Research on Phishing AP Attack Detection Technology Based on RSSI

被引:0
|
作者
Ling Jie [1 ]
Jin Shuangqi [1 ]
机构
[1] Guangdong Univ Technol, Fac Comp, Guangzhou, Guangdong, Peoples R China
来源
PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ELECTRONIC TECHNOLOGY | 2016年 / 48卷
关键词
Phishing AP Attack; WIFI; WLAN; RSSI;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Wi-Fi wireless technology obtained rapid development because of its flexibility, mobility and easy scalability characteristics. But the network identifier (SSID, BSSID) is easy to be forged, the attacker is easy to forge AP that a common user can't identify it, and conduct other attacks, then get the user's sensitive information. In this paper, we propose an improved RSSI phishing AP attack detection method based on the characteristics of RSSI in wireless Wi-Fi network and easy to obtain. The method needs to be in a safe and secure environment construction of Wi-Fi wireless RSSI fingerprint database and the detected target AP and fingerprint library information were compared to determine the safety, solving the problem of twin fishing AP successfully. Experimental results show that in the RSSI threshold with the range of -5dBm, the correct detection rate can reach 95%, to achieve the legitimacy of the WLAN AP detection.
引用
收藏
页码:205 / 208
页数:4
相关论文
共 50 条
  • [1] Research on the phishing detection technology based on SVM-RFE
    China Information Technology Evaluation Center, Beijing 100085, China
    不详
    Wang, T. (barcating@163.com), 1600, Huazhong University of Science and Technology (41):
  • [2] Machine learning-based phishing attack detection
    Hossain S.
    Sarma D.
    Chakma R.J.
    International Journal of Advanced Computer Science and Applications, 2020, 11 (09): : 378 - 388
  • [3] Machine Learning-Based Phishing Attack Detection
    Hossain, Sohrab
    Sarma, Dhiman
    Chakma, Rana Joyti
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2020, 11 (09) : 378 - 388
  • [4] Sybil Attack Detection Based on RSSI for Wireless Sensor Network
    Wang, Jiangtao
    Yang, Geng
    Sun, Yuan
    Chen, Shengshou
    2007 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-15, 2007, : 2684 - 2687
  • [5] Using AP-TED to Detect Phishing Attack Variations
    Le Page, Sophie
    Cui, Qian
    Jourdan, Guy-Vincent
    Bochmann, Gregor V.
    Flood, Jason
    Onut, Iosif-Viorel
    2018 16TH ANNUAL CONFERENCE ON PRIVACY, SECURITY AND TRUST (PST), 2018, : 298 - 303
  • [6] PhAttApp: A Phishing Attack Detection Application
    Lam, Thuy
    Kettani, Houssain
    PROCEEDINGS OF 3RD INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND DATA MINING (ICISDM 2019), 2019, : 154 - 158
  • [7] Research on Network Attack Detection Technology based on Reverse Detection and Protocol Analysis
    Liu, Donglan
    Liu, Xin
    Zhang, Hao
    Wang, Wenting
    Zhao, Xiaohong
    Zhao, Yang
    Yu, Hao
    Ma, Lei
    2019 6TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE 2019), 2019, : 490 - 494
  • [8] Research on ZigBee Indoor Technology Positioning Based on RSSI
    Dong, Zhou Yang
    Xu, Wei Ming
    Zhuang, Hao
    PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE OF INFORMATION AND COMMUNICATION TECHNOLOGY [ICICT-2019], 2019, 154 : 424 - 429
  • [9] HTTP header based phishing attack detection using machine learning
    Shukla, Sanjeev
    Misra, Manoj
    Varshney, Gaurav
    TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2024, 35 (01)
  • [10] WC-PAD: Web Crawling based Phishing Attack Detection
    Nathezhtha, T.
    Sangeetha, D.
    Vaidehi, V.
    2019 IEEE 53RD INTERNATIONAL CARNAHAN CONFERENCE ON SECURITY TECHNOLOGY (ICCST 2019), 2019,