Nu Ri Song^1,#, Seo Yeon Shin^1,#, Ki Min Kim¹, Sa Rang Choi¹, Doo Sang Park², Sun Oh Kim³, Dai Hyun Jung⁴, Kyung Mok Park^1,*

BIOCELL, Vol.49, No.7, pp. 1291-1310, 2025, DOI:10.32604/biocell.2025.065467 - 25 July 2025

Abstract Objectives: Limosilactobacillus reuteri is a beneficial Lactobacillus widely used in foods and supplements to promote overall health. Some studies also suggest it supports skin health and prevents allergies and cardiovascular disease. However, research on its skin-protective effects against photoaging has not been conducted. This study evaluated the potential of culture broths from three L. reuteri strains (DS0333, DS0384, and DS0385) to inhibit skin photoaging. Methods: To assess their anti-photoaging potential, the culture broths were examined for antioxidant capacity, melanin inhibition, and collagen synthesis promotion. Radical scavenging activity was tested using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2^′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays.… More > Graphic Abstract

Fang Xu^1,2,#, Wan Li^1,#, Xiang-Jin Zheng^1,2, Yue Hao^1,2, Yi-Hui Yang^1,2, Hong Yang^1,2, Sen Zhang^1,2, Wan-Xin Cao^1,2, Xiao-Xue Li^1,2, Xu Zhang^1,2, Guan-Hua Du^1,2, Teng-Fei Ji^1,*, Jin-Hua Wang^1,2,*

Oncology Research, Vol.33, No.8, pp. 1969-1989, 2025, DOI:10.32604/or.2025.062386 - 18 July 2025

Abstract Objectives: Colorectal cancer (CRC) is one of the most common cancers all over the world. The progression of CRC is associated with inflammation and disruptions in intestinal flora. 3-O-Acetyl-11-keto-β-boswellic acid (AKBA) has been noted for its potent anti-inflammatory properties. However, the effect of AKBA on colon cancer caused by inflammation and its mechanism are not unclear. The study is to explore the effect of AKBA on CRC and its mechanism. Materials and Methods: Cell proliferation, (5-ethynyl-2^′-deoxyuridine, EdU)-DNA synthesis assay and colony formation were used to assess the effect of AKBA on the proliferation of CRC cells.… More >

Akhila Reddy Yadulla, Mounica Yenugula, Vinay Kumar Kasula^*, Bhargavi Konda, Bala Yashwanth Reddy Thumma

Journal on Internet of Things, Vol.7, pp. 19-48, 2025, DOI:10.32604/jiot.2025.062733 - 11 July 2025

Abstract This study systematically reviews the Internet of Things (IoT) security research based on literature from prominent international cybersecurity conferences over the past five years, including ACM Conference on Computer and Communications Security (ACM CCS), USENIX Security, Network and Distributed System Security Symposium (NDSS), and IEEE Symposium on Security and Privacy (IEEE S&P), along with other high-impact studies. It organizes and analyzes IoT security advancements through the lenses of threats, detection methods, and defense strategies. The foundational architecture of IoT systems is first outlined, followed by categorizing major threats into eight distinct types and analyzing their More >

Fatima Asiri¹, Wajdan Al Malwi¹, Fahad Masood², Mohammed S. Alshehri³, Tamara Zhukabayeva⁴, Syed Aziz Shah⁵, Jawad Ahmad^6,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3943-3960, 2025, DOI:10.32604/cmc.2025.066498 - 03 July 2025

Abstract Edge computing (EC) combined with the Internet of Things (IoT) provides a scalable and efficient solution for smart homes. The rapid proliferation of IoT devices poses real-time data processing and security challenges. EC has become a transformative paradigm for addressing these challenges, particularly in intrusion detection and anomaly mitigation. The widespread connectivity of IoT edge networks has exposed them to various security threats, necessitating robust strategies to detect malicious activities. This research presents a privacy-preserving federated anomaly detection framework combined with Bayesian game theory (BGT) and double deep Q-learning (DDQL). The proposed framework integrates BGT… More >

Tatsuhito Hasegawa^#,*, Kyosuke Fujino^#

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2429-2454, 2025, DOI:10.32604/cmc.2025.066270 - 03 July 2025

Abstract Recent advances in wearable devices have enabled large-scale collection of sensor data across healthcare, sports, and other domains but this has also raised critical privacy concerns, especially under tightening regulations such as the General Data Protection Regulation (GDPR), which explicitly restrict the processing of data that can re-identify individuals. Although existing anonymization approaches such as the Anonymizing AutoEncoder (AAE) can reduce the risk of re-identification, they often introduce substantial waveform distortions and fail to preserve information beyond a single classification task (e.g., human activity recognition). This study proposes a novel sensor data anonymization method based… More >

Subrata Kumer Paul^1,2, Abu Saleh Musa Miah^3,4, Rakhi Rani Paul^1,2, Md. Ekramul Hamid², Jungpil Shin^4,*, Md Abdur Rahim⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2513-2530, 2025, DOI:10.32604/cmc.2025.063563 - 03 July 2025

Abstract The Internet of Things (IoT) and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients. Recognizing Medical-Related Human Activities (MRHA) is pivotal for healthcare systems, particularly for identifying actions critical to patient well-being. However, challenges such as high computational demands, low accuracy, and limited adaptability persist in Human Motion Recognition (HMR). While some studies have integrated HMR with IoT for real-time healthcare applications, limited research has focused on recognizing MRHA as essential for effective patient monitoring. This study proposes a novel HMR method tailored for MRHA detection, leveraging multi-stage deep… More >

Yu-Bin Kim, Dong-Hyuk Shin, Ieck-Chae Euom^*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2217-2243, 2025, DOI:10.32604/cmc.2025.063289 - 03 July 2025

Abstract The global surge in electric vehicle (EV) adoption is proportionally expanding the EV charging station (EVCS) infrastructure, thereby increasing the attack surface and potential impact of security breaches within this critical ecosystem. While ISO 15118 standardizes EV-EVCS communication, its underspecified security guidelines and the variability in manufacturers’ implementations frequently result in vulnerabilities that can disrupt charging services, compromise user data, or affect power grid stability. This research introduces a systematic black-box fuzzing methodology, accompanied by an open-source tool, to proactively identify and mitigate such security flaws in EVCS firmware operating under ISO 15118. The proposed… More >

Jitendra Kumar Samriya¹, Virendra Singh², Gourav Bathla³, Meena Malik⁴, Varsha Arya^5,6, Wadee Alhalabi⁷, Brij B. Gupta^8,9,10,11,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3893-3910, 2025, DOI:10.32604/cmc.2025.063242 - 03 July 2025

Abstract The integration of the Internet of Things (IoT) into healthcare systems improves patient care, boosts operational efficiency, and contributes to cost-effective healthcare delivery. However, overcoming several associated challenges, such as data security, interoperability, and ethical concerns, is crucial to realizing the full potential of IoT in healthcare. Real-time anomaly detection plays a key role in protecting patient data and maintaining device integrity amidst the additional security risks posed by interconnected systems. In this context, this paper presents a novel method for healthcare data privacy analysis. The technique is based on the identification of anomalies in… More >

Kirubavathi G.^1,*, Arjun Pulliyasseri¹, Aswathi Rajesh¹, Amal Ajayan¹, Sultan Alfarhood^2,*, Mejdl Safran², Meshal Alfarhood², Jungpil Shin³

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3005-3031, 2025, DOI:10.32604/cmes.2025.065698 - 30 June 2025

Abstract The exponential expansion of the Internet of Things (IoT), Industrial Internet of Things (IIoT), and Transportation Management of Things (TMoT) produces vast amounts of real-time streaming data. Ensuring system dependability, operational efficiency, and security depends on the identification of anomalies in these dynamic and resource-constrained systems. Due to their high computational requirements and inability to efficiently process continuous data streams, traditional anomaly detection techniques often fail in IoT systems. This work presents a resource-efficient adaptive anomaly detection model for real-time streaming data in IoT systems. Extensive experiments were carried out on multiple real-world datasets, achieving… More >

Sunghyun Yu, Yoojae Won^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3943-3980, 2025, DOI:10.32604/cmes.2025.064997 - 30 June 2025

Abstract Pre-Authentication and Post-Connection (PAPC) plays a crucial role in realizing the Zero Trust security model by ensuring that access to network resources is granted only after successful authentication. While earlier approaches such as Port Knocking (PK) and Single Packet Authorization (SPA) introduced pre-authentication concepts, they suffer from limitations including plaintext communication, protocol dependency, reliance on dedicated clients, and inefficiency under modern network conditions. These constraints hinder their applicability in emerging distributed and resource-constrained environments such as AIoT and browser-based systems. To address these challenges, this study proposes a novel port-sequence-based PAPC scheme structured as a… More >