Purpose: Determine the effects of object based ordering of magnitude (tile) based systems on authentication time.
Parameters: login time entries for an ordered, unordered and standard magnitude based system. For magnitude property based authentication systems, ordering is the act of developing magnitude based systems in which image objects (properties) are arranged in either increasing or decreasing order of magnitude for each image in the system. An ordered system has all images arranged in order of magnitude, an unordered system is a system in which none of the images in the system is ordered, while a standard system contains both ordered and unordered images. This experiment is designed to investigate if the concept of ordering can significantly reduce a user’s authentication time.
5.9.1 Main Hypotheses
In conducting this experiment, the following hypotheses are made in relation the user’s login time and the 3 experimental conditions:
H0: That none of the 3 test conditions will incur statistically significant greater mean login time than the other conditions
H1That at least one of the 3 test conditions will incur statistically significant greater mean login time than the other conditions.
5.9.2 Research Participants
Forty university undergraduate computing science students, 28 males and 12 females were recruited for a within users study of the 3 test conditions; the ordered, the unordered and the standard magnitude based authentication models. All participants were between the ages of 19 and 35 years of age and each had at least one email and one bank account, hence, each participant had at least one online password and one numerical PIN and thus had an experience in the use of passwords. All participants claimed to have used computers and the internet for a number of years and hence were all experienced in the use of computers. The use of a student population ensured that the disparity in skill, proficiency and understanding as well as computing skill among members of the participant population was small.
5.9.3 Experimental Design
A within users design was used for the experiment in which forty participants were recruited and each was allocated the three test conditions which were:
1. An ordered implementation of the magnitude (tile) based model. (see section 3.8) 2. An unordered implementation of the magnitude (tile) based model.
3. A standard implementation of the magnitude (tile) based model.
The operational procedures, interface design and layout of each of the prototypes was identical with the only difference being that the images were from one of the three test conditions. Each participant was to use all three of these systems. The tasks to be performed by each participants on each of the prototypes was also the same.
5.9.4 Experimental Variables
The independent variables are the three implementations of the magnitude based model (ordered, unordered and standard) being investigated in the experiment. The dependent variable is the total login time logged onto the system in each implementation.
5.9.5 Apparatus and Materials
• Three hp pavilion laptop PCs running windows 10, 6. 00 GB RAM and 15.6” monitor
• The laptops run the three prototypes of the magnitude based model, identical in every aspect of the design and the tasks/procedures the participants are expected to perform.
• An information sheet that provides the participants with information about the experiment and what they are expected to do.
• No questionnaires are used in the conduct of this experiment.
5.9.6 Experimental Procedure
The following procedure was followed in the conduct of the experiment:
The participants were recruited by means of a recruitment form. A consent form was provided to each of the participants to sign and confirm their consent before the conduct of the experiments. Each participant tests each of the three test conditions. All three conditions are installed on each of the PCs.
There are basically two operations to be performed at each stage of the experiment on each of the three experimental conditions to be used in the experiment. Each participant registers onto the system in the first instance, and the logs onto the system. These are subdivided into a number of tasks which include:
1. The registration phase
✓ Click on the “sign up” button
✓ Enter a chosen username in the textbox provided
✓ Select the number of authentication steps to be used in the experiment (which is 2)
✓ Select image properties for step 1 in the image properties window
✓ Select image properties for step 2 in the image properties window
2. The authentication phase
✓ Enter your chosen username in the textbox provided
✓ Click on the “continue” button
✓ Select image for step 1 in the step 1 image grid
✓ Click on the “continue” button
✓ Select image for step 2 in the step 1 image grid
✓ Click on the “continue” button
The laboratory environment was selected for the experiment for control and serenity. Each participants worked on all three test conditions.
5.9.7 Experimental Results for Experiment 6
The experimental results were collected and a one-way analysis of variance (ANOVA) was performed on the dataset (Appendix 6) and the analysis did not show any statistically significant mean variation between groups [F(2, 117) = 2.932, p = 0.57]. A Tukey post hoc analysis, however, shows significant variation between the ordered (model 11, M = 25086.03, SD = 18093.535) and the unordered (model 12, M = 37277.15, SD = 23347.476), p = 0.047.
5.9.8 Discussion of Results for Experiment 6
Although the ANOVA analysis did not reveal significant mean variation between any of the groups, the Tukey post hoc analysis did reveal that significant mean variation does occur between the ordered and the unordered pairs of magnitude based systems. The results indicate that the participants’ login time was less in the ordered implementation than in the unordered implementation. Thus the null hypothesis that none of the 3 test conditions will incur statistically significant greater mean login time than the other conditions does not hold as a statistically significant variation in mean login time exists between the models. The main reason for this is that the human brain is engineered towards a ‘goal oriented search’, and it is established that sorting (ordering) can very much enhance search performance [147]. Hence the ordering process has made it easier for the participants in the ordered model than in the unordered model.