Home / Journals / JCS / Vol.3, No.2, 2021
  • Open AccessOpen Access

    ARTICLE

    Multi-UAV Cooperative GPS Spoofing Based on YOLO Nano

    Yongjie Ding1, Zhangjie Fu1,2,*
    Journal of Cyber Security, Vol.3, No.2, pp. 69-78, 2021, DOI:10.32604/jcs.2021.019105
    Abstract In recent years, with the rapid development of the drone industry, drones have been widely used in many fields such as aerial photography, plant protection, performance, and monitoring. To effectively control the unauthorized flight of drones, using GPS spoofing attacks to interfere with the flight of drones is a relatively simple and highly feasible attack method. However, the current method uses ground equipment to carry out spoofing attacks. The attack range is limited and the flexibility is not high. Based on the existing methods, this paper proposes a multi-UAV coordinated GPS spoofing scheme based on YOLO Nano, which can launch… More >

  • Open AccessOpen Access

    ARTICLE

    Pedestrian Crossing Detection Based on HOG and SVM

    Yunzuo Zhang*, Kaina Guo, Wei Guo, Jiayu Zhang, Yi Li
    Journal of Cyber Security, Vol.3, No.2, pp. 79-88, 2021, DOI:10.32604/jcs.2021.017082
    Abstract In recent years, pedestrian detection is a hot research topic in the field of computer vision and artificial intelligence, it is widely used in the field of security and pedestrian analysis. However, due to a large amount of calculation in the traditional pedestrian detection technology, the speed of many systems for pedestrian recognition is very limited. But in some restricted areas, such as construction hazardous areas, real-time detection of pedestrians and cross-border behaviors is required. To more conveniently and efficiently detect whether there are pedestrians in the restricted area and cross-border behavior, this paper proposes a pedestrian cross-border detection method… More >

  • Open AccessOpen Access

    ARTICLE

    Computational Intelligent Techniques To Detect DDOS Attacks : A Survey

    Isha Sood*, Varsha Sharma
    Journal of Cyber Security, Vol.3, No.2, pp. 89-106, 2021, DOI:10.32604/jcs.2021.018623
    Abstract The Internet is often targeted by the Distributed Denial of Service (DDOS) Attacks that deliberately utilize resources and bandwidth to prohibit access to potential users. The attack possibility is that the packets are filled massively. A DOS attack is launched by a single source, while a DDOS attack is originated from numerous resources. DDoS attacks are not capable of stealing website user’s information. The prime motive of the DDoS attacks is to devastate the website resources. Distributed Denial of Service (DDoS) attacks are disruptive to internet access on the Network. The attitude of the customer to get fast and reliable… More >

  • Open AccessOpen Access

    ARTICLE

    Blockchain Based Secure Solution for Cloud Storage: A Model for Synchronizing Industry 4.0 and IIoT

    Prakhar Sahu1,*, S. K. Singh1, Arun Kumar Singh2
    Journal of Cyber Security, Vol.3, No.2, pp. 107-115, 2021, DOI:10.32604/jcs.2021.020831
    Abstract Industry 4.0 is one of the hot topic of today’s world where everything in the industry will be data driven and technological advancements will take place accordingly. In the fourth phase of industrial revolution, manufacturers are dependent upon data produced by the consumers to invent, innovate or change anything for the product. Internet of things devices like OBD, RFID, IIoT, Smart devices are the major source of data generation and represents trends in the industry. Since the IoT device are vulnerable to hackers due to its limitation, consumer data security should be tighten up and enhanced. This paper gives an… More >

  • Open AccessOpen Access

    ARTICLE

    A Hybrid Algorithm Based on PSO and GA for Feature Selection

    Yu Xue1,*, Asma Aouari1, Romany F. Mansour2, Shoubao Su3
    Journal of Cyber Security, Vol.3, No.2, pp. 117-124, 2021, DOI:10.32604/jcs.2021.017018
    Abstract One of the main problems of machine learning and data mining is to develop a basic model with a few features, to reduce the algorithms involved in classification’s computational complexity. In this paper, the collection of features has an essential importance in the classification process to be able minimize computational time, which decreases data size and increases the precision and effectiveness of specific machine learning activities. Due to its superiority to conventional optimization methods, several metaheuristics have been used to resolve FS issues. This is why hybrid metaheuristics help increase the search and convergence rate of the critical algorithms. A… More >

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