4.5 Article

Training fuzzy deep neural network with honey badger algorithm for intrusion detection in cloud environment

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

An Emerging Fuzzy Feature Selection Method Using Composite Entropy-Based Uncertainty Measure and Data Distribution

Weihua Xu et al.

Summary: This paper introduces a feature selection method based on neighborhood rough set and proposes a local composite entropy for dealing with imbalanced data in fuzzy data. Experimental results demonstrate that the proposed method achieves better classification performance in fuzzy data.

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE (2023)

Article Computer Science, Artificial Intelligence

Dynamic updating approximations of local generalized multigranulation neighborhood rough set

Weihua Xu et al.

Summary: The approximation space in rough set theory is crucial for handling uncertainties. The local rough set model, as an effective approach, improves learning efficiency by avoiding unnecessary information granule calculations. This paper investigates the dynamic approximation update mechanism for multigranulation data and proposes corresponding dynamic update algorithms based on the local generalized multigranulation rough set model.

APPLIED INTELLIGENCE (2022)

Article Automation & Control Systems

An Automated Word Embedding with Parameter Tuned Model for Web Crawling

S. Neelakandan et al.

Summary: This paper proposes an Automated Word Embedding with Parameter Tuned Deep Learning (AWE-PTDL) model for focused web crawling. The model involves processes like pre-processing, word embedding, classification, and hyperparameter tuning to improve crawling performance.

INTELLIGENT AUTOMATION AND SOFT COMPUTING (2022)

Article Computer Science, Interdisciplinary Applications

Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems

Fatma A. Hashim et al.

Summary: This paper introduces a new metaheuristic optimization algorithm called Honey Badger Algorithm (HBA), inspired by the intelligent foraging behavior of honey badgers, to develop an efficient search strategy for solving optimization problems. Experimental results demonstrate the effectiveness and superiority of HBA in solving optimization problems with complex search-space.

MATHEMATICS AND COMPUTERS IN SIMULATION (2022)

Article Optics

An efficient low complexity compression based optimal homomorphic encryption for secure fiber optic communication

D. Venu et al.

Summary: The latest advancements in fiber optic communication technology have attracted significant attention due to the benefits of high data rate, acceptable cost, bandwidth, and low attenuation. While fiber optic networks are commonly used for data transfer, security remains a challenge. This paper introduces a new Low Complexity Compression Then Encryption using Optimal Homomorphic Encryption (LCCE-OHE) technique for secure fiber optic communication, which achieves efficient and secure data transmission through compression and encryption processes.

OPTIK (2022)

Article Chemistry, Analytical

Advanced Feature Extraction and Selection Approach Using Deep Learning and Aquila Optimizer for IoT Intrusion Detection System

Abdulaziz Fatani et al.

Summary: In this study, a new intrusion detection system was developed utilizing swarm intelligence algorithms for feature extraction and selection. The system employed neural networks and the Aquila optimizer for this purpose. Performance evaluation on four public datasets demonstrated the competitive nature of the developed approach.

SENSORS (2022)

Article Computer Science, Theory & Methods

Blockchain with deep learning-enabled secure healthcare data transmission and diagnostic model

S. Neelakandan et al.

Summary: Internet of Things (IoT) technologies are widely used in the healthcare sector. This paper introduces a new model, BDL-SMDTD, which combines blockchain and deep learning for secure medical data transmission and diagnosis. The model utilizes image encryption, blockchain storage, and multi-stage operations to achieve secure transmission and accurate diagnosis.

INTERNATIONAL JOURNAL OF MODELING SIMULATION AND SCIENTIFIC COMPUTING (2022)

Article Computer Science, Artificial Intelligence

Updating approximations with dynamic objects based on local multigranulation rough sets in ordered information systems

Wentao Li et al.

Summary: This paper discusses the application of a local rough set model based on dominance relation in ordered information systems, as well as the construction of multigranulation rough set models and the updating process of dynamic objects. Experimental evaluation demonstrates the superiority and effectiveness of the proposed dynamic updating approaches in ordered information systems.

ARTIFICIAL INTELLIGENCE REVIEW (2022)

Article Engineering, Multidisciplinary

A machine learning-based intrusion detection for detecting internet of things network attacks

Yakub Kayode Saheed et al.

Alexandria Engineering Journal (2022)

Review Computer Science, Interdisciplinary Applications

A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges

Ankit Thakkar et al.

Summary: The Internet of Things (IoT) technology is widely accepted in various applications such as smart homes, smart cities, and healthcare, but also raises security concerns. Researchers have proposed numerous security solutions, including intrusion detection systems, to address security issues in IoT networks.

ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2021)

Article Telecommunications

Network intrusion detection system: A systematic study of machine learning and deep learning approaches

Zeeshan Ahmad et al.

Summary: The rapid advances in the internet and communication fields have led to a significant increase in network size and data. Despite efforts to improve accuracy and reduce false alarms, IDS still faces challenges in effectively detecting intrusions and novel attacks. Machine learning and deep learning-based IDS systems have emerged as potential solutions for efficient intrusion detection across networks.

TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES (2021)

Article Computer Science, Information Systems

Effective combining of feature selection techniques for machine learning-enabled IoT intrusion detection

Md Arafatur Rahman et al.

Summary: The paper investigates and leverages effective feature selection techniques to improve intrusion detection using machine learning methods, achieving high detection accuracy on Aegean Wi-Fi Intrusion Dataset.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

Review Computer Science, Hardware & Architecture

Towards secure intrusion detection systems using deep learning techniques: Comprehensive analysis and review

Sang-Woong Lee et al.

Summary: This article focuses on the application of deep learning in intrusion detection systems, discussing how different methods utilize deep learning networks for better results. It classifies the studied IDS schemes and compares their features in different aspects. Finally, comparisons of deep IDS approaches and future research directions are provided.

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS (2021)

Article Computer Science, Information Systems

A Deep Blockchain Framework-Enabled Collaborative Intrusion Detection for Protecting IoT and Cloud Networks

Osama Alkadi et al.

Summary: Significant research has been done on combining blockchain and intrusion detection for enhanced data privacy and detection of cyberattacks. Learning-based ensemble models can identify complex malicious events while ensuring data privacy, providing additional security during VM migration and IoT network protection. The deep blockchain framework proposed in this study outperforms peer models and has potential as a decision support system for secure data migration.

IEEE INTERNET OF THINGS JOURNAL (2021)

Review Computer Science, Information Systems

Deep Learning-Based Intrusion Detection Systems: A Systematic Review

Jan Lansky et al.

Summary: The article discusses the application of deep learning in intrusion detection systems to enhance their performance, including classification and implementation of different deep learning methods, as well as an introduction and analysis of relevant concepts and frameworks.

IEEE ACCESS (2021)

Article Computer Science, Information Systems

A Hybrid Intrusion Detection System Based on Scalable K-Means plus Random Forest and Deep Learning

Chao Liu et al.

Summary: The study proposes an intrusion detection model that combines machine learning and deep learning to classify digital assets into different attack types, achieving better true positive rate and faster data preprocessing speed. The model utilizes adaptive synthetic sampling to address the issue of imbalanced datasets and achieves high accuracy rates in two different datasets.

IEEE ACCESS (2021)

Article Computer Science, Theory & Methods

Intrusion detection in Edge-of-Things computing

Ahmad S. Almogren

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING (2020)

Proceedings Paper Computer Science, Theory & Methods

Big Data Security and Privacy: Current Challenges and Future Research perspective in Cloud Environment

Shafia Riaz et al.

PROCEEDINGS OF 2020 INTERNATIONAL CONFERENCE ON INFORMATION MANAGEMENT AND TECHNOLOGY (ICIMTECH) (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Securing the Data in Cloud Environment Using Parallel and Multistage Security Mechanism

Ranjan Goyal et al.

SOFT COMPUTING FOR PROBLEM SOLVING, SOCPROS 2018, VOL 2 (2020)

Article Computer Science, Software Engineering

An Improved Intrusion Detection System to Preserve Security in Cloud Environment

Partha Ghosh et al.

INTERNATIONAL JOURNAL OF INFORMATION SECURITY AND PRIVACY (2020)

Proceedings Paper Computer Science, Hardware & Architecture

Privacy preserving Intrusion Detection via Homomorphic Encryption

Luigi Coppolino et al.

2019 IEEE 28TH INTERNATIONAL CONFERENCE ON ENABLING TECHNOLOGIES: INFRASTRUCTURE FOR COLLABORATIVE ENTERPRISES (WETICE) (2019)

Article Computer Science, Information Systems

Enhanced intrusion detection and prevention system on cloud environment using hybrid classification and OTS generation

V. Balamurugan et al.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2019)

Article Computer Science, Information Systems

Deep Learning Approach for Intelligent Intrusion Detection System

R. Vinayakumar et al.

IEEE ACCESS (2019)

Article Computer Science, Artificial Intelligence

A Hierarchical Fused Fuzzy Deep Neural Network for Data Classification

Yue Deng et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2017)

Article Automation & Control Systems

Granular Computing Approach to Two-Way Learning Based on Formal Concept Analysis in Fuzzy Datasets

Weihua Xu et al.

IEEE TRANSACTIONS ON CYBERNETICS (2016)