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Psychological Distance in Cyber Decision Making: Information about the Attackers 52nd Edwards Bayesian Research Conference Fullerton, 15 February 2014.

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Presentation on theme: "Psychological Distance in Cyber Decision Making: Information about the Attackers 52nd Edwards Bayesian Research Conference Fullerton, 15 February 2014."— Presentation transcript:

1 Psychological Distance in Cyber Decision Making: Information about the Attackers 52nd Edwards Bayesian Research Conference Fullerton, 15 February 2014 Jinshu Cui, Department of Psychology Heather Rosoff, Sol Price School of Public Policy Richard John, Department of Psychology CREATE, University of Southern California

2 Human operators are often thought of as a major cause of security failures - “the weakest link in the chain” [Schneier 2008] It is difficult for human operators to take cyber threats seriously when few cause serious consequences at the individual level Critical to understand perception and behavioral response to cyber threats Evaluation of Cyber Threats

3 Experience of a near miss significantly increased respondents’ endorsement of safer options, the effect was bigger under a gain frame than a loss frame. Experience of a hit significantly increased respondents’ endorsement of safer options relative to the near miss past experience. Experience of a false alarm significantly decreased respondents’ likelihood of endorsing safer response options, compared to the near miss past experience. Rosoff, H., Cui, J., & John, R. S. (2013). Heuristics and biases in cyber security dilemmas. Environment Systems and Decisions, 33(4), Previous Research

4 Real Crime vs. Cyber Crime Personally targeted Instant consequences Have information about the offender, have interaction with the offender, concern about the offender Group targeted Delayed consequences Rarely have information about the attacker, have no interaction with the attacker, ignore the attacker Who? Why?

5 Construal level theory (CLT) – “distant” attacks will be viewed abstractly, and “proximal” attacks will be viewed concretely. (Trope & Liberman, 2003, 2010; Trope, Liberman, & Wakslak, 2007) Motivation Information about AttackersAttributesPsychological DistanceConstrual Level attacker identification unknownmost distanthighest groupdistanthigh individualproximallow physical identified individualmost proximallowest attacker motivations unknownmost distanthighest terrorismdistanthigh fameproximallow moneymost proximallowest

6 Attacker identification o group or individual o physical identified or not Attack tactics o personal account o database Experiment 1 – Research Questions

7 Attacker Motivations o money: purchase luxury items o fame: increase his visibility and reputation within the hacker community o terrorism: provide financial support to a Middle Eastern terrorist group Resolution Status o resolved o unresolved Experiment 2 – Research Questions

8 Financial attack scenario 4 (attacker identification) x 2 (attack tactics) between-subjects design Manipulations –Attacker identification: unknown group individual individual with picture –Attack tactics: database vs. personal account Experiment 1 - Design

9 Official Bank Notification ___________________________________________________ August 2, 2013 Dear Valued Customer, We are writing to notify you that two days ago, there was an unauthorized attempt to withdraw all of your current funds. (personal account) As of now, we know an individual online hacker is responsible for the breach into your account. (individual attacker) The hacker acted alone in carrying out the attack. We are working with law enforcement officials and regret any concern or inconvenience this incident may have caused you. We will keep you informed as we make progress in his capture. Kindest Regards, Your Bank

10 Experiment 1 – Measures 10-item PANAS –1 (not at all) to 5 (extremely) –5-item negative affect: α = 0.94 –5-item positive affect: α = item Risk Perception: –0 to 10 / 0% to 100% –α = item Behavioral Intention: –1 (strongly disagree) to 5 (strongly agree) –3-item stay with bank: α = 0.63 –3-item stay away from bank: α = 0.75

11 Recruited from Amazon Mechanical Turk N = 239 $0.55 each Median time to complete: 6 min 43 % female 50% years old 98.3% shop online, 92.9% bank online Experiment 1 – Respondents

12 Less negative affect associated with pictured individual attacker compared to individual attacker without a picture (p =.038) low psychological distance would increase participants’ interest in subordinate and secondary aspects (Liviatan, Trope, and Liberman, 2008) Experiment 1 – Negative Affect

13 More positive affect was experienced if a personal account was attacked compared to a database (p =.024) Experiment 1 – Positive Affect

14 When database was attacked, respondents are more willing to count on the bank when the attacker was physically identified; with an individual account attacked, there is little difference. (p = 0.036) Experiment 1 – Protective Behavior

15 Female respondents tended to experience more negative affect (p =.014), higher perceived risk (p =.022), and were more likely to support for government’s intervention for online protection (p =.021) (Hale, 1996) Experiment 1 – Sex as a Moderator

16 Identity theft scenario 4 (perpetrator’s motivation) x 3 (resolution status) between-subjects design Manipulations –Perpetrator’s motivation: fame money terrorism unknown –Resolution status: resolved unresolved unknown Experiment 2 - Design

17 Scene 1: This morning in the mail you received a credit card statement in your name from a company with which you do not have an account. As you looked over the statement, you noticed several cash advances totaling $500. (PANAS) Scene 2: One week following your receipt of the suspicious credit card statement, you receive the following voice mail: “Good morning, my name is Gabriel Dawson from the Identity Theft Unit of the Police Department. Our investigation into a cyber perpetrator has led us to believe your personal computer has been compromised. We believe this individual hacked into your computer and obtained access to your account and the cache data of your online activities. In doing so, he was able to obtain your usernames, passwords, banking information, and other personal information. Our investigation thus far shows no evidence that can confirm the perpetrator's intent. (unknown motivation) I plan to be in touch in the coming weeks to report on the progress of our investigation. Please be vigilant in reporting to us any suspicious mail, , or phone call. Thank you.“ (PANAS, risk perception, short-term behavior) Experiment 2 – Scenes 1 and 2

18 Scene 3: In the days following the call from the Identity Theft Unit, you notice an increase in suspicious activity. You are receiving more spam s, junk mails and phone calls from solicitors. More notably is your receipt of a phone call from the Department of Motor Vehicles confirming the issuance of a new driver's license you did not order. You also receive a letter in the mail from the Internal Revenue Service inquiring about your filing of duplicate income tax returns, suggesting that fraudulent returns were submitted in your name. (PANAS) Scene 4: Moving ahead to several weeks following the call from the Identity Theft Unit of the Police Department, you receive yet another credit card statement in the mail from a company with which you do not have an account. This statement has a $1,500 balance. (unresolved) It is clear that you are continuing to experience complications as a result of your identity theft and that you are still at risk. (PANAS, risk perception, long-term behavior) Experiment 2 – Scenes 3 and 4

19 10-item negative affect (from PANAS): –1 (not at all) to 5 (extremely) –8-item negative affect (4 time periods): α = 0.93, 0.92, 0.92, item Risk Perception: –1 (strongly disagree) to 6 (strongly agree) – 5-item risk perception (2 time periods): α = 0.81, item short-term behavior: –check all that apply –Summed number of checked responses 12-item long-term behavior: –1 (strongly disagree) to 6 (strongly agree) –9-item long-term behavior: α = 0.86 Experiment 2 - Measures

20 Recruited from Amazon Mechanical Turk N = 419 $0.75 each Median time to complete: 7 min 44 % Female 50% years old 72% have at least one credit card, of which: – 8% have had an account opened fraudulently in their name –6% pay for an identity theft protection service Experiment 2 - Respondents

21 Respondents experienced less negative affect when the identity theft case was resolved compared to unresolved or unknown Experiment 2 – Negative Affect

22 Respondents perceived less risk of identity theft when the perpetrator was to fund terrorism compared to for money or fame Participants in the low psychological distance condition reported higher risk perceptions (Chandran&Menon, 2004) Experiment 2 – Risk Perception

23 Respondents perceived less risk of identity theft when the situation was resolved compared to unresolved or unknown Experiment 2 – Risk Perception

24 Participants are more willing to pursue long-term behavior of online identity protection when the identity theft case was unresolved or unknown than if it was resolved. Experiment 2 – Long Term Protective Behavior

25 Female participants tended to experience more negative affect, high perceived risk, were more likely to seek help (short-term behavior) and more likely to pursue online identity protection (long-term behavior) Experiment 2 – Sex as a Moderating Variable

26 Conclusions Cyber attacker and attack characteristics influence respondents’ affective responses, risk perceptions, and intended long term behavior Cyber Attacker Identification (Individual, Group, Individual with Picture, UK) Cyber Attack Tactics (Personal account vs. Database) Cyber Attackers’ Motivations (Fame, Money, Terror, UK) Resolution of Cyber Attack (Resolved, Unresolved, UK)

27 Psychological Distance in Cyber Decision Making: Information about the Attackers 52nd Edwards Bayesian Research Conference Fullerton, 15 February 2014 Jinshu Cui, Department of Psychology Richard John, Department of Psychology Heather Rosoff, Sol Price School of Public Policy CREATE, University of Southern California

28 Overview Research Questions –Do attacker identification (e.g., picture or not), attack tactics (i.e., personal account or database), motivations of the perpetrator (e.g., money, terrorism), or resolution of the event influence emotional, cognitive and behavioral responses? Experiment 1 –Financial Fraud: attacker identification, attack tactics Experiment 2 –Identity Theft: perpetrator’s motivation, resolution status


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