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Online Scam Detection Using Human Psychology: Toward Usable Cybersecurity /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Online Scam Detection Using Human Psychology: Toward Usable Cybersecurity // Sarah Ying Zheng.
Author:
Zheng, Sarah Ying,
Description:
1 electronic resource (167 pages)
Notes:
Source: Dissertations Abstracts International, Volume: 85-07, Section: A.
Contained By:
Dissertations Abstracts International85-07A.
Subject:
Computer science. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30989976
ISBN:
9798381418514
Online Scam Detection Using Human Psychology: Toward Usable Cybersecurity /
Zheng, Sarah Ying,
Online Scam Detection Using Human Psychology: Toward Usable Cybersecurity /
Sarah Ying Zheng. - 1 electronic resource (167 pages)
Source: Dissertations Abstracts International, Volume: 85-07, Section: A.
Online scams are taking an emotional and financial toll on people around the globe. Current scam prevention methods thus are falling short. This thesis aims to understand why people are bad at detecting online scams and develop interventions to help people improve, using phishing e-mails as quintessential scam examples.It first presents a fundamental advance in understanding why people may have difficulties discerning honesty in online contexts. Using computational methods and a novel task, we find that worse discernment is driven by how people weight heuristics versus more cognitively demanding computations. Specifically, over-reliance on one's own behaviour led to worse discernment and higher reliance on statistical probabilities led to more accurate discernment. This finding is then applied to improve people's ability to detect phishing e-mails. People may not recognise phishing scams, because most people do not create phishing themselves. Our results suggest that engaging people with how to write phishing e-mails indeed improves detection. Next, we find that people's phishing detection ability is not related to demographic factors, user interaction styles, nor negligence of e-mail sender details. Instead, poor phishing detection related to people's lacking understanding of technical legitimacy cues and widely differing communication norms. We then show promising directions for user-centric e-mail security tools that enhance intuitive cues of legitimacy.These studies demonstrate that a deeper understanding of why people may fail to detect online scams can help develop new methods to reduce victimisation. Specifically, online legitimacy judgements may be improved by (i) policies that enforce media to recommend content that reflect true statistics of real-world phenomena, (ii) teaching people how online scams are created, and (iii) highlighting trust cues and norms for digital conduct. Individual risk-based approaches such as targeted interventions based on demographics are unwarranted by the current research.
English
ISBN: 9798381418514Subjects--Topical Terms:
573171
Computer science.
Subjects--Index Terms:
Deception
Online Scam Detection Using Human Psychology: Toward Usable Cybersecurity /
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Online Scam Detection Using Human Psychology: Toward Usable Cybersecurity /
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Sarah Ying Zheng.
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Online scams are taking an emotional and financial toll on people around the globe. Current scam prevention methods thus are falling short. This thesis aims to understand why people are bad at detecting online scams and develop interventions to help people improve, using phishing e-mails as quintessential scam examples.It first presents a fundamental advance in understanding why people may have difficulties discerning honesty in online contexts. Using computational methods and a novel task, we find that worse discernment is driven by how people weight heuristics versus more cognitively demanding computations. Specifically, over-reliance on one's own behaviour led to worse discernment and higher reliance on statistical probabilities led to more accurate discernment. This finding is then applied to improve people's ability to detect phishing e-mails. People may not recognise phishing scams, because most people do not create phishing themselves. Our results suggest that engaging people with how to write phishing e-mails indeed improves detection. Next, we find that people's phishing detection ability is not related to demographic factors, user interaction styles, nor negligence of e-mail sender details. Instead, poor phishing detection related to people's lacking understanding of technical legitimacy cues and widely differing communication norms. We then show promising directions for user-centric e-mail security tools that enhance intuitive cues of legitimacy.These studies demonstrate that a deeper understanding of why people may fail to detect online scams can help develop new methods to reduce victimisation. Specifically, online legitimacy judgements may be improved by (i) policies that enforce media to recommend content that reflect true statistics of real-world phenomena, (ii) teaching people how online scams are created, and (iii) highlighting trust cues and norms for digital conduct. Individual risk-based approaches such as targeted interventions based on demographics are unwarranted by the current research.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30989976
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