Younghoon Ban, Myeonghyun Kim, Haehyun Cho^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3535-3563, 2024, DOI:10.32604/cmes.2023.046658

Abstract Antivirus vendors and the research community employ Machine Learning (ML) or Deep Learning (DL)-based static analysis techniques for efficient identification of new threats, given the continual emergence of novel malware variants. On the other hand, numerous researchers have reported that Adversarial Examples (AEs), generated by manipulating previously detected malware, can successfully evade ML/DL-based classifiers. Commercial antivirus systems, in particular, have been identified as vulnerable to such AEs. This paper firstly focuses on conducting black-box attacks to circumvent ML/DL-based malware classifiers. Our attack method utilizes seven different perturbations, including Overlay Append, Section Append, and Break Checksum,… More >

Tao Xu^1,*, Fangqiang Zuo¹, Kai Zheng^2,*

International Journal of Mental Health Promotion, Vol.26, No.2, pp. 93-103, 2024, DOI:10.32604/ijmhp.2023.043226

Abstract Background: This study aimed to investigate the relationship between parental educational expectations and adolescent mental health problems, with academic pressure as a moderating variable. Methods: This study was based on the baseline data of the China Education Panel Survey, which was collected within one school year during 2013–2014. It included 19,958 samples from seventh and ninth graders, who ranged from 11 to 18 years old. After removing missing values and conducting relevant data processing, the effective sample size for analysis was 16344. The OLS (Ordinary Least Squares) multiple linear regression analysis was used to examine… More >

Shahad Alzahrani¹, Hatim Alsuwat², Emad Alsuwat^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1635-1654, 2024, DOI:10.32604/cmes.2023.044718

Abstract Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables. However, the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data streams. One of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks, wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their performance. In this research paper, we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning algorithms. Our framework… More >

Fayaz Hassan^1,*, Jianguo Yu¹, Zafi Sherhan Syed², Arif Hussain Magsi³, Nadeem Ahmed⁴

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3185-3208, 2023, DOI:10.32604/cmc.2023.044650

Abstract Vehicular Ad-hoc Networks (VANETs) are mobile ad-hoc networks that use vehicles as nodes to create a wireless network. Whereas VANETs offer many advantages over traditional transportation networks, ensuring security in VANETs remains a significant challenge due to the potential for malicious attacks. This study addresses the critical issue of security in VANETs by introducing an intelligent Intrusion Detection System (IDS) that merges Machine Learning (ML)–based attack detection with Explainable AI (XAI) explanations. This study ML pipeline involves utilizing correlation-based feature selection followed by a Random Forest (RF) classifier that achieves a classification accuracy of 100%… More >

Anna Szabina Szele^1,*, Beáta Erika Nagy²

International Journal of Mental Health Promotion, Vol.24, No.5, pp. 699-709, 2022, DOI:10.32604/ijmhp.2022.021809

Abstract Preterm and low birth weight infants are at higher risk of neurodevelopmental outcomes; breastfeeding offers several beneficial aspects for them. This study aimed to describe the average neurodevelopmental outcomes of preterm infants and examine the associations between neurodevelopment and breastfeeding among Hungarian preterm infants at 12 months of corrected age. 154 preterm infants with low birth weight (<2500 g) and their mothers were participated in this study. Bayley-III Screening Test (Bayley Scales of Infant and Toddler Development Screening Test, Third Edition) was administered to measure the cognitive, language and motor skills of infants; breastfeeding data was… More >

Komeil Raisian¹, Jamaiah Yahaya^2,*, Aziz Deraman³

Computer Systems Science and Engineering, Vol.41, No.1, pp. 271-288, 2022, DOI:10.32604/csse.2022.020496

Abstract Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits… More >

Doudou Liu^1,*, Liang Qiao^2,3, Feng Zhang⁴, Xueliang Yuan²

Energy Engineering, Vol.118, No.5, pp. 1395-1409, 2021, DOI:10.32604/EE.2021.014697

Abstract The rapid development of urbanization has led to a rapid increase in total energy consumption. The proportion of domestic energy consumption to total energy consumption has gradually increased and has become the major driving force for energy consumption. With the pressure from urbanization and domestic energy consumption, it is necessary to study the impact of urbanization on domestic energy consumption of the regional level and to explore the function paths of these two factors. The findings are helpful to realize sustainable development based on the actual situation analysis, horizontal survey data and statistical yearbook panel… More >

Qin He¹, Shuang Dong^1,*, Yaxin Cheng¹

Computer Systems Science and Engineering, Vol.34, No.4, pp. 225-230, 2019, DOI:10.32604/csse.2019.34.225

Abstract When studying the various factors affecting a group’s social attitudes, minor changes in a factor will easily cause changes to other factors due to their association and relevance to each other; therefore, such a factor is more sensitive, although there is a difference between sensitivity and importance. In order to comprehensively learn about the influence of multiple factors, explorations based on entropy theory have been conducted to determine the sensitivity of each factor, to specify the difference between the frequency and sensitivity priority of entropy theory, and to provide a method, a way of thinking, More >