Journal of High Speed Networks - Volume 30, issue 2

Authors: Granata, Daniele | Mastroianni, Michele | Rak, Massimiliano | Cantiello, Pasquale | Salzillo, Giovanni

Article Type: Research Article

Abstract: Since 2018, the enactment of the General Data Protection Regulation (GDPR) has bestowed distinct privileges upon each person while imposing protocols to safeguard personal information. The GDPR effectively tackles an evident requirement within our interconnected, social media-driven society. However, its compliance poses a considerable challenge, particularly for small and medium-sized businesses. This work aims to identify and select the proper countermeasures in order to comply with GDPR, by using standard security controls. Thus, we designed a tool to handle some phases of the compliance process in an almost semi-automated way. The proposed approach relies on standard security control frameworks (namely …NIST SP-800-53) and can be easily adapted to different frameworks. The proposed technique was validated using our university as a case study, through a simple demonstrator, although the solution can be transparently applied to different contexts. Show more

Keywords: GDPR, privacy, cloud, security policy, security control framework

DOI: 10.3233/JHS-230080

Citation: Journal of High Speed Networks, vol. 30, no. 2, pp. 147-174, 2024

Authors: Lu, Qiuyu | Li, Haibo | Zheng, Jianping | Qin, Jianru | Yang, Yinguo | Li, Li | Jiang, Keteng

Article Type: Research Article

Abstract: In order to study the operating characteristics of variable speed constant frequency wind turbine under different working conditions and the monitoring system of wind turbine. In this paper, the simulation model of each component system of wind turbine is established by MATLAB/Simulink module, and the influence law of different wind speed and ground fault types on the output power of wind turbine is studied. The active power of wind turbines under different short-circuit fault types is compared. At the same time, in order to realize real-time monitoring of wind turbine speed and output power, an online monitoring system for wind …turbine operation based on industrial Internet of Things is proposed, and the composition and operation characteristics of this remote monitoring system are given. The practical application shows that the on-line monitoring system can accurately and remotely monitor the running status of the wind turbine and avoid the unstable running of the wind turbine. The research conclusions of this paper can provide reference for the design and construction of wind turbines and the operation of connecting to the power grid. Show more

Keywords: Wind power, variable speed constant frequency wind turbine, remote monitoring system, Internet of Things

DOI: 10.3233/JHS-222009

Citation: Journal of High Speed Networks, vol. 30, no. 2, pp. 175-189, 2024

Authors: Shirley, C.P. | Kumar, Jaydip | Pitambar Rane, Kantilal | Kumar, Narendra | Radha Rani, Deevi | Harshitha, Kuntamukkula | Tiwari, Mohit

Article Type: Research Article

Abstract: IoT networks can be defined as groups of physically connected things and devices that can connect to the Internet and exchange data with one another. Since enabling an increasing number of internets of things devices to connect with their networks, organizations have become more vulnerable to safety issues and attacks. A major drawback of previous research is that it can find out prior seen types only, also any new device types are considered anomalous. In this manuscript, IoT device type detection utilizing Training deep quantum neural networks optimized with a Chimp optimization algorithm for enhancing IOT security (IOT-DTI-TDQNN-COA-ES) is proposed. …The proposed method entails three phases namely data collection, feature extraction and detection. For Data collection phase, real network traffic dataset from different IoT device types are collected. For feature mining phase, the internet traffic features are extracted through automated building extraction (ABE) method. IoT device type identification phase, Training deep quantum neural networks (TDQNN) optimized with Chimp optimization algorithm (COA) is utilized to detect the category of IoT devices as known and unknown device. IoT network is implemented in Python. Then the simulation performance of the proposed IOT-DTI-TDQNN-COA-ES method attains higher accuracy as26.82% and 23.48% respectively, when compared with the existing methods. Show more

Keywords: IOT security, device type identification, training deep quantum neural networks, chimp optimization algorithm

DOI: 10.3233/JHS-230028

Citation: Journal of High Speed Networks, vol. 30, no. 2, pp. 191-201, 2024

Authors: Amune, Amruta Chandrakant | Pande, Himangi

Article Type: Research Article

Abstract: Wireless sensor networks (WSNs) have emerged as a one of the most fascinating areas of lookup in the past few years principally due to its massive quantity of workable applications. However limited energy, node deployment strategy, routing techniques has considerable impact on the overall performance of network. This paper proposes sustainable honey bee ratel based hybrid wireless sensor network (SHHWSN) layering framework for improving load balancing and scalability issues in network. In SHHWSN tessellated hexagonal shape clusters are formed to cover entire geographical region without any gaps. Hybrid routing schema constrained with redundant data identification policy used in this, seeks …to optimize energy utilization. The proposed SHHWSN was evaluated and validated by simulation, and the results were compared with earlier schematics where mostly one sided stochastic node deployments were followed. The experimental results show that SHHWSN has superior performance in terms of network alive nodes, delay, energy and throughput. The proposed SHHWSN obtained values of 50 nodes is 3, 0.061, 0.14, 0.89, 100 nodes is 3,0.037, 0.19, 0.551, 150 nodes is 13, 0.081, 0.23, 0.415, and 200 nodes is 23, 1.01, 0.25, 0.356, which is significantly more effective than current techniques. Show more

Keywords: WSN, honey bee ratel optimization, multitier scalable clustering, routing and Djiskstra algorithm

DOI: 10.3233/JHS-230086

Citation: Journal of High Speed Networks, vol. 30, no. 2, pp. 203-219, 2024

Authors: Singh, Charanjeet | Singh, Pawan Kumar

Article Type: Research Article

Abstract: Massive MIMO (M-MIMO) devices are the key tool to meet the performance stards established for 5G-wireless communication. However, more Radio Frequency (RF) chains needed in base station (BS) with a huge count of transmitting antennas, involve expensive hardware and computing complexities. In order to decrease the RF chains needed in BS, this work intended to use the optimal transmit antenna selection (TAS) strategy. This strategy is gaining a lot of interest since the optimization algorithm aids in the ability to enhance the system performance considerably the efficiency and secrecy rate. This work proposes a novel Coati Adopted Pelican Optimization (CA-PO) …for choosing the optimal TA by considering efficiency as well as secrecy rate. In addition, the CA-PO algorithm makes the decision on which antenna to be elected. At last, the supremacy of CA-PO-based TAS is proven from the analysis regarding secrecy rate and EE analysis. Accordingly, the proposed CA-PO method for MF for set up 2 has attained a higher EE of 0.976; whereas, the DMOA, COA, MRFO, POA and BEA techniques have got a relatively lower EE of 0.968. Show more

Keywords: M-MIMO, Optimal TAS, efficiency, secrecy rate, CA-PO Algorithm

DOI: 10.3233/JHS-230087

Citation: Journal of High Speed Networks, vol. 30, no. 2, pp. 221-238, 2024

Authors: Barolli, Leonard

Article Type: Research Article

Abstract: In this paper, we present a hybrid intelligent simulation system for optimization of mesh routers in Wireless Mesh Networks (WMNs) called WMN-PSOHCDGA. We implemented six mesh router replacement methods: CM, RIWM, LDIWM, LDVM, RDVM and FC-RDVM and consider Two Islands distribution of mesh clients. We carry out a comparison study of these router replacement methods for small and middle scale WMNs. We assessed the performance by computer simulations. The simulation results show that six methods have a good performance for connectivity and coverage metrics, for both small and middle scale WMNs. However, they have different behavior for load balancing. For …small scale WMNs, the load balancing of LDIWM, RIWM and FC-RDVM is better than CM, LDVM and RDVM. While, comparing LDIWM, RIWM and FC-RDVM, the LDIWM has better load balancing. We found that the load balancing for small scale WMNs is not good, because there is a concentration of mesh routers in some areas. For middle scale WMNs, the CM, LDIWM, LDVM and RDVM have not a good load balancing. While, the RIWM and FC-RDVM have better performance. Comparing RIWM and FC-RDVM, we found that the load balancing of FC-RDVM is better than RIWM. Show more

Keywords: Wireless mesh networks, mesh router replacement methods, two islands distribution, intelligent algorithms, hybrid intelligent simulation system

DOI: 10.3233/JHS-230093

Citation: Journal of High Speed Networks, vol. 30, no. 2, pp. 239-250, 2024

Authors: Muthukumar, S. | Ashfauk Ahamed, A.K.

Article Type: Research Article

Abstract: The “Distributed Denial of Service (DDoS)” threats have become a tool for the hackers, cyber swindlers, and cyber terrorists. Despite the high amount of conventional mitigation mechanisms that are present nowadays, the DDoS threats continue to enhance in severity, volume, and frequency. The DDoS attack has highly affected the availability of the networks for the previous years and still, there is no efficient defense technique against it. Moreover, the new and complex DDoS attacks are increasing on a daily basis but the traditional DDoS attack detection techniques cannot react to these threats. On the other hand, the hackers are employing …very innovative strategies to initiate the threats. But, the traditional methods can become effective and reliable when combined with the deep learning-aided approaches. To solve these certain issues, a framework detection mechanism for DDoS attacks utilizes an attention-aided deep learning methodology. The primary thing is the acquisition of data from standard data online sources. Further, from the garnered data, the significant features are drawn out from the “Deep Weighted Restricted Boltzmann Machine (RBM)” using a “Deep Belief Network (DBN)”, in which the parameters are tuned by employing the recommended Enhanced Gannet Optimization Algorithm (EGOA). This feature extraction operation increases the network performance rate and also diminishes the dimensionality issues. Lastly, the acquired features are transferred to the model of “Attention and Cascaded Recurrent Neural Network (RNN) with Residual Long Short Term Memory (LSTM) (ACRNN-RLSTM)” blocks for the DDoS threat detection purpose. This designed network precisely identifies the complex and new attacks, thus it increases the trustworthiness of the network. In the end, the performance of the approach is contrasted with other traditional algorithms. Hence, the simulation outcomes are obtained that prove the system’s efficiency. Also, the outcomes displayed that the designed system overcame the conventional threat detection techniques. Show more

Keywords: DDoS Attack Detection, deep learning, features extraction, restricted Boltzmann machine, hyper-parameters optimization, enhanced gannet optimization algorithm, attention and cascaded recurrent neural network with residual long short term memory

DOI: 10.3233/JHS-230142

Citation: Journal of High Speed Networks, vol. 30, no. 2, pp. 251-277, 2024

Authors: Higashi, Shunya | Ampririt, Phudit | Qafzezi, Ermioni | Ikeda, Makoto | Matsuo, Keita | Barolli, Leonard

Article Type: Research Article

Abstract: In recent years, the human-to-human and human-to-things relationships are becoming complicated and unreliable, which makes harder decisions in a variety of situations. As a result, trust computing is gaining interest in a number of research fields. The Logical Trust (LT) is one of trust computing concepts. In this paper, we design a Fuzzy-based System for Decision of Logical Trust (FSDLT). We implement two models: FSDLTM1 and FSDLTM2. The FSDLTM1 considers three input parameters: Belief (Be), Experience (Ep), Rationality (Ra) and the output parameter is LT. In FSDLTM2, we consider Reliability (Re) as a new parameter. We evaluated the implemented models …by computer simulations. The simulation results show that when Be, Ep, Ra and Re are increasing, the LT is increased. For FSDLTM1, when Ep value is 0.9, all LT values are greater than 0.5. While for FSDLTM2, in case when Be is 0.9, for all values of Ra and Re, when Ep is 0.5 and 0.9, all LT values are higher than 0.5. This shows that the person or device is trustworthy. The FSDLTM2 is more complex than FSALTM1 but it makes a better decision for LT by considering four input parameters. Show more

Keywords: Trust computing, fuzzy logic, intelligent algorithms, decision making systems

DOI: 10.3233/JHS-230189

Citation: Journal of High Speed Networks, vol. 30, no. 2, pp. 279-295, 2024