were added in [62].…”

Section: Blockchain and Smart Contractsmentioning

confidence: 99%

Distributed Denial of Service (DDoS) Mitigation Using Blockchain—A Comprehensive Insight

et al. 2021

View full text Add to dashboard Cite

Distributed Denial of Service (DDoS) attack is a major threat impeding service to legitimate requests on any network. Although the first DDoS attack was reported in 1996, the complexity and sophistication of these attacks has been ever increasing. A 2 TBps attack was reported in mid-August 2020 directed towards critical infrastructure, such as finance, amidst the COVID-19 pandemic. It is estimated that these attacks will double, reaching over 15 million, in the next 2 years. A number of mitigation schemes have been designed and developed since its inception but the increasing complexity demands advanced solutions based on emerging technologies. Blockchain has emerged as a promising and viable technology for DDoS mitigation. The inherent and fundamental characteristics of blockchain such as decentralization, internal and external trustless attitude, immutability, integrity, anonymity and verifiability have proven to be strong candidates, in tackling this deadly cyber threat. This survey discusses different approaches for DDoS mitigation using blockchain in varied domains to date. The paper aims at providing a comprehensive review, highlighting all necessary details, strengths, challenges and limitations of different approaches. It is intended to serve as a single platform to understand the mechanics of current approaches to enhance research and development in the DDoS mitigation domain.

show abstract

“…In [14], the blockchain is also used to secure the communication between the SDN controller and the other network elements against false flow rule injection. In [15], a blockchain mechanism is proposed to protect against unauthorized access and DDoS attack. In this mechanism, the switches are registered and verified using zero proof of knowledge.…”

Section: Related Workmentioning

confidence: 99%

BMC‐SDN: Blockchain‐Based Multicontroller Architecture for Secure Software‐Defined Networks

Derhab

Gabsi

Belaoued

et al. 2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Multicontroller software-defined networks have been widely adopted to enable management of large-scale networks. However, they are vulnerable to several attacks including false data injection, which creates topology inconsistency among controllers. To deal with this issue, we propose BMC-SDN, a security architecture that integrates blockchain and multicontroller SDN and divides the network into several domains. Each SDN domain is managed by one master controller that communicates through blockchain with the masters of the other domains. The master controller creates blocks of network flow updates, and its redundant controllers validate the new block based on a proposed reputation mechanism. The reputation mechanism rates the controllers, i.e., block creator and voters, after each voting operation using constant and combined adaptive fading reputation strategies. The evaluation results demonstrate a fast and optimal detection of fraudulent flow rule injection.

show abstract

Deep-Learning-Based Blockchain Framework for Secure Software-Defined Industrial Networks

Cited by 62 publications

References 22 publications

Towards design and implementation of Industry 4.0 for food manufacturing

Towards design and implementation of Industry 4.0 for food manufacturing

Distributed Denial of Service (DDoS) Mitigation Using Blockchain—A Comprehensive Insight

BMC‐SDN: Blockchain‐Based Multicontroller Architecture for Secure Software‐Defined Networks

Contact Info

Product

Resources

About