Users’ Reaction Time for Improvement of Security and Access Control in Web Services

Magomedov, Shamil; Gusev, Alexander; Ilin, Dmitry; Nikulchev, Evgeny

doi:10.3390/app11062561

Cited by 4 publications

(2 citation statements)

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“…Technically, user reaction time is the timespan from the start of the web survey screen representing a page with a number of questions to the time when the user clicked the desired answer option. In works [4][5][6] on various experiments with large samples, it was shown that reaction time reflects personal skills of interaction with the user interface. Of course, various factors may influence the change in reaction time, but in general, reactions are maintained the same over the course of a few hours of experimentation.…”

Section: Introductionmentioning

confidence: 99%

“…Different researchers [31][32][33][34] defined and filtered random clickers and their thoughtless responses in different ways. In previous studies of web surveys [4,5,30], we gained experience in detecting random clickers. In this study, we simulate the behavior of random clickers based on the analysis of data from previous surveys when working with the given web interface.…”

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confidence: 99%

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Evaluation of User Reactions and Verification of the Authenticity of the User’s Identity during a Long Web Survey

et al. 2021

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Web surveys are very popular in the Internet space. Web surveys are widely incorporated for gathering customer opinion about Internet services, for sociological and psychological research, and as part of the knowledge testing systems in electronic learning. When conducting web surveys, one of the issues to consider is the respondents’ authenticity throughout the entire survey process. We took 20,000 responses to an online questionnaire as experimental data. The survey took about 45 min on average. We did not take into account the given answers; we only considered the response time to the first question on each page of the survey interface, that is, only the users’ reaction time was taken into account. Data analysis showed that respondents get used to the interface elements and want to finish a long survey as soon as possible, which leads to quicker reactions. Based on the data, we built two neural network models that identify the records in which the respondent’s authenticity was violated or the respondent acted as a random clicker. The amount of data allows us to conclude that the identified dependencies are widely applicable.

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Evaluation of User Reactions and Verification of the Authenticity of the User’s Identity during a Long Web Survey

et al. 2021

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Detect and Mitigate Cyberattacks Using SIEM

Younus,

Alanezi

2023

2023 16th International Conference on Developments in eSystems Engineering (DeSE)

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Research and implementation of non-linear management and monitoring system for classified information network

Jun

2023

Nonlinear Engineering

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In order to better realize the secret-related information monitoring system, an algorithm based on a nonlinear network is proposed and is combined with the traditional algorithm. This article mainly analyzes the theory of nonlinear networks, designs and trains new network parameters according to their own needs, and combines the nonlinear network as a feature extractor with the existing intrusion detection and wandering detection algorithms, which greatly improves the recognition ability of traditional algorithms. The main feature of a nonlinear network is that it can extract the positional features of objects from the network while also extracting object features, that is, positioning and classification are realized in the same network. As a feature extractor, this network can not only have a higher recognition rate than background difference, hog, and other algorithms but also have a greater ability to extract position information than other convolutional neural networks. The successful application of nonlinear production network systems in TV stations at all levels has greatly improved the editing and production capability and efficiency of TV programs. How to ensure the safe, reliable, stable, orderly, and efficient operation of nonlinear production network systems requires vendors and TVS Taiwan technical staff to jointly conduct in-depth research and summarize their findings. In this article, from the perspective of TV users, information components in nonlinear production network systems are analyzed, including class, title management mode, storage space management, material management, security management, and workflow management in nonlinear systems. Make some analysis, discussion, and summaries of network system and operation management problems. The experimental results show that the nonlinear algorithm in this article has a significant advantage over the original tracking algorithm; that is, most tracking algorithms do not have the ability of category recognition during the initial tracking process, which means that these tracking algorithms cannot accurately know what they are tracking. Because the nonlinear network has the ability to output categories, whether it is initial tracking or tracking loss recovery, nonlinearity has fundamentally better advantages than other tracking algorithms. Therefore, it can be predicted that there is a strong recognition ability in the later monitoring and wandering detection. It has been proved that the nonlinear algorithm can be effectively applied to the secret information monitoring system.

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