Shihao Zhou¹, Ziyuan Xu^3,4, Jin Han^1,*, Xingming Sun^1,2, Yi Cao⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5995-6009, 2022, DOI:10.32604/cmc.2022.023316

Abstract In recent years, academic misconduct has been frequently exposed by the media, with serious impacts on the academic community. Current research on academic misconduct focuses mainly on detecting plagiarism in article content through the application of character-based and non-text element detection techniques over the entirety of a manuscript. For the most part, these techniques can only detect cases of textual plagiarism, which means that potential culprits can easily avoid discovery through clever editing and alterations of text content. In this paper, we propose an academic misconduct detection method based on scholars’ submission behaviors. The model… More >

MUBASHIR HUSSAIN¹, ZEESHAN ALI¹, BIN LIU², JIANGUO DAI¹, XIAOLONG LIU¹, JUNCHEN ZHU¹, YONGJUN TANG¹

BIOCELL, Vol.46, No.1, pp. 61-74, 2022, DOI:10.32604/biocell.2022.016392

Abstract Dengue virus infections are increasing worldwide generally and in Asia, Central and South America and Africa, particularly. It poses a serious threat to the children population. The rapid and accurate diagnostic systems are essentially required due to lack of effective vaccine against dengue virus and the progressive spread of the dengue virus infection. The recent progress in developing micro- and nano-fabrication techniques has led to low cost and scale down the biomedical point-of-care devices. Starting from the conventional and modern available methods for the diagnosis of dengue infection, this review examines several emerging rapid and More >

Taifeng Pan^*

Journal of Quantum Computing, Vol.3, No.4, pp. 161-171, 2021, DOI:10.32604/jqc.2021.025373

Abstract The rapid development of Internet of Things (IoT) technology has brought great convenience to people’s life. However, the security protection capability of IoT is weak and vulnerable. Therefore, more protection needs to be done for the security of IoT. The paper proposes an intrusion detection method for IoT based on multi GBDT feature reduction and hierarchical traffic detection model. Firstly, GBDT is used to filter the features of IoT traffic data sets BoT-IoT and UNSW-NB15 to reduce the traffic feature dimension. At the same time, in order to improve the reliability of feature filtering, this… More >

Yabin Xu^1,2,*, Peiyuan Gu², Xiaowei Xu³

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 113-127, 2021, DOI:10.32604/iasc.2021.018895

Abstract In order to effectively detect interest flooding attack (IFA) in Named Data Networking (NDN), this paper proposes a detection method of interest flooding attack based on chi-square test and similarity test. Firstly, it determines the detection window size based on the distribution of information name prefixes (that is information entropy) in the current network traffic. The attackers may append arbitrary random suffix to a certain prefix in the network traffic, and then send a large number of interest packets that cannot get the response. Targeted at this problem, the sensitivity of chi-square test is used… More >

Yabin Xu^1,2,*, Meishu Zhang², Xiaowei Xu³

Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 17-28, 2021, DOI:10.32604/jihpp.2021.017497

Abstract In order to quickly and accurately find the implementer of the network crime, based on the user portrait technology, a rapid detection method for users with abnormal behaviorsis proposed. This method needs to construct the abnormal behavior rule base on various kinds of abnormal behaviors in advance, and construct the user portrait including basic attribute tags, behavior attribute tags and abnormal behavior similarity tagsfor network users who have abnormal behaviors. When a network crime occurs, firstly get the corresponding tag values in all user portraits according to the category of the network crime. Then, use More >

Kunkun Wang^1,2, Xianda Liu^2,3,4,*

Journal on Artificial Intelligence, Vol.3, No.1, pp. 9-19, 2021, DOI:10.32604/jai.2021.016706

Abstract With the development of Internet technology, the computing power of data has increased, and the development of machine learning has become faster and faster. In the industrial production of industrial control systems, quality inspection and safety production of process products have always been our concern. Aiming at the low accuracy of anomaly detection in process data in industrial control system, this paper proposes an anomaly detection method based on stacking integration using the machine learning algorithm. Data are collected from the industrial site and processed by feature engineering. Principal component analysis (PCA) and integrated rule… More >

Afiqah Halim¹, Wan Azani Mustafa^1,2,*, Wan Khairunizam Wan Ahmad¹, Hasliza A. Rahim², Hamzah Sakeran³

Oncologie, Vol.23, No.1, pp. 73-88, 2021, DOI:10.32604/Oncologie.2021.015154

Abstract Cervical cancer is a cell disease in the cervix that develops out of control in the female body. The cervix links the vagina (birth canal) with the upper section of the uterus, which can only be found in the female body. This is the second leading cause of death among women around the world. However, cervical cancer is currently one of the most preventable cancers if early detection is identified. The effect of unidentified cancer may increase the risk of death when the cell disease spreads to other parts of the female anatomy (metastasize). The… More >

Dongyue Gao¹, Yunlong Ma², Zhanjun Wu^3,*, Yuebin Zheng³, Hongbo Lu¹

Structural Durability & Health Monitoring, Vol.15, No.1, pp. 23-37, 2021, DOI:10.32604/sdhm.2021.013737

Abstract Guided waves based damage detection methods using base signals offer the advantages of simplicity of signal generation and reception, sensitivity to damage, and large area coverage; however, applications of the technology are limited by the sensitivity to environmental temperature variations. In this paper, a Spearman Damage Index-based damage diagnosis method for structural health condition monitoring under varying temperatures is presented. First, a PZT sensor-based Guided wave propagation model is proposed and employed to analyze the temperature effect. The result of the analysis shows the wave speed of the Guided wave signal has higher temperature sensitivity More >

Jialin Wan¹, Muhammad Waqas^1,2, Shanshan Tu^1,*, Syed Mudassir Hussain³, Ahsan Shah², Sadaqat Ur Rehman⁴, Muhammad Hanif²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 267-281, 2021, DOI:10.32604/cmc.2021.016260

Abstract Fog computing paradigm extends computing, communication, storage, and network resources to the network’s edge. As the fog layer is located between cloud and end-users, it can provide more convenience and timely services to end-users. However, in fog computing (FC), attackers can behave as real fog nodes or end-users to provide malicious services in the network. The attacker acts as an impersonator to impersonate other legitimate users. Therefore, in this work, we present a detection technique to secure the FC environment. First, we model a physical layer key generation based on wireless channel characteristics. To generate More >

Yonghua Huo¹, Yi Cao², Zhihao Wang¹, Yu Yan³, Zhongdi Ge³, Yang Yang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1053-1091, 2021, DOI:10.32604/cmes.2021.013045

Abstract In recent years, with the continuous development of information technology and the rapid growth of network scale, network monitoring and management become more and more important. Network traffic is an important part of network state. In order to ensure the normal operation of the network, improve the availability of the network, find network faults in time and deal with network attacks; it is necessary to detect the abnormal traffic in the network. Abnormal traffic detection is of great significance in the actual network management. Therefore, in order to improve the accuracy and efficiency of network… More >