Deep learning based energy efficient optimal RMC-CNN model for secured data transmission and anomaly detection in industrial IOT

Sankaran, Kris; Kim, Bong-Hyun

doi:10.1016/j.seta.2022.102983

Cited by 18 publications

(11 citation statements)

References 22 publications

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“…In the industrial IoT, industrial control networks mostly have obvious structural systems, from bottom to top are the on-site control layer network, process control layer network/data acquisition and monitoring layer, and enterprise management layer. As shown in Figure 2, a typical industrial IoT security control network structure is presented [24].…”

Section: Application Of Lightgbm Feature Algorithm Fusion With Multil...mentioning

confidence: 99%

Design of Industrial IoT Intrusion Security Detection System Based on LightGBM Feature Algorithm and Multi-layer Perception Network

Deng

2024

JCSANDM

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Continuous improvement of machine learning technology has provided more support for intrusion security detection in the industrial Internet of Things (IoT). The intrusion security detection system based on LightGBM feature algorithm and multi-layer perception network fusion provides more options for improving security detection, further enhancing the effectiveness of industrial IoT intrusion security detection. By comparing the applications of different models in the security detection process, the model constructed based on the LightGBM feature algorithm can achieve higher accuracy and precision in industrial IoT intrusion security detection, as well as higher F1-score and AUC values; A more reasonable detection time also lays the foundation for improving the overall efficiency of industrial IoT intrusion security detection. Therefore, in the field of industrial IoT intrusion security detection, the detection model constructed in this article can provide more support for further improvement and improvement of IoT intrusion security detection performance.

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Section: Application Of Lightgbm Feature Algorithm Fusion With Multil...mentioning

confidence: 99%

Design of Industrial IoT Intrusion Security Detection System Based on LightGBM Feature Algorithm and Multi-layer Perception Network

Deng

2024

JCSANDM

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“…For the purpose of outlier identification in the IIoT, Sankaran et al [14] suggested a technique for energy-efficient, protected data transfer. The primary goal of this method is to provide an industrial IoT data transfer technique that is both safe and private.…”

Section: Related Workmentioning

confidence: 99%

Design of Mutual Authentication Method for Deep Learning Based Hybrid Cryptography to Secure Data in Cloud Computin

Mohd,

Kummarikunta,

Naga

et al. 2023

IJSSE

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In today's highly competitive environment, it might be difficult to keep sensitive data or information safe. Sharing sensitive information between parties in a cloud environment requires a high level of trust between them. There are numerous methods for achieving data and information security, including cryptography, steganography, etc. This research introduces a new approach to mutual authentication by using a pre-trained model of a convolutional neural network (CNN) to identify malicious activity on the internet. In this research paper, we present a novel approach for enhancing the security of data in cloud computing environments through the design of a mutual authentication method for deep learning-based hybrid cryptography. Our approach combines the strengths of hybrid cryptography and the power of deep learning to provide a robust and adaptable solution for securing data in the cloud. One of the key innovations of our approach is the integration of a pre-trained convolutional neural network (CNN) model. This CNN plays a pivotal role in identifying and mitigating malicious activities on the internet that could pose a threat to cloud-based data. By continuously monitoring network traffic and data patterns, the CNN contributes to the proactive defense mechanism of our system. Secure communication between the involved parties is ensured by combining cryptography with authentication for key agreements. However, no known security method has simultaneously provided a high level of security and a fast execution time. When compared to older encryption systems, hybrid encryption techniques are far superior in terms of providing peace of mind for users. In order to provide robust security, this paper presents hybrid encryption procedures (HEA) by combination of symmetric key (Message Authentication Code [MAC]) and asymmetric key cryptographic procedures (Modified and Enhanced Lattice-Based Cryptography [MELBC]). Results from experiments show that the suggested HEA algorithm offers more security than competing security algorithms.

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“…where, 𝜗 * j − 𝜗 p is represented as the detection speed. Then the context layer with hidden layer equation is given in (11),…”

Section: • Hyb Eesccnn For Classification Processmentioning

confidence: 99%

“…But the performance, like a battery's lifetime, computing resources scarcity and storage, can be limited due to the challenges of mobile devices. Stored data security is another fundamental problem in cloud and mobile computing 11‐13 . The Internet‐based next‐generation computing system is cloud computing which provides the user access to an easy and customizable service with different applications in the cloud.…”

Section: Introductionmentioning

confidence: 99%

“…Stored data security is another fundamental problem in cloud and mobile computing. [11][12][13] The Internet-based next-generation computing system is cloud computing which provides the user access to an easy and customizable service with different applications in the cloud. By connecting cloud applications with the internet, cloud information can be stored and accessed through cloud computing from anywhere.…”

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confidence: 99%

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An efficient and secure key management with the extended convolutional neural network for intrusion detection in cloud storage

Ahmad

Mehfuz

Beg

2023

Concurrency and Computation

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SummaryCloud computing aids users for storing and recovering their information everywhere in the world. Security and efficiency are the two main issues in cloud service. Numerous intrusion detection techniques for the cloud computing environment were proposed, but those techniques do not effectively and accurately detect the attacks. Hence, an efficient and secure key management using extended convolutional neural network, that is, hybrid Enhanced Elman Spike convolutional Neural Network optimized with improved COOT optimization algorithm (Hyb EESCCNN) is proposed for intrusion detection in cloud system. Furthermore, the novel Adaptive Tangent Brakerski‐Gentry Vaikuntanathan Homomorphic Encryption (ATBGVHE) method is proposed for providing the security of the system. At first, SHA‐512 is used for authenticating cloud users to store its own information in to the cloud server. Then for Intrusion Detection (ID) the input data from the NSL‐KDD, UNSWNB15, CICIDS2018, and ToN‐IoT datasets are pre‐processed. The most relevant features are extracted using Fast Independent Component Analysis (Fast ICA) from the pre‐processed output. These extracted data are classified into malicious and non‐malicious data using Hyb EESCCNN. After classification, the non‐malicious data is secured using an ATBGVHE technique. The outcomes of the proposed methods shows that the NSL‐KDD datasets attains 99.9% higher accuracy, UNSW‐NB15 datasets offer 99.89% higher accuracy, CSE‐CIC‐IDS2018 datasets attains 99.8% higher accuracy, ToN‐IoT datasets attains 99.8% higher accuracy and 0.02 s lower encryption time compared with existing methods. Finally, case study with real time applications is also analyzed to prove the efficiency of the proposed method.

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Deep learning based energy efficient optimal RMC-CNN model for secured data transmission and anomaly detection in industrial IOT

Cited by 18 publications

References 22 publications

Design of Industrial IoT Intrusion Security Detection System Based on LightGBM Feature Algorithm and Multi-layer Perception Network

Design of Industrial IoT Intrusion Security Detection System Based on LightGBM Feature Algorithm and Multi-layer Perception Network

Design of Mutual Authentication Method for Deep Learning Based Hybrid Cryptography to Secure Data in Cloud Computin

An efficient and secure key management with the extended convolutional neural network for intrusion detection in cloud storage

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