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  • Open Access

    ARTICLE

    IoT Services: Realizing Private Real-Time Detection via Authenticated Conjunctive Searchable Encryption

    Chungen Xu1,*, Lin Mei1, Jinxue Cheng2, Yu Zhao1, Cong Zuo3

    Journal of Cyber Security, Vol.3, No.1, pp. 55-67, 2021, DOI:10.32604/jcs.2021.017217

    Abstract With the rapid development of wireless communication technology, the Internet of Things is playing an increasingly important role in our everyday. The amount of data generated by sensor devices is increasing as a large number of connectable devices are deployed in many fields, including the medical, agricultural, and industrial areas. Uploading data to the cloud solves the problem of data overhead but results in privacy issues. Therefore, the question of how to manage the privacy of uploading data and make it available to be interconnected between devices is a crucial issue. In this paper, we propose a scheme that supports… More >

  • Open Access

    ARTICLE

    An LSTM-Based Malware Detection Using Transfer Learning

    Zhangjie Fu1,2,3,*, Yongjie Ding1, Musaazi Godfrey1

    Journal of Cyber Security, Vol.3, No.1, pp. 11-28, 2021, DOI:10.32604/jcs.2021.016632

    Abstract Mobile malware occupies a considerable proportion of cyberattacks. With the update of mobile device operating systems and the development of software technology, more and more new malware keep appearing. The emergence of new malware makes the identification accuracy of existing methods lower and lower. There is an urgent need for more effective malware detection models. In this paper, we propose a new approach to mobile malware detection that is able to detect newly-emerged malware instances. Firstly, we build and train the LSTM-based model on original benign and malware samples investigated by both static and dynamic analysis techniques. Then, we build… More >

  • Open Access

    REVIEW

    Overview of Strain Characterization in Relation to Serological and Molecular Detection of Citrus tristeza Closterovirus

    Yasir Iftikhar1,*, Mazhar Abbas2, Mustansar Mubeen3, Muhammad Zafar-ul-Hye4,*, Faheema Bakhtawar1, Sonum Bashir1, Ashara Sajid1, Muhammad Asif Shabbir1

    Phyton-International Journal of Experimental Botany, Vol.90, No.4, pp. 1063-1074, 2021, DOI:10.32604/phyton.2021.015508

    Abstract Tristeza is a devastating viral disease in all the citrus growing countries throughout the world and has killed millions of citrus trees in severely affected orchards. The citrus species grafted on sour orange rootstock are affected by this disease. Predominantly, the sweet orange, grapefruit and lime trees grafted on sour orange exhibit severe symptoms like quick decline, vein clearing, pin holing, bark scaling and degeneration leading to variable symptoms. Symptomatic expression of Citrus tristeza virus (CTV) in different hosts has been attributed to virus isolates which are from severe to mild. Different serological and molecular assays have been deployed to… More >

  • Open Access

    ARTICLE

    Deep Learning for Object Detection: A Survey

    Jun Wang1, Tingjuan Zhang2,*, Yong Cheng3, Najla Al-Nabhan4

    Computer Systems Science and Engineering, Vol.38, No.2, pp. 165-182, 2021, DOI:10.32604/csse.2021.017016

    Abstract Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in people s life, such as monitoring security, autonomous driving and so on, with the purpose of locating instances of semantic objects of a certain class. With the rapid development of deep learning algorithms for detection tasks, the performance of object detectors has been greatly improved. In order to understand the main development status of target detection, a comprehensive literature review of target detection and an overall discussion of the works closely related to it are presented in this paper. This… More >

  • Open Access

    ARTICLE

    Combined Signal Processing Based Techniques and Feed Forward Neural Networks for Pathological Voice Detection and Classification

    T. Jayasree1,*, S.Emerald Shia2

    Sound & Vibration, Vol.55, No.2, pp. 141-161, 2021, DOI:10.32604/sv.2021.011734

    Abstract This paper presents the pathological voice detection and classification techniques using signal processing based methodologies and Feed Forward Neural Networks (FFNN). The important pathological voices such as Autism Spectrum Disorder (ASD) and Down Syndrome (DS) are considered for analysis. These pathological voices are known to manifest in different ways in the speech of children and adults. Therefore, it is possible to discriminate ASD and DS children from normal ones using the acoustic features extracted from the speech of these subjects. The important attributes hidden in the pathological voices are extracted by applying different signal processing techniques. In this work, three… More >

  • Open Access

    ARTICLE

    A Broadcast Storm Detection and Treatment Method Based on Situational Awareness

    Zhe Zhu1, Mingjian Zhang2, Yong Liu1, Lan Ma1, Xin Liu1,*

    Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 47-54, 2021, DOI:10.32604/jihpp.2021.016690

    Abstract At present, the research of blockchain is very popular, but the practical application of blockchain is very few. The main reason is that the concurrency of blockchain is not enough to support application scenarios. After that, applications such as Intervalue increase the concurrency of blockchain transactions. However, due to the problems of network bandwidth and algorithm performance, there is always a broadcast storm, which affects the normal use of nodes in the whole network. However, the emergence of broadcast storms needs to rely on the node itself, which may be very slow. Even if developers debug the corresponding code, they… More >

  • Open Access

    ARTICLE

    A Fast Detection Method of Network Crime Based on User Portrait

    Yabin Xu1,2,*, 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 the Naive Bayesian method matching… More >

  • Open Access

    ARTICLE

    Feature-Enhanced RefineDet: Fast Detection of Small Objects

    Lei Zhao*, Ming Zhao

    Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 1-8, 2021, DOI:10.32604/jihpp.2021.010065

    Abstract Object detection has been studied for many years. The convolutional neural network has made great progress in the accuracy and speed of object detection. However, due to the low resolution of small objects and the representation of fuzzy features, one of the challenges now is how to effectively detect small objects in images. Existing target detectors for small objects: one is to use high-resolution images as input, the other is to increase the depth of the CNN network, but these two methods will undoubtedly increase the cost of calculation and time-consuming. In this paper, based on the RefineDet network framework,… More >

  • Open Access

    ARTICLE

    A Real-Time Integrated Face Mask Detector to Curtail Spread of Coronavirus

    Shilpa Sethi1, Mamta Kathuria1,*, Trilok Kaushik2

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 389-409, 2021, DOI:10.32604/cmes.2021.014478

    Abstract Effective strategies to control COVID-19 pandemic need high attention to mitigate negatively impacted communal health and global economy, with the brim-full horizon yet to unfold. In the absence of effective antiviral and limited medical resources, many measures are recommended by WHO to control the infection rate and avoid exhausting the limited medical resources. Wearing mask is among the non-pharmaceutical intervention measures that can be used as barrier to primary route of SARS-CoV2 droplets expelled by presymptomatic or asymptomatic individuals. Regardless of discourse on medical resources and diversities in masks, all countries are mandating coverings over nose and mouth in public… More >

  • Open Access

    ARTICLE

    A Novel Technique for Early Detection of COVID-19

    Mohammad Yamin1,*, Adnan Ahmed Abi Sen2, Zenah Mahmoud AlKubaisy1, Rahaf Almarzouki1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2283-2298, 2021, DOI:10.32604/cmc.2021.017433

    Abstract COVID-19 is a global pandemic disease, which results from a dangerous coronavirus attack, and spreads aggressively through close contacts with infected people and artifacts. So far, there is not any prescribed line of treatment for COVID-19 patients. Measures to control the disease are very limited, partly due to the lack of knowledge about technologies which could be effectively used for early detection and control the disease. Early detection of positive cases is critical in preventing further spread, achieving the herd immunity, and saving lives. Unfortunately, so far we do not have effective toolkits to diagnose very early detection of the… More >

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