Article
Telecommunications
Haifeng Lin, Qilin Xue, Jiayin Feng, Di Bai
Summary: With the rapid development of the Internet of Things (IoT), there are challenges in terms of security. This study applies cloud computing and machine learning to improve intrusion detection in IoT applications. By using an improved extreme learning machine and other methods, the study explores IoT intrusion detection, cloud node monitoring, and intrusion response in the cloud computing environment. The experimental results show that the proposed algorithm can effectively detect and identify most IoT data and achieve efficient intrusion detection.
DIGITAL COMMUNICATIONS AND NETWORKS
(2023)
Article
Computer Science, Artificial Intelligence
Gauri Kalnoor, S. Gowrishankar
Summary: The proposed work aims to design an intelligent intrusion detection system using machine learning models to identify and protect IoT networks from attacks. Experimental results show that the Markov model performs well in the I-IDS IoT network, achieving a 100% detection rate and low false alarm rate.
Article
Computer Science, Information Systems
Parminder Singh, Avinash Kaur, Gagangeet Singh Aujla, Ranbir Singh Batth, Salil Kanhere
Summary: This article introduces the Dew Computing as a Service (DaaS) for intelligent intrusion detection in Edge of Things (EoT) ecosystems. It uses a deep learning-based classifier to design an intelligent alarm filtration mechanism. The experimentation in a simulated environment shows lower response time, improved classification accuracy, and reduced workload of cloud servers compared to edge IDS.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Hardware & Architecture
Xingzhu Wang
Summary: With the advancement of network security, intrusion detection system (IDS) is increasingly used for network-connected environments. The proposed Enterprise Network for Intrusion Detection System (ENIDS) with a fast localization algorithm detects and locates attacks by identifying abnormal domain values in packets. ENIDS comprises an event generator, an analysis engine, and a reaction component. Experimental results show that the proposed method has a higher localization rate and outperforms existing systems based on accuracy, precision, recall, and F1-score.
MOBILE NETWORKS & APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Li You, Zhanyong Wang
Summary: This paper conducts design analysis and empirical study of network intrusion detection system based on cloud computing, and the results show that the system can effectively detect various types of attacks, verifying the feasibility of the system detection.
TEHNICKI VJESNIK-TECHNICAL GAZETTE
(2022)
Article
Computer Science, Information Systems
Muhammad Nadeem, Ali Arshad, Saman Riaz, Shahab S. Band, Amir Mosavi
Summary: This article discusses the security issues of cloud computing and defense mechanisms, focusing on monitoring the attack rate of the network using an Intrusion Detection System, and providing various solutions to protect the cloud server from attacks.
Article
Chemistry, Multidisciplinary
Mesfer Al Duhayyim, Khalid A. Alissa, Fatma S. Alrayes, Saud S. Alotaibi, ElSayed M. Tag El Din, Amgad Atta Abdelmageed, Ishfaq Yaseen, Abdelwahed Motwakel
Summary: This study introduces a new Stochastic Fractal Search Algorithm with Deep Learning Driven Intrusion Detection System (SFSA-DLIDS) for a cloud-based CPS environment, with a focus on intrusion recognition and classification to enhance security.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Fazlullah Khan, Mian Ahmad Jan, Ryan Alturki, Mohammad Dahman Alshehri, Syed Tauhidullah Shah, Ateeq Ur Rehman
Summary: The Internet of Medical Things (IoMT) effectively addresses various issues in conventional healthcare systems such as personnel shortages, care quality, insufficient supplies, and expenses. IoMT technology offers advantages in treatment efficiency and quality, but faces increasing cyberattacks. This article proposes a cyberattack detection method using ensemble learning and fog-cloud architecture to ensure security. The method outperforms baseline approaches in terms of precision by 4% according to evaluation on the ToN-IoT dataset.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Yunhui Wang, Weichu Zheng, Zifei Liu, Jinyan Wang, Hongjian Shi, Mingyu Gu, Yicheng Di
Summary: The rapid development of cloud-fog-edge computing and mobile devices has generated massive amounts of data. In this context, protecting the cloud-fog-edge computing system from attacks has become crucial. This paper proposes an integrated model that incorporates binary classifiers into a simple classifier network to construct a network intrusion detection system that can protect data privacy.
Review
Computer Science, Hardware & Architecture
Cristiano Antonio de Souza, Carlos Becker Westphall, Renato Bobsin Machado, Leandro Loffi, Carla Merkle Westphall, Guilherme Arthur Geronimo
Summary: The Internet of Things and fog computing play important roles in smart environments, but security is a major challenge. Therefore, research on intrusion detection and prevention is necessary. This article conducts a systematic literature review to evaluate existing technologies and propose possible directions for future research.
Article
Computer Science, Information Systems
Francisco T. Chimuco, Joao B. F. Sequeiros, Carolina Galvao Lopes, Tiago M. C. Simoes, Mario M. Freire, Pedro R. M. Inacio
Summary: This paper discusses the popularity and adoption of mobile devices, driven by the increasing number of mobile applications that solve problems in contemporary societies. The usage of Cloud technology further enhances the resources of mobile devices. However, the lack of security measures has not kept up with the development speed, resulting in a gap between software and security engineering. To bridge this gap, this paper provides a comprehensive approach to attack taxonomy and security test specification for the Cloud and Mobile ecosystem, which is the first of its kind.
INTERNATIONAL JOURNAL OF INFORMATION SECURITY
(2023)
Article
Computer Science, Information Systems
Edeh Michael Onyema, Surjeet Dalal, Carlos Andres Tavera Romero, Bijeta Seth, Praise Young, Mohd Anas Wajid
Summary: This paper proposes an ensemble intrusion strategy based on Cyborg Intelligence framework to enhance the security of IoT enabled networks. By utilizing multiple algorithms, the paper successfully identifies threats and attacks-botnets in IoT networks and achieves good accuracy and detection rate.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
David R. Matos, Miguel L. Pardal, Antonio Rito Silva, Miguel Correia
Summary: Microservice architectures allow complex applications to be developed as a collection of loosely coupled components. Recovering from intrusions in such architectures is challenging due to distribution, different technologies, and scale. We propose mu Verum, a framework that recovers microservices from intrusions by logging user requests and executing compensating operations.
Article
Computer Science, Artificial Intelligence
Dilli Babu Salvakkam, Vijayalakshmi Saravanan, Praphula Kumar Jain, Rajendra Pamula
Summary: The increasing popularity of cloud computing systems has raised concerns about privacy, confidentiality, and availability. Intrusion detection has become crucial, especially in detecting new types of intrusions that can compromise cloud security. This research proposes a unique method using deep learning to detect cloud computing intrusions and presents an accuracy enhancement model for intrusion detection.
COGNITIVE COMPUTATION
(2023)
Review
Computer Science, Information Systems
Jyoti Verma, Abhinav Bhandari, Gurpreet Singh
Summary: This article reviews the advancements in intrusion detection field in the last five years and conducts a comprehensive SWOT analysis of contemporary Network Intrusion Detection Systems in multiple technology dimensions. The authors have performed a comprehensive SWOT analysis of contemporary Network Intrusion Detection Systems, including big-data processing of high volume network traffic, machine learning, deep learning for self-learning machines, readiness for zero-day attacks, distributed processing, cost-effective solution, and ability to perform autonomous operations.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Kaveh Bakhtiyari, Hafizah Husain
NEURAL COMPUTING & APPLICATIONS
(2014)
Article
Computer Science, Artificial Intelligence
Kaveh Bakhtiyari, Mona Taghavi, Hafizah Husain
NEURAL COMPUTING & APPLICATIONS
(2015)
Article
Computer Science, Information Systems
Mona Taghavi, Jamal Bentahar, Hadi Otrok, Kaveh Bakhtiyari
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2020)
Proceedings Paper
Computer Science, Theory & Methods
Kaveh Bakhtiyari, Mona Taghavi, Milad Taghavi, Jamal Bentahar
2019 5TH INTERNATIONAL CONFERENCE ON WEB RESEARCH (ICWR)
(2019)
Article
Computer Science, Hardware & Architecture
Mona Taghavi, Jamal Bentahar, Kaveh Bakhtiyari, Chihab Hanachi
Proceedings Paper
Computer Science, Artificial Intelligence
Kaveh Bakhtiyari, Juergen Ziegler, Hafizah Husain
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2017, PT I
(2017)
Article
Management
Masoud Shakiba, Nader Ale Ebrahim, Mahmoud Danaee, Kaveh Bakhtiyari, Elankovan Sundararajan
REVISTA DE GESTAO E SECRETARIADO-GESEC
(2015)
Proceedings Paper
Computer Science, Artificial Intelligence
Kaveh Bakhtiyari, Mona Taghavi, Hafizah Husain
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, PT 1
(2014)
Article
Information Science & Library Science
Ahmed Patel, Kaveh Bakhtiyari, Mona Taghavi
Article
Computer Science, Hardware & Architecture
Zihang Zhen, Xiaoding Wang, Hui Lin, Sahil Garg, Prabhat Kumar, M. Shamim Hossain
Summary: In this paper, a blockchain architecture based on dynamic state sharding (DSSBD) is proposed to solve the problems caused by cross-shard transactions and reconfiguration. By utilizing deep reinforcement learning, the number of shards, block spacing, and block size can be dynamically adjusted to improve the performance of the blockchain. The experimental results show that the crowdsourcing system with DSSBD has better performance in terms of throughput, latency, balancing, cross-shard transaction proportion, and node reconfiguration proportion, while ensuring security.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Gabriel F. C. de Queiroz, Jose F. de Rezende, Valmir C. Barbosa
Summary: Multi-access Edge Computing (MEC) is a technology that enables faster task processing at the network edge by deploying servers closer to end users. This paper proposes the FlexDO algorithm to solve the DAG application partitioning and offloading problem, and compares it with other solutions to demonstrate its superior performance in various test scenarios.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shahid Latif, Wadii Boulila, Anis Koubaa, Zhuo Zou, Jawad Ahmad
Summary: In the field of Industrial Internet of Things (IIoT), networks are increasingly vulnerable to cyberattacks. This research introduces an optimized Intrusion Detection System based on Deep Transfer Learning (DTL) for heterogeneous IIoT networks, combining Convolutional Neural Networks (CNNs), Genetic Algorithms (GA), and ensemble techniques. Through rigorous evaluation, the framework achieves exceptional performance and accurate detection of various cyberattacks.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Rongji Liao, Yuan Zhang, Jinyao Yan, Yang Cai, Narisu Tao
Summary: This paper proposes a joint control approach called STOP to guarantee user-perceived deadline using curriculum-guided deep reinforcement learning. Experimental results show that the STOP scheme achieves a significantly higher average arrival ratio in NS-3.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Miguel Rodriguez-Perez, Sergio Herreria-Alonso, J. Carlos Lopez-Ardao, Raul F. Rodriguez-Rubio
Summary: This paper presents an implementation of an active queue management (AQM) algorithm for the Named-Data Networking (NDN) architecture and its application in congestion control protocols. By utilizing the congestion mark field in NDN packets, information about each transmission queue is encoded to achieve a scalable AQM solution.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Angel Canete, Mercedes Amor, Lidia Fuentes
Summary: This paper proposes an energy-aware placement of service function chains of Virtual Network Functions (VNFs) and a resource-allocation solution for heterogeneous edge infrastructures. The solution has been integrated with an open source management and orchestration project and has been successfully applied to augmented reality services, achieving significant reduction in power consumption and ensuring quality of service compliance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Sachin Kadam, Kaustubh S. Bhargao, Gaurav S. Kasbekar
Summary: This paper discusses the problem of estimating the node cardinality of each node type in a heterogeneous wireless network. Two schemes, HSRC-M1 and HSRC-M2, are proposed to rapidly estimate the number of nodes of each type. The accuracy and efficiency of these schemes are proven through mathematical analysis and simulation experiments.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Jean Nestor M. Dahj, Kingsley A. Ogudo, Leandro Boonzaaier
Summary: The launch of commercial 5G networks has opened up opportunities for heavy data users and highspeed applications, but traditional monitoring and evaluation techniques have limitations in the 5G networks. This paper presents a cost-effective hybrid analytical approach for detecting and evaluating user experience in real-time 5G networks, using statistical methods to calculate the user quality index.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Ali Nauman, Haya Mesfer Alshahrani, Nadhem Nemri, Kamal M. Othman, Nojood O. Aljehane, Mashael Maashi, Ashit Kumar Dutta, Mohammed Assiri, Wali Ullah Khan
Summary: The integration of terrestrial and satellite wireless communication networks offers a practical solution to enhance network coverage, connectivity, and cost-effectiveness. This study introduces a resource allocation framework that leverages local cache pool deployments and non-orthogonal multiple access (NOMA) to improve energy efficiency. Through the use of a multi-agent enabled deep deterministic policy gradient algorithm (MADDPG), the proposed approach optimizes user association, cache design, and transmission power control, resulting in enhanced energy efficiency and reduced time delays compared to existing methods.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Wu Chen, Jiayi Zhu, Jiajia Liu, Hongzhi Guo
Summary: With advancements in technology, large-scale drone swarms will be widely used in commercial and military fields. Current application methods are mainly divided into autonomous methods and controlled methods. This paper proposes a new framework for global coordination through local interaction.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Peiying Zhang, Zhihu Luo, Neeraj Kumar, Mohsen Guizani, Hongxia Zhang, Jian Wang
Summary: With the development of Industry 5.0, the demand for network access devices is increasing, especially in areas such as financial transactions, drone control, and telemedicine where low latency is crucial. However, traditional network architectures limit the construction of low-latency networks due to the tight coupling of control and data forwarding functions. To overcome this problem, researchers propose a constraint escalation virtual network embedding algorithm assisted by Graph Convolutional Networks (GCN), which automatically extracts network features and accelerates the learning process to improve network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Review
Computer Science, Hardware & Architecture
P. Anitha, H. S. Vimala, J. Shreyas
Summary: Congestion control is crucial for maintaining network stability, reliability, and performance in IoT. It ensures that critical applications can operate seamlessly and that IoT devices can communicate efficiently without overwhelming the network. Congestion control algorithms ensure that the network operates within its capacity, preventing network overload and maintaining network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shunmugapriya Ramanathan, Abhishek Bhattacharyya, Koteswararao Kondepu, Andrea Fumagalli
Summary: This article presents an experiment that achieves live migration of a containerized 5G Central Unit module using modified open-source migration software. By comparing different migration techniques, it is found that the hybrid migration technique can reduce end-user service recovery time by 36% compared to the traditional cold migration technique.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Fatma Foad Ashrif, Elankovan A. Sundararajan, Rami Ahmad, Mohammad Kamrul Hasan, Elaheh Yadegaridehkordi
Summary: This article introduces the development and current status of authentication protocols in 6LoWPAN, and proposes an innovative perspective to fill the research gap. The article comprehensively surveys and evaluates AKA protocols, analyzing their suitability in wireless sensor networks and the Internet of Things, and proposes future research directions and issues.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Pranjal Kumar Nandi, Md. Rejaul Islam Reaj, Sujan Sarker, Md. Abdur Razzaque, Md. Mamun-or-Rashid, Palash Roy
Summary: This paper proposes a task offloading policy for IoT devices to a mobile edge computing system, aiming to balance device utility and execution cost. A meta heuristic approach is developed to solve the offloading problem, and the results show its potential in terms of task execution latency, energy consumption, utility per unit cost, and task drop rate.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)