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Modeling the Triad of User Behaviors in IT Security

Adi Marko – M.Sc. student

In the past, IT security was considered a technical issue (good algorithms and well-designed 

systems will prevent security risks). Today, there is increasing awareness of the human as a key 

determinant of the safety of IT systems. Security systems often mainly provide alerts, and rely on 

the user to make decisions and to adjust system settings. Hence end-users’ behavior should be 

considered when developing security systems. 

An important aspect in this context are risk-related behaviors. These are not expressions of a 

single tendency to take risks, but rather the combination of a number of different behaviors that 

can change dynamically in response to changes in task requirements and the environment. One 

model of these multiple behaviors is the Triad of Risk-related behavior (Ben-Asher, 2011). The 

original study was empirical research in the context of a microworld. In this thesis I developed a 

quantitative model of the three security behaviors, analyzed the relations between them, and 

show how they effects on the security level of the system. In addition, I studied changes in the 

predicted behavior as a function of risk attitude and the weighting of information from alerts. 

The study provides some insights on the effects of different parameters on outcomes and on the 

effects of deviations from optimality.

This work was performed under the supervision of  Prof. Joachim Meyer

Effects of user characteristics and security alerts on cybersecurity behavior

Anna Morgenshtein-Sekeles

The rapid advances in computer technology cause organizations to depend on these 

technologies for practically all corporate activities. Information systems and networks 

process, store and transmit digital data. As organizations have come to depend on 

information technology, the likelihood of malicious interference with the functioning 

of these systems, unauthorized access to sensitive materials and other forms of 

malicious activities greatly increased. These can cause major damages, as well as 

indirect damage through the loss of reputation.

Threats are often introduced into systems as a result of user actions. Legitimate users 

might perform actions such as browsing a malicious site, downloading a file with 

malicious content from email or a website, connecting an infected external device to 

the computer, etc. The user performs these actions for some purpose, but they may 

result in undesirable outcomes, if hidden malware was unintentionally activated. In 

many cases, especially in organizations, various security systems can notify the user 

about potentially dangerous actions. System detection thresholds can be configured by 

the organization according to the organizational information security policy.

The study examines the effects of the user’s ability to distinguish between threat and 

no-threat events and the user’s risk aversion on users’ cyber security behavior with 

security systems with different threshold settings and on the results of these 

behaviors. A laboratory experiment was conducted in which participants had to 

classify stimuli as threats or no threats, based on information they received about the 

stimuli and on the output from an alerting system. The results were compared to the 

predictions of a simulation model of user behavior in this context. 

Results showed that user's knowledge significantly affects cyber security behavior. 

Better knowledge reduces the probability of security breaches and improves the 

quality of work. The availability of a security system reduces risky behavior, but less 

than predicted. People use the information they receive from the system, but they do 

not utilize it optimally and tend to give excessive weight to their own knowledge. 

This work was performed under the supervision of  Prof. Joachim Meyer