Min-Gyu Kim¹, Hwankuk Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 585-607, 2024, DOI:10.32604/cmes.2024.051221 - 20 August 2024

Abstract In the IoT (Internet of Things) domain, the increased use of encryption protocols such as SSL/TLS, VPN (Virtual Private Network), and Tor has led to a rise in attacks leveraging encrypted traffic. While research on anomaly detection using AI (Artificial Intelligence) is actively progressing, the encrypted nature of the data poses challenges for labeling, resulting in data imbalance and biased feature extraction toward specific nodes. This study proposes a reconstruction error-based anomaly detection method using an autoencoder (AE) that utilizes packet metadata excluding specific node information. The proposed method omits biased packet metadata such as… More >

Ruchun Jia, Jianwei Zhang^*, Yi Lin

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2391-2418, 2024, DOI:10.32604/cmc.2024.044149 - 27 February 2024

Abstract With the popularization of the Internet and the development of technology, cyber threats are increasing day by day. Threats such as malware, hacking, and data breaches have had a serious impact on cybersecurity. The network security environment in the era of big data presents the characteristics of large amounts of data, high diversity, and high real-time requirements. Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats. This paper proposes a machine-learning security defense algorithm based on metadata association features. Emphasize control over unauthorized users through… More >

Adnan Ali¹, Jinlong Li¹, Huanhuan Chen¹, Uzair Aslam Bhatti², Asad Khan^3,*

Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 241-258, 2023, DOI:10.32604/iasc.2023.041645 - 27 February 2024

Abstract Spammer detection is to identify and block malicious activities performing users. Such users should be identified and terminated from social media to keep the social media process organic and to maintain the integrity of online social spaces. Previous research aimed to find spammers based on hybrid approaches of graph mining, posted content, and metadata, using small and manually labeled datasets. However, such hybrid approaches are unscalable, not robust, particular dataset dependent, and require numerous parameters, complex graphs, and natural language processing (NLP) resources to make decisions, which makes spammer detection impractical for real-time detection. For… More >

Naseer Ahmed Sajid¹, Munir Ahmad¹, Atta-ur Rahman^2,*, Gohar Zaman³, Mohammed Salih Ahmed⁴, Nehad Ibrahim², Mohammed Imran B. Ahmed⁴, Gomathi Krishnasamy⁶, Reem Alzaher², Mariam Alkharraa², Dania AlKhulaifi², Maryam AlQahtani², Asiya A. Salam⁶, Linah Saraireh⁵, Mohammed Gollapalli⁶, Rashad Ahmed⁷

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2195-2214, 2023, DOI:10.32604/csse.2023.033844 - 09 February 2023

Abstract From the beginning, the process of research and its publication is an ever-growing phenomenon and with the emergence of web technologies, its growth rate is overwhelming. On a rough estimate, more than thirty thousand research journals have been issuing around four million papers annually on average. Search engines, indexing services, and digital libraries have been searching for such publications over the web. Nevertheless, getting the most relevant articles against the user requests is yet a fantasy. It is mainly because the articles are not appropriately indexed based on the hierarchies of granular subject classification. To… More >

Jongyun Choi¹, Hyesoo Kong², Hwamook Yoon², Heungseon Oh³, Yuchul Jung^1,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4019-4037, 2022, DOI:10.32604/cmc.2022.025711 - 29 March 2022

Abstract The volume of academic literature, such as academic conference papers and journals, has increased rapidly worldwide, and research on metadata extraction is ongoing. However, high-performing metadata extraction is still challenging due to diverse layout formats according to journal publishers. To accommodate the diversity of the layouts of academic journals, we propose a novel LAyout-aware Metadata Extraction (LAME) framework equipped with the three characteristics (e.g., design of automatic layout analysis, construction of a large meta-data training set, and implementation of metadata extractor). In the framework, we designed an automatic layout analysis using PDFMiner. Based on the More >

R. Punithavathi^1,*, M. Kowsigan², R. Shanthakumari³, Miodrag Zivkovic⁴, Nebojsa Bacanin⁴, Marko Sarac⁴

Computer Systems Science and Engineering, Vol.42, No.1, pp. 105-120, 2022, DOI:10.32604/csse.2022.020486 - 02 December 2021

Abstract At present, health care applications, government services, and banking applications use big data with cloud storage to process and implement data. Data mobility in cloud environments uses protection protocols and algorithms to secure sensitive user data. Sometimes, data may have highly sensitive information, leading users to consider using big data and cloud processing regardless of whether they are secured are not. Threats to sensitive data in cloud systems produce high risks, and existing security methods do not provide enough security to sensitive user data in cloud and big data environments. At present, several security solutions… More >

Abdullah Baz¹, Mohammed Baz^2,*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1051-1069, 2022, DOI:10.32604/iasc.2022.020304 - 22 September 2021

Abstract COVID-19 constitutes one of the devastating pandemics plaguing humanity throughout the centuries; within about 18 months since its appearing, the cumulative confirmed cases hit 173 million, whereas the death toll approaches 3.72 million. Although several vaccines became available for the public worldwide, the speed with which COVID-19 is spread, and its different mutant strains hinder stopping its outbreak. This, in turn, prompting the desperate need for devising fast, cheap and accurate tools via which the disease can be diagnosed in its early stage. Reverse Transcription Polymerase Chain Reaction (RTPCR) test is the mainstay tool used… More >

Muhammad Yahya Saeed¹, Muhammad Awais¹, Muhammad Younas¹, Muhammad Arif Shah^2,*, Atif Khan³, M. Irfan Uddin⁴, Marwan Mahmoud⁵

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2409-2423, 2021, DOI:10.32604/cmc.2021.014330 - 28 December 2020

Abstract Text Summarization is an essential area in text mining, which has procedures for text extraction. In natural language processing, text summarization maps the documents to a representative set of descriptive words. Therefore, the objective of text extraction is to attain reduced expressive contents from the text documents. Text summarization has two main areas such as abstractive, and extractive summarization. Extractive text summarization has further two approaches, in which the first approach applies the sentence score algorithm, and the second approach follows the word embedding principles. All such text extractions have limitations in providing the basic… More >