Web Intelligence - Volume 22, issue 4

Authors: Sharma, Sonam | Seth, Dambarudhar | Kapil, Manoj

Article Type: Research Article

Abstract: Software Defined Network (SDN) facilitates a centralized control management of devices in network, which solves many issues in the old network. However, as the modern era generates a vast amount of data, the controller in an SDN could become overloaded. Numerous investigators have offered their opinions on how to address the issue of controller overloading in order to resolve it. Mostly the traditional models consider two or three parameters to evenly distribute the load in SDN, which is not sufficient for precise load balancing strategy. Hence, an effective load balancing model is in need that considers different parameters. Considering this …aspect, this paper presents a new load balancing model in SDN is introduced by following three major phases: (a) work load prediction, (b) optimal load balancing, and (c) switch migration. Initially, work load prediction is done via improved Deep Maxout Network. COA and BWO are conceptually combined in the proposed hybrid optimization technique known as Coati Updated Black Widow (CUBW). Then, the optimal load balancing is done via hybrid optimization named Coati Updated Black Widow (CUBW) Optimization Algorithm. The optimal load balancing is done by considering migration time, migration cost, distance and load balancing parameters like server load, response time and turnaround time. Finally, switch migration is carried out by considering the constraints like migration time, migration cost, and distance. The migration time of the proposed method achieves lower value, which is 27.3%, 40.8%, 24.40%, 41.8%, 42.8%, 42.2%, 40.0%, and 41.6% higher than the previous models like BMO, BES, AOA, TDO, CSO, GLSOM, HDD-PLB, BWO and COA respectively. Finally, the performance of proposed work is validated over the conventional methods in terms of different analysis. Show more

Keywords: SDN, load balancing, deep Maxout, CUBW, switch migration

DOI: 10.3233/WEB-230263

Citation: Web Intelligence, vol. 22, no. 4, pp. 479-500, 2024

Authors: Y, Kingston Albert Dhas | Jerine, S.

Article Type: Research Article

Abstract: Mobile Ad-Hoc Network (MANETs) is referred to as the mobile wireless nodes that make up ad hoc networks. The network topology may fluctuate on a regular basis due to node mobility. Each node serves as a router, passing traffic throughout the network, and they construct the network’s infrastructure on their own. MANET routing protocols need to be able to store routing information and adjust to changes in the network topology in order to forward packets to their destinations. While mobile networks are the main application for MANET routing techniques, networks with stationary nodes and no network infrastructure can also benefit …from using them. In this paper, we proposed a Self Adaptive Tasmanian Devil Optimization (SATDO) based Routing and Data Aggregation in MANET. The first step in the process is clustering, where the best cluster heads are chosen according to a number of limitations, such as energy, distance, delay, and enhanced risk factor assessment on security conditions. In this study, the SATDO algorithm is proposed for this optimal selection. Subsequent to the clustering process, routing will optimally take place via the same SATDO algorithm introduced in this work. Finally, an improved kernel least mean square-based data aggregation method is carried out to avoid data redundancy. The efficiency of the suggested routing model is contrasted with the conventional algorithms via different performance measures. Show more

Keywords: MANET, routing, mobile networks, kernel, clustering

DOI: 10.3233/WEB-230272

Citation: Web Intelligence, vol. 22, no. 4, pp. 501-521, 2024

Authors: Singh, Balkar | Kasana, Geeta

Article Type: Research Article

Abstract: The rapid progress in the transfer of information and its availability are the reasons behind the widespread use of the Internet. Document images are the most complicated and challenging category among various forms of digital data to which watermarking can be applied for its security and authentication. Watermarking of the document image is a very difficult task, since these images have very limited redundancy. Because of this factor there has been very little research in this area. A comprehensive research should be carried out to ensure the effective assessment, review as well as implementation of document image watermarking techniques. This …paper reviews the existing document image watermarking by considering different evaluation parameters. Based on this review, a variety of challenges and directions have been prescribed for the development of effective watermarking techniques for document images. Show more

Keywords: Entropy, peak-signal to noise-ratio, bit error rate, normalized hamming distance, normalized absolute error

DOI: 10.3233/WEB-230280

Citation: Web Intelligence, vol. 22, no. 4, pp. 523-553, 2024

Authors: Pawar, Shilpa Devram | Rao, Damala Dayakar

Article Type: Research Article

Abstract: Heart disease is a critical issue that affects people, causes serious sickness, and is the main cause of mortality worldwide. Early diagnosis of disease plays a significant role in heart disease prediction and is attained by various automation techniques. The availability of automation techniques initiates the necessity for medical data and the storage of medical data becomes a research problem due to its high sensitivity. The emergence of IoT networks formed a promising solution for data storage through the cloud server and preventing the data from various threats is a challenging problem. A secure heart disease prediction system is developed …by the utility of the ESVO-based Swish Bessel CNN classifier (Emperor Spheniscidae Vampire Optimization-based Swish Bessel Convolutional Neural Network), and the important significance of the research depends on the ESVO optimization that helps in gaining a deeper insight of the classifier as well as helps in preventing the threatening of data. The security of the cloud server is enhanced by the EDH-ECC (Entropy Diffie Hellman – Elliptic Curve Cryptography) which promotes the information exchange even in unsecured channels. Similarly, the authentication and authorization of the cloud server are carried out using the EAN-13 and salt-based digital signature that initiates strong credentials and enhance data security. Finally, the heart disease is diagnosed using the ESVO-based Swish Bessel CNN classifier. Assessing the accuracy, sensitivity, specificity, and F1-measure, which provided values of 94.877 %, 95.464 %, 93.293 %, and 95.14 % shows the effectiveness of the research. Show more

Keywords: Heart disease, ESVO-based Swish Bessel CNN classifier, EDH-ECC, EAN-13, security

DOI: 10.3233/WEB-220118

Citation: Web Intelligence, vol. 22, no. 4, pp. 555-579, 2024

Authors: Chandan, Madhavarapu | Santhi, S.G. | Srinivasa Rao, T.

Article Type: Research Article

Abstract: Malware transmission is a significant security issue in WSN, however, the influence of the attack and defensive processes on malware propagation is rarely taken into account in traditional malware propagation prevention methods. Advanced methods are in need to stop the propagation of malware of sensor nodes. With the formulation of representing dynamics among states, a new decision-making problem as the optimal control problem via hybrid optimization algorithm. The proposing model is termed as Butterfly Updated Bald Eagle Optimization based Prevention of Malware Propagation in Wireless Sensor Network (BUBEO-PMPWSN). In the proposed controlling system, optimal system parameters are analyzed via the …BUBEO for preventing malware propagation in WSN. Particularly, the sensor node states considered are Susceptible, Infectious, Infectious and sleeping, recovered, Recovered and sleeping, and finally Dead. The system parameter tuning will be under the evaluation of fitness calculation under probability of infectious sensor node becoming recovered and the probability of infectious sensor node entering sleeping state. This optimal tuning strategy ensures the preventing of malware propagation. Finally, the performance of proposed BUBEO-PMPWSN model is evaluated and validated successfully by comparing other state-of-the-art models. The BUBEO-PMPWSN achieved 250 recovered nodes for time 500, while the HGS, BOA, HBA, COOT, and HHO scored 123, 115, 236, 172, and 180, respectively, for recovered nodes. Show more

Keywords: Wireless sensor network, malware propagation, hybrid optimization, malware prevention, Butterfly Updated Bald Eagle Optimization

DOI: 10.3233/WEB-230058

Citation: Web Intelligence, vol. 22, no. 4, pp. 581-597, 2024

Authors: Gokulkumari, G. | Alhassan, Ibrahim | Basahel, Sulafah M.

Article Type: Research Article

Abstract: Augmented Reality is recognized as the newest clever breakthrough in marketing and is used to promote a variety of goods and services. Through the use of this technology, businesses and brands interact with their target market to learn everything about their current and potential customers’ expectations. However, important elements are associated with the development of augmented reality technology. The objective of this article is to scientifically evaluate the usefulness of virtual reality techniques in digital marketing. The study concentrated on a variety of variables, including those that influence consumers’ desire to make a purchase, such as the degree to which …a system is interactive, instructive, and congruent with reality. The quantitative methodology used in this study. Random sampling methodology is used in a survey method to gather data. The partially least-squares Structured Equation Modeling (PLS-SEM) method will also be used to evaluate and confirm any proposed causal links between the latent variables. Direct marketing and system quality were shown to be correlated, and the significance value (sig ) was found to be less than 0.05. The conclusion confirms the assumption that interactivity has no significant and positive impact on digital marketing but, system quality, product informativeness, and reality congruence have a large and advantageous effect on digital marketing. Empirical findings suggest that using augmented reality technologies is one of the greatest digital marketing ways to engage customers in interactive experiences and provide them with quality goods and services. Show more

Keywords: Augmented reality, digital marketing, customer experience, AR marketing activities

DOI: 10.3233/WEB-230262

Citation: Web Intelligence, vol. 22, no. 4, pp. 599-610, 2024

Authors: Yan, Xin | Liu, Fangchang | Jiang, Lincheng | Long, Youlong

Article Type: Research Article

Abstract: The conventional approach to event extraction requires predefined event types and their corresponding annotations to train event extractors. However, these prerequisites are often difficult to satisfy in real-world applications. To automatically induct event types, most work has been devoted to clustering event triggers, where a cluster of event triggers is represented as an event type. Some works use trigger semantics, while others use co-occurrence relationships to cluster triggers. However, the clustering results of event triggers obtained by the above work are not sufficiently detailed in describing event types, making it difficult to accurately determine the corresponding event types manually. This …paper proposes an open-domain event type induction framework that automatically discovers a set of event types from a given corpus. Unlike previous work on event trigger clustering, this paper takes into consideration the hierarchical relationship of event types to partition the event trigger clusters into event mains and subtypes. The framework employs a latent variable-based neural generation module and a semantic-based clustering module, the former of which obtains event trigger clusters representing the main types of events by jointly projecting the co-occurrence and semantic information of event triggers into a latent space for event type latent variable mining, and the latter of which further divides these event trigger clusters into event subtypes based on semantic information. Finally, experiment results show that, compared with the benchmark model, the ETGen-Clus can improve event type quality scores of 6.23% and 3.11% on the two datasets, respectively. Show more

Keywords: Event extraction, event type induction, deep learning, latent variable

DOI: 10.3233/WEB-230394

Citation: Web Intelligence, vol. 22, no. 4, pp. 611-626, 2024

Authors: Lavanya P, Venkata | Tripathi, Mukesh Kumar | E P, Hemand | K, Sangeetha | Ramesh, Janjhyam Venkata Naga

Article Type: Research Article

Abstract: Agriculture is a significant source of income, and categorizing the crop has turned into vital factor that aids more in the crop production sector. Traditionally, crop development stage determination is done manually by eye inspection. However, producing high-quality crop type maps using modern approaches remains difficult. In this paper, the hyperspectral crop image classification model is proposed that includes four stages, they are (a) preprocessing, (b) segmentation, (c) feature extraction and (d) classification. In the preprocessing step, the hyperspectral image is provided as input, where the filtering process will carried out using median filtering. The filtered image is then used …as the segmentation’s input. The image is segmented in the segmentation step using the enhanced entropy-based fuzzy c -means technique. Subsequently, spectral spatial features and vegetation index-based features are derived from segmented images. The final step is the classification, where the ensemble of classification model will be used that includes models like Convolutional Neural Networks (CNN), Deep Maxout (DMO), Recurrent Neural Networks (RNN), and Bidirectional Gated Recurrent Unit (Bi-GRU), respectively. The proposed Self Improved Tasmanian devil Optimization (SI-TDO) approach has optimally adjusted the Bi-GRU model’s training weights to enhance ensemble classification performance. Finally, the effectiveness of the proposed SI-TDO method compared to the traditional algorithm is examined for several metrics. The SI-TDO obtained the greatest accuracy of 94.68% in training rate 80, while other existing models have the lowest ratings. Show more

Keywords: Hyperspectral images, crop, classification, Bidirectional Gated Recurrent Unit, self improved Tasmanian devil optimization algorithm

DOI: 10.3233/WEB-230209

Citation: Web Intelligence, vol. 22, no. 4, pp. 627-657, 2024

Authors: Abdulmunim, Tamara | Tao, Xiaohui | Zhang, Ji | Yong, Jianming | Yong, Jianming | Zhou, Xujuan

Article Type: Research Article

Abstract: Recommender Systems are mainly used in various e-commerce applications, especially online stores threatening users’ privacy. The privacy issues can be overcome by using security solutions, which include blockchain technology for privacy applications. The fusion of the Internet of Things and blockchain technology has fully improved modern distributed systems. The combination guarantees the safety and scalability of the recommender system. We aim to create an authorized secure exchange device using blockchain-enabled multiparty computation by adding smart contracts to the core blockchain protocol. The recommendation structure and Blockchain technology make online shopping more convenient and private. We propose a blockchain-related recommender system …using the “movielens” data. The case study includes a smart contract model that recommends movies to buyers. Initially, we tested the model on a small “movielens dataset” and extended it to a 3M movielens dataset. We developed a classifier model for movielens and proposed a Dual light graph convolutional network for movielens data classification. Our results, including ablation analysis, show that blockchain strategies and Dual light graph convolutional networks can effectively improve recommender systems’ privacy. Furthermore, the suggested blockchain technique can be stretched by similar procedures. Show more

Keywords: Blockchain, recommender systems, privacy preserving, decentralized system, Ethereum

DOI: 10.3233/WEB-230346

Citation: Web Intelligence, vol. 22, no. 4, pp. 659-680, 2024