Abdulaziz Attaallah¹, Raees Ahmad Khan^2,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5683-5705, 2022, DOI:10.32604/cmc.2022.021643 - 11 October 2021

Abstract The apparent contradiction between usability and security has been discussed in the literature for several years. This continuous trade-off requires be acknowledging and handling whenever security solutions are introduced. However, some progressive analysts point out that present security solutions are usually very difficult for several users, and they have expressed a willingness to simplify the security product user experience. Usable security is still mostly unexplored territory in computer science. Which we are all aware with security and usability on many levels, usable security has received little operational attention. Companies have recently focused primarily on usable… More >

Sohail Khan^1,*, Mohammad Nauman², Suleiman Ali Alsaif¹, Toqeer Ali Syed³, Hassan Ahmad Eleraky¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5345-5362, 2022, DOI:10.32604/cmc.2022.021271 - 11 October 2021

Abstract Mobile phones are an essential part of modern life. The two popular mobile phone platforms, Android and iPhone Operating System (iOS), have an immense impact on the lives of millions of people. Among these two, Android currently boasts more than 84% market share. Thus, any personal data put on it are at great risk if not properly protected. On the other hand, more than a million pieces of malware have been reported on Android in just 2021 till date. Detecting and mitigating all this malware is extremely difficult for any set of human experts. Due… More >

Mesfer Al Duhayyim¹, Haya Mesfer Alshahrani², Fahd N. Al-Wesabi³, Mohammed Alamgeer⁴, Anwer Mustafa Hilal^5,*, Mohammed Rizwanullah⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6257-6270, 2022, DOI:10.32604/cmc.2022.021212 - 11 October 2021

Abstract Cybersecurity encompasses various elements such as strategies, policies, processes, and techniques to accomplish availability, confidentiality, and integrity of resource processing, network, software, and data from attacks. In this scenario, the rising popularity of Online Social Networks (OSN) is under threat from spammers for which effective spam bot detection approaches should be developed. Earlier studies have developed different approaches for the detection of spam bots in OSN. But those techniques primarily concentrated on hand-crafted features to capture the features of malicious users while the application of Deep Learning (DL) models needs to be explored. With this… More >

G. Naga Chandrika¹, Khalid Alnowibet², K. Sandeep Kautish³, E. Sreenivasa Reddy⁴, Adel F. Alrasheedi², Ali Wagdy Mohamed^5,6,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5707-5720, 2022, DOI:10.32604/cmc.2022.021186 - 11 October 2021

Abstract Graphs are used in various disciplines such as telecommunication, biological networks, as well as social networks. In large-scale networks, it is challenging to detect the communities by learning the distinct properties of the graph. As deep learning has made contributions in a variety of domains, we try to use deep learning techniques to mine the knowledge from large-scale graph networks. In this paper, we aim to provide a strategy for detecting communities using deep autoencoders and obtain generic neural attention to graphs. The advantages of neural attention are widely seen in the field of NLP… More >

Ajisha Mathias¹, Samiappan Dhanalakshmi^1,*, R. Kumar¹, R. Narayanamoorthi²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5251-5267, 2022, DOI:10.32604/cmc.2022.021168 - 11 October 2021

Abstract Object recognition and computer vision techniques for automated object identification are attracting marine biologist's interest as a quicker and easier tool for estimating the fish abundance in marine environments. However, the biggest problem posed by unrestricted aquatic imaging is low luminance, turbidity, background ambiguity, and context camouflage, which make traditional approaches rely on their efficiency due to inaccurate detection or elevated false-positive rates. To address these challenges, we suggest a systemic approach to merge visual features and Gaussian mixture models with You Only Look Once (YOLOv3) deep network, a coherent strategy for recognizing fish in… More >

Amgad Muneer^1,2,*, Shakirah Mohd Taib^1,2, Suliman Mohamed Fati³, Abdullateef O. Balogun¹, Izzatdin Abdul Aziz^1,2

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5363-5381, 2022, DOI:10.32604/cmc.2022.021113 - 11 October 2021

Abstract Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world problems. Many issues in this field still unsolved, so several modern anomaly detection methods struggle to maintain adequate accuracy due to the highly descriptive nature of big data. Such a phenomenon is referred to as the “curse of dimensionality” that affects traditional techniques in terms of both accuracy and performance. Thus, this research proposed a hybrid model based on Deep Autoencoder Neural Network (DANN) with five layers to reduce the difference between the input and output. The proposed… More >

Nouh Sabri Elmitwally^1,2, Asma Kanwal^3,4, Sagheer Abbas³, Muhammad A. Khan⁵, Muhammad Adnan Khan^6,*, Munir Ahmad³, Saad Alanazi¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4947-4964, 2022, DOI:10.32604/cmc.2022.021104 - 11 October 2021

Abstract Detection of personality using emotions is a research domain in artificial intelligence. At present, some agents can keep the human’s profile for interaction and adapts themselves according to their preferences. However, the effective method for interaction is to detect the person’s personality by understanding the emotions and context of the subject. The idea behind adding personality in cognitive agents begins an attempt to maximize adaptability on the basis of behavior. In our daily life, humans socially interact with each other by analyzing the emotions and context of interaction from audio or visual input. This paper More >

Mesfer Al Duhayyim¹, Haya Mesfer Alshahrani², Fahd N. Al-Wesabi³, Mohammed Alamgeer⁴, Anwer Mustafa Hilal^5,*, Manar Ahmed Hamza⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5871-5887, 2022, DOI:10.32604/cmc.2022.021093 - 11 October 2021

Abstract An exponential growth in advanced technologies has resulted in the exploration of Ocean spaces. It has paved the way for new opportunities that can address questions relevant to diversity, uniqueness, and difficulty of marine life. Underwater Wireless Sensor Networks (UWSNs) are widely used to leverage such opportunities while these networks include a set of vehicles and sensors to monitor the environmental conditions. In this scenario, it is fascinating to design an automated fish detection technique with the help of underwater videos and computer vision techniques so as to estimate and monitor fish biomass in water… More >

Khaled M. Fouad¹ , Basma M. Hassan^2,*, Omar M. Salim³

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4965-4985, 2022, DOI:10.32604/cmc.2022.020926 - 11 October 2021

Abstract

Energy conservation is a crucial issue to extend the lifetime of wireless sensor networks (WSNs) where the battery capacity and energy sources are very restricted. Intelligent energy-saving techniques can help designers overcome this issue by reducing the number of selected sensors that report environmental measurements by eliminating all replicated and unrelated features. This paper suggests a Hybrid Sensor Selection (HSS) technique that combines filter-wrapper method to acquire a rich-informational subset of sensors in a reasonable time. HSS aims to increase the lifetime of WSNs by using the optimal number of sensors. At the same time, HSS

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Atif Naseer^1,*, Enrique Nava Baro¹, Sultan Daud Khan², Yolanda Vila³, Jennifer Doyle⁴

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5321-5344, 2022, DOI:10.32604/cmc.2022.020886 - 11 October 2021

Abstract The Norway lobster, Nephrops norvegicus, is one of the main commercial crustacean fisheries in Europe. The abundance of Nephrops norvegicus stocks is assessed based on identifying and counting the burrows where they live from underwater videos collected by camera systems mounted on sledges. The Spanish Oceanographic Institute (IEO) and Marine Institute Ireland (MI-Ireland) conducts annual underwater television surveys (UWTV) to estimate the total abundance of Nephrops within the specified area, with a coefficient of variation (CV) or relative standard error of less than 20%. Currently, the identification and counting of the Nephrops burrows are carried out manually by… More >