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  • Open Access

    ARTICLE

    Enhancing Ransomware Resilience in Cloud-Based HR Systems through Moving Target Defense

    Jay Barach*

    CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.071705 - 09 December 2025

    Abstract Human Resource (HR) operations increasingly rely on cloud-based platforms that provide hiring, payroll, employee management, and compliance services. These systems, typically built on multi-tenant microservice architectures, offer scalability and efficiency but also expand the attack surface for adversaries. Ransomware has emerged as a leading threat in this domain, capable of halting workflows and exposing sensitive employee records. Traditional defenses such as static hardening and signature-based detection often fail to address the dynamic requirements of HR Software as a Service (SaaS), where continuous availability and privacy compliance are critical. This paper presents a Moving Target Defense… More >

  • Open Access

    ARTICLE

    Distributed Photovoltaic Power Prediction Technology Based on Spatio-Temporal Graph Neural Networks

    Dayan Sun1, Xiao Cao2,*, Zhifeng Liang1, Junrong Xia2, Yuqi Wang3

    Energy Engineering, Vol.122, No.8, pp. 3329-3346, 2025, DOI:10.32604/ee.2025.066341 - 24 July 2025

    Abstract Photovoltaic (PV) power generation is undergoing significant growth and serves as a key driver of the global energy transition. However, its intermittent nature, which fluctuates with weather conditions, has raised concerns about grid stability. Accurate PV power prediction has been demonstrated as crucial for power system operation and scheduling, enabling power slope control, fluctuation mitigation, grid stability enhancement, and reliable data support for secure grid operation. However, existing prediction models primarily target centralized PV plants, largely neglecting the spatiotemporal coupling dynamics and output uncertainties inherent to distributed PV systems. This study proposes a novel Spatio-Temporal… More >

  • Open Access

    ARTICLE

    Detecting and Preventing of Attacks in Cloud Computing Using Hybrid Algorithm

    R. S. Aashmi1, T. Jaya2,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 79-95, 2023, DOI:10.32604/iasc.2023.024291 - 06 June 2022

    Abstract

    Cloud computing is the technology that is currently used to provide users with infrastructure, platform, and software services effectively. Under this system, Platform as a Service (PaaS) offers a medium headed for a web development platform that uniformly distributes the requests and resources. Hackers using Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks abruptly interrupt these requests. Even though several existing methods like signature-based, statistical anomaly-based, and stateful protocol analysis are available, they are not sufficient enough to get rid of Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks

    More >

  • Open Access

    ARTICLE

    Prevention of Runtime Malware Injection Attack in Cloud Using Unsupervised Learning

    M. Prabhavathy1,*, S. UmaMaheswari2

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 101-114, 2022, DOI:10.32604/iasc.2022.018257 - 26 October 2021

    Abstract Cloud computing utilizes various Internet-based technologies to enhance the Internet user experience. Cloud systems are on the rise, as this technology has completely revolutionized the digital industry. Currently, many users rely on cloud-based solutions to acquire business information and knowledge. As a result, cloud computing services such as SaaS and PaaS store a warehouse of sensitive and valuable information, which has turned the cloud systems into the obvious target for many malware creators and hackers. These malicious attackers attempt to gain illegal access to a myriad of valuable information such as user personal information, password, More >

  • Open Access

    ARTICLE

    Investigating the Role of Trust Dimension as a Mediator on CC-SaaS Adoption

    Hiba Jasim Hadi*, Mohd Adan Omar, Wan Rozaini Sheik Osman

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 373-386, 2021, DOI:10.32604/iasc.2021.018207 - 16 June 2021

    Abstract The public sector of Iraq has been struggling from poor management of resources and numerous difficulties that affect its governmental organization’s development, such as financial issues resulting from corruption, insecurity, and the lack of IT resources and infrastructure. Thus, cloud computing Software as a Service (CC-SaaS) can be a useful solution to help governmental organizations increase their service efficiency through the adoption of low-cost technology and provision of better services. The adoption of CC-SaaS remains limited in Iraqi public organizations due to numerous challenges, including privacy and protection, legal policy, and trust. Trust was found… More >

  • Open Access

    ARTICLE

    A Performance Fault Diagnosis Method for SaaS Software Based on GBDT Algorithm

    Kun Zhu1, Shi Ying1, *, Nana Zhang1, Rui Wang1, Yutong Wu1, Gongjin Lan2, Xu Wang2

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1161-1185, 2020, DOI:10.32604/cmc.2020.05247

    Abstract SaaS software that provides services through cloud platform has been more widely used nowadays. However, when SaaS software is running, it will suffer from performance fault due to factors such as the software structural design or complex environments. It is a major challenge that how to diagnose software quickly and accurately when the performance fault occurs. For this challenge, we propose a novel performance fault diagnosis method for SaaS software based on GBDT (Gradient Boosting Decision Tree) algorithm. In particular, we leverage the monitoring mean to obtain the performance log and warning log when the… More >

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