Hoon Ko¹, Marek R. Ogiela^2,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 259-278, 2025, DOI:10.32604/cmc.2024.057257 - 03 January 2025

Abstract This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology. By combining the strengths of blockchain and generative AI, the research team aimed to address the timely challenge of safeguarding visual medical content. The participating researchers conducted a comprehensive analysis, examining the vulnerabilities of medical AI services, personal information protection issues, and overall security weaknesses. This multifaceted exploration led to an in-depth evaluation of the model’s performance and security. Notably, the correlation between accuracy, detection rate, and error rate was… More >

Carlos Merlano^*

Journal of Cyber Security, Vol.6, pp. 89-116, 2024, DOI:10.32604/jcs.2024.056164 - 06 December 2024

Abstract The constantly increasing degree and frequency of cyber threats require the emergence of flexible and intelligent approaches to systems’ protection. Despite the calls for the use of artificial intelligence (AI) and machine learning (ML) in strengthening cyber security, there needs to be more literature on an integrated view of the application areas, open issues or trends in AI and ML for cyber security. Based on 90 studies, in the following literature review, the author categorizes and systematically analyzes the current research field to fill this gap. The review evidences that, in contrast to rigid rule-based… More >

Guan-Yan Yang^1,*, Yi-Heng Ko¹, Farn Wang¹, Kuo-Hui Yeh², Haw-Shiang Chang¹, Hsueh Yi Chen¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-4, 2024, DOI:10.32604/icces.2024.013297

Abstract 1 Introduction
Ensuring the absence of exploitable vulnerabilities within applications has always been a critical aspect of software development [1-3]. Traditional code security testing methods often rely on manual inspection or rule-based approaches, which can be time-consuming and prone to human errors. With the recent advancements in natural language processing, deep learning has emerged as a viable approach for code security testing. In this work, we investigated the application of deep learning techniques to code security testing to enhance the efficiency and effectiveness of security analysis in the software development process. In 2022, Wartschinski et al.… More >

Jiaojiao Wu^1,#, Dou Fu^2,#, Lili Zhang^1,*, Xiangying Xie³, Xinmei Wang², Xiangying Shen¹, Shanshan Liu², Xu Xu⁴, Hui Cheng⁵, Xiaojie Ma¹, Doudou Lin¹

International Journal of Mental Health Promotion, Vol.26, No.11, pp. 897-904, 2024, DOI:10.32604/ijmhp.2024.056223 - 28 November 2024

Abstract Background: With the rapid aging of China’s population and the increasing prevalence of comorbidities in the elderly, psychological crises have become more common. This study aims to investigate the present status of psychological vulnerability, aging attitudes, and life meaning in elderly patients with comorbidities. Methods: A total of 685 elderly inpatients and outpatients at Renmin Hospital of Wuhan University between July and December 2022 were selected using the simple random sampling method. Social demographic data were collected, and the Attitudes to aging Questionnaire (AAQ), the Chinese Life Meaning Questionnaire (C-MLQ), and the Psychological Vulnerability Scale… More >

Tao Zheng¹, Rui Tang^1,2,3, Xingshu Chen^1,2,3,*, Changxiang Shen¹

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1595-1612, 2024, DOI:10.32604/cmc.2024.055180 - 15 October 2024

Abstract RESTful API fuzzing is a promising method for automated vulnerability detection in Kubernetes platforms. Existing tools struggle with generating lengthy, high-semantic request sequences that can pass Kubernetes API gateway checks. To address this, we propose KubeFuzzer, a black-box fuzzing tool designed for Kubernetes RESTful APIs. KubeFuzzer utilizes Natural Language Processing (NLP) to extract and integrate semantic information from API specifications and response messages, guiding the generation of more effective request sequences. Our evaluation of KubeFuzzer on various Kubernetes clusters shows that it improves code coverage by 7.86% to 36.34%, increases the successful response rate by More >

Bum-Sok Kim¹, Hye-Won Suk¹, Yong-Hoon Choi², Dae-Sung Moon³, Min-Suk Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1551-1574, 2024, DOI:10.32604/cmes.2024.052375 - 27 September 2024

Abstract Currently, cybersecurity threats such as data breaches and phishing have been on the rise due to the many different attack strategies of cyber attackers, significantly increasing risks to individuals and organizations. Traditional security technologies such as intrusion detection have been developed to respond to these cyber threats. Recently, advanced integrated cybersecurity that incorporates Artificial Intelligence has been the focus. In this paper, we propose a response strategy using a reinforcement-learning-based cyber-attack-defense simulation tool to address continuously evolving cyber threats. Additionally, we have implemented an effective reinforcement-learning-based cyber-attack scenario using Cyber Battle Simulation, which is a… More >

Li-Anne Gacul¹, Dexter Ferrancullo¹, Romel Gallano¹, KC Jane Fadriquela¹, Kyla Jane Mendez¹, John Rommel Morada¹, John Kevin Morgado¹, Jerome Gacu^1,2,*

Revue Internationale de Géomatique, Vol.33, pp. 295-320, 2024, DOI:10.32604/rig.2024.055085 - 03 September 2024

Abstract Risk assessment is vital for humanities, especially in assessing natural and manmade hazards. Romblon, an archipelagic province in the Philippines, faces frequent typhoons and heavy rainfall, resulting in floods, with the Municipality of Santa Fe being particularly vulnerable to its severe damage. Thus, this research study intends to evaluate the flood risk of Santa Fe spatially using the fuzzy analytical hierarchy process (FAHP), taking into account data sourced from various government agencies and online databases. GIS was utilized to map flood-prone areas in the municipality. Hazard assessment factors included average annual rainfall, elevation, slope, soil… More > Graphic Abstract

Shibin Zhao^*, Junhu Zhu, Jianshan Peng

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3263-3287, 2024, DOI:10.32604/cmc.2024.041949 - 15 August 2024

Abstract In recent years, the rapid development of computer software has led to numerous security problems, particularly software vulnerabilities. These flaws can cause significant harm to users’ privacy and property. Current security defect detection technology relies on manual or professional reasoning, leading to missed detection and high false detection rates. Artificial intelligence technology has led to the development of neural network models based on machine learning or deep learning to intelligently mine holes, reducing missed alarms and false alarms. So, this project aims to study Java source code defect detection methods for defects like null pointer… More >

Yaqiong He, Jinlin Fan^*, Huaiguang Wu

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 995-1032, 2024, DOI:10.32604/cmc.2024.052887 - 18 July 2024

Abstract With the rise of blockchain technology, the security issues of smart contracts have become increasingly critical. Despite the availability of numerous smart contract vulnerability detection tools, many face challenges such as slow updates, usability issues, and limited installation methods. These challenges hinder the adoption and practicality of these tools. This paper examines smart contract vulnerability detection tools from 2016 to 2023, sourced from the Web of Science (WOS) and Google Scholar. By systematically collecting, screening, and synthesizing relevant research, 38 open-source tools that provide installation methods were selected for further investigation. From a developer’s perspective,… More >

Jiawei Qin^1,2, Hua Zhang^1,*, Hanbing Yan², Tian Zhu², Song Hu¹, Dingyu Yan²

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 527-544, 2024, DOI:10.32604/iasc.2024.047509 - 11 July 2024

Abstract By the analysis of vulnerabilities of Android native system services, we find that some vulnerabilities are caused by inconsistent data transmission and inconsistent data processing logic between client and server. The existing research cannot find the above two types of vulnerabilities and the test cases of them face the problem of low coverage. In this paper, we propose an extraction method of test cases based on the native system services of the client and design a case construction method that supports multi-parameter mutation based on genetic algorithm and priority strategy. Based on the above method, More >