Where the User Does Look When Reading Phishing Mails - An Eye-Tracking Study

被引:17
作者
Pfeffel, Kevin [1 ]
Ulsamer, Philipp [1 ]
Mueller, Nicholas H. [1 ]
机构
[1] Univ Appl Sci Wurzburg Schweinfurt, Wurzburg, Germany
来源
LEARNING AND COLLABORATION TECHNOLOGIES. DESIGNING LEARNING EXPERIENCES, LCT 2019, PT I | 2019年 / 11590卷
关键词
Phishing; Awareness; Security; Eye-tracking; Human factors;
D O I
10.1007/978-3-030-21814-0_21
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
To detect phishing mails, various strategies based on a reliable cryptography-based security framework exist. Nevertheless, the user themselves still provide a greater opportunity for phishing attacks. Therefore, it is crucial to understand how the user deals with phishing mails when confronted with them. This study limits itself to visual stimuli of phishing mails and therefore uses an eye-tracking procedure to determine the gaze behavior. Twenty-one different mails were used for this experiment, of which fourteen were phishing mails. The task of the users was to decide whether it was a phishing mail or a real mail. For the evaluation, the individual mails were provided with Areas of Interest (AOIs). This is similar to the usual components of a mail that would be attachment, body, footer, header and signature. Thereafter, three artificial groups were formed. There was one group with a low score of correct answers, one with a middle score and one with a high score. These three groups were then compared and showed differences in processing time. This led to the assumption that knowledge and time are two important factors in recognizing phishing mails.
引用
收藏
页码:277 / 287
页数:11
相关论文
共 12 条
  • [1] [Anonymous], 2017, State of Cyber Security 2017
  • [2] [Anonymous], FBI Gov Homepage
  • [3] Bergholz A., 2008, P INT C E MAIL ANTIS
  • [4] Dhamija R., 2006, P SIGCHI C HUMAN FAC, P581
  • [5] Fette I., 2006, LEARNING DETECT PHIS
  • [6] Jakobsson M., 2005, Financial Cryptography and Data Security, P89, DOI DOI 10.1007/115078409
  • [7] Protecting users against phishing attacks
    Kirda, Engin
    Kruegel, Christopher
    [J]. COMPUTER JOURNAL, 2006, 49 (05) : 554 - 561
  • [8] Ma J, 2009, KDD-09: 15TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, P1245
  • [9] Prakash P, 2010, IEEE INFOCOM SER
  • [10] Semba B., 2016, TAG MULT WIRTSCH 201, P1083