So-Eun Jeon, Sun-Jin Lee, Il-Gu Lee^*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2407-2419, 2023, DOI:10.32604/iasc.2023.039937 - 21 June 2023

Abstract With the development of the 5th generation of mobile communication (5G) networks and artificial intelligence (AI) technologies, the use of the Internet of Things (IoT) has expanded throughout industry. Although IoT networks have improved industrial productivity and convenience, they are highly dependent on nonstandard protocol stacks and open-source-based, poorly validated software, resulting in several security vulnerabilities. However, conventional AI-based software vulnerability discovery technologies cannot be applied to IoT because they require excessive memory and computing power. This study developed a technique for optimizing training data size to detect software vulnerabilities rapidly while maintaining learning accuracy. More >

R. Rema^*, N. Nalanth

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1497-1506, 2023, DOI:10.32604/iasc.2023.032540 - 05 January 2023

Abstract Researchers worldwide have employed a varied array of sources to calculate the successful management of Construction and Demolition (C&DW). Limited research has been undertaken in the domain of Construction and Demolition Waste Management (C&DWM) and consequently leaving a large gap in the availability of effective management techniques. Due to the limited time available for building removal and materials collection, preparing for building materials reuse at the end of life is frequently a challenging task. In this research work Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) is proposed to predict the number of waste materials that are More >

Juan Ramón Bermejo Higuera¹, Javier Bermejo Higuera¹, Juan Antonio Sicilia Montalvo¹, Tomás Sureda Riera², Christopher I. Argyros³, Á. Alberto Magreñán^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 541-565, 2021, DOI:10.32604/cmes.2021.017213 - 08 October 2021

Abstract Security weaknesses in web applications deployed in cloud architectures can seriously affect its data confidentiality and integrity. The construction of the procedure utilized in the static analysis tools of source code security differs and therefore each tool finds a different number of each weakness type for which it is designed. To utilize the possible synergies different static analysis tools may process, this work uses a new method to combine several source codes aiming to investigate how to increase the performance of security weakness detection while reducing the number of false positives. Specifically, five static analysis More >

Roddy A. Correa¹, Juan Ramón Bermejo Higuera², Javier Bermejo Higuera², Juan Antonio Sicilia Montalvo², Manuel Sánchez Rubio², Á. Alberto Magreñán^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 89-124, 2021, DOI:10.32604/cmes.2021.010700 - 22 December 2020

Abstract This study presents a methodology to evaluate and prevent security vulnerabilities issues for web applications. The analysis process is based on the use of techniques and tools that allow to perform security assessments of white box and black box, to carry out the security validation of a web application in an agile and precise way. The objective of the methodology is to take advantage of the synergies of semi-automatic static and dynamic security analysis tools and manual checks. Each one of the phases contemplated in the methodology is supported by security analysis tools of different… More >