Shinjin Kang¹, Soo Kyun Kim^2,*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3725-3736, 2021, DOI:10.32604/cmc.2021.016828 - 06 May 2021

Abstract In this study, we propose a low-cost system that can detect the space outlier utilization of residents in an indoor environment. We focus on the users’ app usage to analyze unusual behavior, especially in indoor spaces. This is reflected in the behavioral analysis in that the frequency of using smartphones in personal spaces has recently increased. Our system facilitates autonomous data collection from mobile app logs and Google app servers and generates a high-dimensional dataset that can detect outlier behaviors. The density-based spatial clustering of applications with noise (DBSCAN) algorithm was applied for effective singular… More >

Kathiravan Srinivasan¹, Lalit Garg^2,*, Debajit Datta³, Abdulellah A. Alaboudi⁴, N. Z. Jhanjhi⁵, Rishav Agarwal³, Anmol George Thomas¹

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4109-4124, 2021, DOI:10.32604/cmc.2021.016736 - 06 May 2021

Abstract According to various worldwide statistics, most car accidents occur solely due to human error. The person driving a car needs to be alert, especially when travelling through high traffic volumes that permit high-speed transit since a slight distraction can cause a fatal accident. Even though semi-automated checks, such as speed detecting cameras and speed barriers, are deployed, controlling human errors is an arduous task. The key causes of driver’s distraction include drunken driving, conversing with co-passengers, fatigue, and operating gadgets while driving. If these distractions are accurately predicted, the drivers can be alerted through an More >

Romany F. Mansour^1,*, Shaha Al-Otaibi², Amal Al-Rasheed², Hanan Aljuaid³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2843-2858, 2021, DOI:10.32604/cmc.2021.016626 - 06 May 2021

Abstract Big data streams started becoming ubiquitous in recent years, thanks to rapid generation of massive volumes of data by different applications. It is challenging to apply existing data mining tools and techniques directly in these big data streams. At the same time, streaming data from several applications results in two major problems such as class imbalance and concept drift. The current research paper presents a new Multi-Objective Metaheuristic Optimization-based Big Data Analytics with Concept Drift Detection (MOMBD-CDD) method on High-Dimensional Streaming Data. The presented MOMBD-CDD model has different operational stages such as pre-processing, CDD, and… More >

Osamah Ibrahim Khalaf¹, Munsif Sokiyna^2,*, Youseef Alotaibi³, Abdulmajeed Alsufyani⁴, Saleh Alghamdi⁵

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3167-3184, 2021, DOI:10.32604/cmc.2021.016099 - 06 May 2021

Abstract A major issue while building web applications is proper input validation and sanitization. Attackers can quickly exploit errors and vulnerabilities that lead to malicious behavior in web application validation operations. Attackers are rapidly improving their capabilities and technologies and now focus on exploiting vulnerabilities in web applications and compromising confidentiality. Cross-site scripting (XSS) and SQL injection attack (SQLIA) are attacks in which a hacker sends malicious inputs (cheat codes) to confuse a web application, to access or disable the application’s back-end without user awareness. In this paper, we explore the problem of detecting and removing… More >

Sajid Habib Gill¹, Noor Ahmed Sheikh¹, Samina Rajpar¹, Zain ul Abidin², N. Z. Jhanjhi^3,*, Muneer Ahmad⁴, Mirza Abdur Razzaq¹, Sultan S. Alshamrani⁵, Yasir Malik⁶, Fehmi Jaafar⁷

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3773-3787, 2021, DOI:10.32604/cmc.2021.016001 - 06 May 2021

Abstract Medical data tampering has become one of the main challenges in the field of secure-aware medical data processing. Forgery of normal patients’ medical data to present them as COVID-19 patients is an illegitimate action that has been carried out in different ways recently. Therefore, the integrity of these data can be questionable. Forgery detection is a method of detecting an anomaly in manipulated forged data. An appropriate number of features are needed to identify an anomaly as either forged or non-forged data in order to find distortion or tampering in the original data. Convolutional neural… More >

D. Venugopal¹, T. Jayasankar², Mohamed Yacin Sikkandar³, Mohamed Ibrahim Waly³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵, K. Shankar^6,*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2877-2893, 2021, DOI:10.32604/cmc.2021.015480 - 06 May 2021

Abstract Data fusion is one of the challenging issues, the healthcare sector is facing in the recent years. Proper diagnosis from digital imagery and treatment are deemed to be the right solution. Intracerebral Haemorrhage (ICH), a condition characterized by injury of blood vessels in brain tissues, is one of the important reasons for stroke. Images generated by X-rays and Computed Tomography (CT) are widely used for estimating the size and location of hemorrhages. Radiologists use manual planimetry, a time-consuming process for segmenting CT scan images. Deep Learning (DL) is the most preferred method to increase the… More >

Chungen Xu^1,*, Lin Mei¹, Jinxue Cheng², Yu Zhao¹, Cong Zuo³

Journal of Cyber Security, Vol.3, No.1, pp. 55-67, 2021, DOI:10.32604/jcs.2021.017217 - 30 April 2021

Abstract With the rapid development of wireless communication technology, the Internet of Things is playing an increasingly important role in our everyday. The amount of data generated by sensor devices is increasing as a large number of connectable devices are deployed in many fields, including the medical, agricultural, and industrial areas. Uploading data to the cloud solves the problem of data overhead but results in privacy issues. Therefore, the question of how to manage the privacy of uploading data and make it available to be interconnected between devices is a crucial issue. In this paper, we More >

Zhangjie Fu^1,2,3,*, Yongjie Ding¹, Musaazi Godfrey¹

Journal of Cyber Security, Vol.3, No.1, pp. 11-28, 2021, DOI:10.32604/jcs.2021.016632 - 30 April 2021

Abstract Mobile malware occupies a considerable proportion of cyberattacks. With the update of mobile device operating systems and the development of software technology, more and more new malware keep appearing. The emergence of new malware makes the identification accuracy of existing methods lower and lower. There is an urgent need for more effective malware detection models. In this paper, we propose a new approach to mobile malware detection that is able to detect newly-emerged malware instances. Firstly, we build and train the LSTM-based model on original benign and malware samples investigated by both static and dynamic More >

Yu Xue^1,2,*, Xu Cai¹, Shoubao Su², Junxiang Han¹, Romany F. Mansour³

Journal of Cyber Security, Vol.3, No.1, pp. 1-10, 2021, DOI:10.32604/jcs.2021.016371 - 30 April 2021

Abstract According to some data in the Industrial Purchasing Trends report released by China in 2017, we can see that e-commerce purchasing channels have ranked first among all industrial products purchasing channels in China compared with European and American countries. In addition, in the whole industrial product purchasing market, we can also see that both manufacturers and suppliers are making active e-commerce transformation, and some other Internet giants are also actively entering the industrial product e-commerce industry. But at present, the revenue of all kinds of subjects is still a lot of room for improvement compared… More >

Peng Wan¹, Ting Wen^2,*, Yunfei Zhang³, Hong Gao¹, Jigan Wang¹

International Journal of Mental Health Promotion, Vol.23, No.2, pp. 201-219, 2021, DOI:10.32604/IJMHP.2021.015759 - 30 April 2021

Abstract Goal self-concordance reflects self-generated personal goals aligning with people’s interests and core values in one’s implicit personality as organic components, which is measured by the “perceived locus of causality” PLOC. Pursuing and achieving self-concordant goals both predict diversified outcomes in need-satisfaction, mental and physical well-being, positive attitude and behavior, etc. Based on expounding and sorting out the concept and measurement about goal self-concordance, the author analyzes the differences among a series of goal self-concordance theories. This paper focuses on the latest research trends and summarizes five influencing aspects of goal self-concordance: mental health, cognition, emotion, More >