Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (59)
  • Open Access


    Phishing Scam Detection on Ethereum via Mining Trading Information

    Yanyu Chen1, Zhangjie Fu1,2,*

    Journal of Cyber Security, Vol.4, No.3, pp. 189-200, 2022, DOI:10.32604/jcs.2022.038401

    Abstract As a typical representative of web 2.0, Ethereum has significantly boosted the development of blockchain finance. However, due to the anonymity and financial attributes of Ethereum, the number of phishing scams is increasing rapidly and causing massive losses, which poses a serious threat to blockchain financial security. Phishing scam address identification enables to detect phishing scam addresses and alerts users to reduce losses. However, there are three primary challenges in phishing scam address recognition task: 1) the lack of publicly available large datasets of phishing scam address transactions; 2) the use of multi-order transaction information requires a large number of… More >

  • Open Access


    Cybersecurity Plan for a Healthcare Cloud-Based Solutions

    A. S. Yusuf1,*, A. Q. Ayinde2

    Journal of Cyber Security, Vol.4, No.3, pp. 185-188, 2022, DOI:10.32604/jcs.2022.035446

    Abstract Hospitals provide daily health services for thousands of patients. People, processes, and technologies drive the objectives and goals of the hospitals to ensure optimal and satisfactory health care services are rendered to their customers. Due to the sensitivity of the organization data and patient data, it is essential to ensure that the confidentiality, integrity, availability, and security of these data are considered. The leadership of the organization (managers and executives) must integrate a robust security plan when choosing the technologies that will be used to drive the organization’s processes. This paper will evaluate the existing technologies risk assessment, and the… More >

  • Open Access


    A Survey on Visualization-Based Malware Detection

    Ahmad Moawad*, Ahmed Ismail Ebada, Aya M. Al-Zoghby

    Journal of Cyber Security, Vol.4, No.3, pp. 169-184, 2022, DOI:10.32604/jcs.2022.033537

    Abstract In computer security, the number of malware threats is increasing and causing damage to systems for individuals or organizations, necessitating a new detection technique capable of detecting a new variant of malware more efficiently than traditional anti-malware methods. Traditional anti-malware software cannot detect new malware variants, and conventional techniques such as static analysis, dynamic analysis, and hybrid analysis are time-consuming and rely on domain experts. Visualization-based malware detection has recently gained popularity due to its accuracy, independence from domain experts, and faster detection time. Visualization-based malware detection uses the image representation of the malware binary and applies image processing techniques… More >

  • Open Access


    An Adaptive BWO Algorithm with RSA for Anomaly Detection in VANETs

    Y. Sarada Devi*, M. Roopa

    Journal of Cyber Security, Vol.4, No.3, pp. 153-167, 2022, DOI:10.32604/jcs.2022.033436

    Abstract Vehicular ad hoc networks (VANETs) are designed in accordance with the ad hoc mobile networks (MANETs), i.e., impulsive formation of a wireless network for V2V (vehicle-to-vehicle) communication. Each vehicle is preserved as a node which remains as share of network. All the vehicle in the network is made to be under communication in a VANET because of which all the vehicles in the range can be made connected to a to a unit & a wide network can be established with a huge range. Healthier traffic management, vehicle-to-vehicle communication and provision of road information can be done in VANETs. There… More >

  • Open Access


    An Adaptive-Feature Centric XGBoost Ensemble Classifier Model for Improved Malware Detection and Classification

    J. Pavithra*, S. Selvakumarasamy

    Journal of Cyber Security, Vol.4, No.3, pp. 135-151, 2022, DOI:10.32604/jcs.2022.031889

    Abstract Machine learning (ML) is often used to solve the problem of malware detection and classification, and various machine learning approaches are adapted to the problem of malware classification; still acquiring poor performance by the way of feature selection, and classification. To address the problem, an efficient novel algorithm for adaptive feature-centered XG Boost Ensemble Learner Classifier “AFC-XG Boost” is presented in this paper. The proposed model has been designed to handle varying data sets of malware detection obtained from Kaggle data set. The model turns the XG Boost classifier in several stages to optimize performance. At preprocessing stage, the data… More >

  • Open Access


    Deep Learning Based Image Forgery Detection Methods

    Liang Xiu-jian1,2,*, Sun He2

    Journal of Cyber Security, Vol.4, No.2, pp. 119-133, 2022, DOI:10.32604/jcs.2022.032915

    Abstract Increasingly advanced image processing technology has made digital image editing easier and easier. With image processing software at one’s fingertips, one can easily alter the content of an image, and the altered image is so realistic that it is illegible to the naked eye. These tampered images have posed a serious threat to personal privacy, social order, and national security. Therefore, detecting and locating tampered areas in images has important practical significance, and has become an important research topic in the field of multimedia information security. In recent years, deep learning technology has been widely used in image tampering localization,… More >

  • Open Access


    Analysis of Security Aspects in LoRaWAN

    Ahmed AL-Hthlool1,*, Mounir Frikha2

    Journal of Cyber Security, Vol.4, No.2, pp. 109-118, 2022, DOI:10.32604/jcs.2022.030498

    Abstract Nowadays, emerging trends in the field of technology related to big data, cognitive computing, and the Internet of Things (IoT) have become closely related to people’s lives. One of the hottest areas these days is transforming traditional cities into smart cities, using the concept of IoT depending on several types of modern technologies to develop and manage cities in order to improve and facilitate the quality of life. The Internet of Things networks consist of a huge number of interconnected devices and sensors that process and transmit data. Such Activities require efficient energy to be performed at the highest quality… More >

  • Open Access


    Application and Challenge of Blockchain Technology in Medical Field

    Kaifeng Zhang1, Zhao Qiu1,*, Gengquan Xie1, Jiale Lin1, Tingting Zhang1, Yingsheng Lian1, Tao Chen1, Yunlong He2, Yu Yang2

    Journal of Cyber Security, Vol.4, No.2, pp. 95-107, 2022, DOI:10.32604/jcs.2022.029451

    Abstract Due to its unique security, blockchain technology is widely used in the financial field. Under the background of the rapid development of information technology and the rapid improvement of medical level, it is also a general trend to integrate blockchain technology into the medical field. According to the characteristics of blockchain and the research contents of many scholars on the application of blockchain in the medical field, this paper analyzes and summarizes the problems existing in the current development of blockchain, puts forward corresponding solutions, and looks forward to the further application of blockchain technology in the medical field. More >

  • Open Access


    Web Tracking Domain and Possible Privacy Defending Tools: A Literature Review

    Maryam Abdulaziz Saad Bubukayr1,*, Mounir Frikha2

    Journal of Cyber Security, Vol.4, No.2, pp. 79-94, 2022, DOI:10.32604/jcs.2022.029020

    Abstract Personal data are strongly linked to web browsing history. By visiting a certain website, a user can share her favorite items, location, employment status, financial information, preferences, gender, medical status, news, etc. Therefore, web tracking is considered as one of the most significant internet privacy threats that can have a serious impact on end-users. Usually, it is used by most websites to track visitors through the internet in order to enhance their services and improve search customization. Moreover, selling users’ data to the advertising companies without their permission. Although there are more research efforts focused on third-party tracking to protect… More >

  • Open Access


    CenterPicker: An Automated Cryo-EM Single-Particle Picking Method Based on Center Point Detection

    Jianquan Ouyang1,*, Jinling Wang1, Yaowu Wang1, Tianming Liu2

    Journal of Cyber Security, Vol.4, No.2, pp. 65-77, 2022, DOI:10.32604/jcs.2022.028065

    Abstract Cryo-electron microscopy (cryo-EM) has become one of the mainstream techniques for determining the structures of proteins and macromolecular complexes, with prospects for development and significance. Researchers must select hundreds of thousands of particles from micrographs to acquire the database for single-particle cryo-EM reconstruction. However, existing particle picking methods cannot ensure that the particles are in the center of the bounding box because the signal-to-noise ratio (SNR) of micrographs is extremely low, thereby directly affecting the efficiency and accuracy of 3D reconstruction. We propose an automated particle-picking method (CenterPicker) based on particle center point detection to automatically select a large number… More >

Displaying 1-10 on page 1 of 59. Per Page  

Share Link

WeChat scan