A personality-based behavioural model: Susceptibility to phishing on social networking sites
- Authors: Frauenstein, Edwin Donald
- Date: 2021-10-29
- Subjects: Phishing , Social networks , Personality , Self-presentation in mass media , Internet fraud , Internet users Habits and behavior , Big Five model , Human information processing , Heuristic-Systematic Model (HSM)
- Language: English
- Type: Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/190306 , vital:44982 , 10.21504/10962/190306
- Description: The worldwide popularity of social networking sites (SNSs) and the technical features they offer users have created many opportunities for malicious individuals to exploit the behavioral tendencies of their users via social engineering tactics. The self-representation and social interactions on SNSs encourage users to reveal their personalities in a way which characterises their behaviour. Frequent engagement on SNSs may also reinforce the performance of certain activities, such as sharing and clicking on links, at a “habitual” level on these sites. Subsequently, this may also influence users to overlook phishing posts and messages on SNSs and thus not apply sufficient cognitive effort in their decision-making. As users do not expect phishing threats on these sites, they may become accustomed to behaving in this manner which may consequently put them at risk of such attacks. Using an online survey, primary data was collected from 215 final-year undergraduate students. Employing structural equation modelling techniques, the associations between the Big Five personality traits, habits and information processing were examined with the aim to identify users susceptible to phishing on SNSs. Moreover, other behavioural factors such as social norms, computer self-efficacy and perceived risk were examined in terms of their influence on phishing susceptibility. The results of the analysis revealed the following key findings: 1) users with the personality traits of extraversion, agreeableness and neuroticism are more likely to perform habitual behaviour, while conscientious users are least likely; 2) users who perform certain behaviours out of habit are directly susceptible to phishing attacks; 3) users who behave out of habit are likely to apply a heuristic mode of processing and are therefore more susceptible to phishing attacks on SNSs than those who apply systematic processing; 4) users with higher computer self-efficacy are less susceptible to phishing; and 5) users who are influenced by social norms are at greater risk of phishing. This study makes a contribution to scholarship and to practice, as it is the first empirical study to investigate, in one comprehensive model, the relationship between personality traits, habit and their effect on information processing which may influence susceptibility to phishing on SNSs. The findings of this study may assist organisations in the customisation of an individual anti-phishing training programme to target specific dispositional factors in vulnerable users. By using a similar instrument to the one used in this study, pre-assessments could determine and classify certain risk profiles that make users vulnerable to phishing attacks. , Thesis (PhD) -- Faculty of Commerce, Information Systems, 2021
- Full Text:
- Date Issued: 2021-10-29
- Authors: Frauenstein, Edwin Donald
- Date: 2021-10-29
- Subjects: Phishing , Social networks , Personality , Self-presentation in mass media , Internet fraud , Internet users Habits and behavior , Big Five model , Human information processing , Heuristic-Systematic Model (HSM)
- Language: English
- Type: Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/190306 , vital:44982 , 10.21504/10962/190306
- Description: The worldwide popularity of social networking sites (SNSs) and the technical features they offer users have created many opportunities for malicious individuals to exploit the behavioral tendencies of their users via social engineering tactics. The self-representation and social interactions on SNSs encourage users to reveal their personalities in a way which characterises their behaviour. Frequent engagement on SNSs may also reinforce the performance of certain activities, such as sharing and clicking on links, at a “habitual” level on these sites. Subsequently, this may also influence users to overlook phishing posts and messages on SNSs and thus not apply sufficient cognitive effort in their decision-making. As users do not expect phishing threats on these sites, they may become accustomed to behaving in this manner which may consequently put them at risk of such attacks. Using an online survey, primary data was collected from 215 final-year undergraduate students. Employing structural equation modelling techniques, the associations between the Big Five personality traits, habits and information processing were examined with the aim to identify users susceptible to phishing on SNSs. Moreover, other behavioural factors such as social norms, computer self-efficacy and perceived risk were examined in terms of their influence on phishing susceptibility. The results of the analysis revealed the following key findings: 1) users with the personality traits of extraversion, agreeableness and neuroticism are more likely to perform habitual behaviour, while conscientious users are least likely; 2) users who perform certain behaviours out of habit are directly susceptible to phishing attacks; 3) users who behave out of habit are likely to apply a heuristic mode of processing and are therefore more susceptible to phishing attacks on SNSs than those who apply systematic processing; 4) users with higher computer self-efficacy are less susceptible to phishing; and 5) users who are influenced by social norms are at greater risk of phishing. This study makes a contribution to scholarship and to practice, as it is the first empirical study to investigate, in one comprehensive model, the relationship between personality traits, habit and their effect on information processing which may influence susceptibility to phishing on SNSs. The findings of this study may assist organisations in the customisation of an individual anti-phishing training programme to target specific dispositional factors in vulnerable users. By using a similar instrument to the one used in this study, pre-assessments could determine and classify certain risk profiles that make users vulnerable to phishing attacks. , Thesis (PhD) -- Faculty of Commerce, Information Systems, 2021
- Full Text:
- Date Issued: 2021-10-29
An exploration into the use of webinjects by financial malware
- Authors: Forrester, Jock Ingram
- Date: 2014
- Subjects: Malware (Computer software) -- Analysis , Internet fraud , Computer crimes , Computer security , Electronic commerce
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4697 , http://hdl.handle.net/10962/d1012079 , Malware (Computer software) -- Analysis , Internet fraud , Computer crimes , Computer security , Electronic commerce
- Description: As the number of computing devices connected to the Internet increases and the Internet itself becomes more pervasive, so does the opportunity for criminals to use these devices in cybercrimes. Supporting the increase in cybercrime is the growth and maturity of the digital underground economy with strong links to its more visible and physical counterpart. The digital underground economy provides software and related services to equip the entrepreneurial cybercriminal with the appropriate skills and required tools. Financial malware, particularly the capability for injection of code into web browsers, has become one of the more profitable cybercrime tool sets due to its versatility and adaptability when targeting clients of institutions with an online presence, both in and outside of the financial industry. There are numerous families of financial malware available for use, with perhaps the most prevalent being Zeus and SpyEye. Criminals create (or purchase) and grow botnets of computing devices infected with financial malware that has been configured to attack clients of certain websites. In the research data set there are 483 configuration files containing approximately 40 000 webinjects that were captured from various financial malware botnets between October 2010 and June 2012. They were processed and analysed to determine the methods used by criminals to defraud either the user of the computing device, or the institution of which the user is a client. The configuration files contain the injection code that is executed in the web browser to create a surrogate interface, which is then used by the criminal to interact with the user and institution in order to commit fraud. Demographics on the captured data set are presented and case studies are documented based on the various methods used to defraud and bypass financial security controls across multiple industries. The case studies cover techniques used in social engineering, bypassing security controls and automated transfers.
- Full Text:
- Date Issued: 2014
- Authors: Forrester, Jock Ingram
- Date: 2014
- Subjects: Malware (Computer software) -- Analysis , Internet fraud , Computer crimes , Computer security , Electronic commerce
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4697 , http://hdl.handle.net/10962/d1012079 , Malware (Computer software) -- Analysis , Internet fraud , Computer crimes , Computer security , Electronic commerce
- Description: As the number of computing devices connected to the Internet increases and the Internet itself becomes more pervasive, so does the opportunity for criminals to use these devices in cybercrimes. Supporting the increase in cybercrime is the growth and maturity of the digital underground economy with strong links to its more visible and physical counterpart. The digital underground economy provides software and related services to equip the entrepreneurial cybercriminal with the appropriate skills and required tools. Financial malware, particularly the capability for injection of code into web browsers, has become one of the more profitable cybercrime tool sets due to its versatility and adaptability when targeting clients of institutions with an online presence, both in and outside of the financial industry. There are numerous families of financial malware available for use, with perhaps the most prevalent being Zeus and SpyEye. Criminals create (or purchase) and grow botnets of computing devices infected with financial malware that has been configured to attack clients of certain websites. In the research data set there are 483 configuration files containing approximately 40 000 webinjects that were captured from various financial malware botnets between October 2010 and June 2012. They were processed and analysed to determine the methods used by criminals to defraud either the user of the computing device, or the institution of which the user is a client. The configuration files contain the injection code that is executed in the web browser to create a surrogate interface, which is then used by the criminal to interact with the user and institution in order to commit fraud. Demographics on the captured data set are presented and case studies are documented based on the various methods used to defraud and bypass financial security controls across multiple industries. The case studies cover techniques used in social engineering, bypassing security controls and automated transfers.
- Full Text:
- Date Issued: 2014
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