Personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis.
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
| Main Authors: | , , , |
|---|---|
| 其他作者: | |
| 格式: | Thesis |
| 语言: | English |
| 出版: |
Brac University
2019
|
| 主题: | |
| 在线阅读: | http://hdl.handle.net/10361/11726 |
| id |
10361-11726 |
|---|---|
| record_format |
dspace |
| spelling |
10361-117262022-01-26T10:20:01Z Personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis. Neaz, Fabiha Ahmed, Hasan Tawqir Granthi, Marium Tasnuva Saha, Shuvro Dev Alam, Dr. Md. Ashraful Department of Computer Science and Engineering, Brac University Personnel security Nuclear power plant Machine learning Social media activity System security. Nuclear power plants--Safety measures. This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 39-40). In this research, a novel Personnel Security Model is designed and demonstrated for detecting suspicious people in an organization especially for nuclear power plants. The proposed system composed of three subsystems and a final decision making system such as i. Application software for performing a dynamic questionnaire session of individual employee of the power plant, ii. Eye blink and response time counter for lie detection during the questionnaire session and iii. Another sub system is also introduced for sentiment analysis from social media activities. Then, based on the outputs of three sub-systems, final decision is generated. In first sub-system, According to the science of psychology, suspicious people can be detected by asking some questions, by their response time and their eye blinking, lie can also detected. On the other hand their social media posts can also reflect a person’s actual psychological condition. In this study a person’s answers of the psychological questions, their eye blinking and response time corresponding to the question, and their social media activity are taken in consideration to extract as parameters or features for the final prediction model to find out whether a person is suspicious or not. Experimental results and analysis have been presented to justify the validity of the proposed method. Fabiha Neaz Hasan Tawqir Ahmed Marium Tasnuva Granthi Shuvro Dev Saha B. Computer Science and Engineering 2019-04-17T09:52:09Z 2019-04-17T09:52:09Z 2018 2018-12 Thesis ID 14301031 ID 14101203 ID 14301020 ID 14101200 http://hdl.handle.net/10361/11726 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 43 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Personnel security Nuclear power plant Machine learning Social media activity System security. Nuclear power plants--Safety measures. |
| spellingShingle |
Personnel security Nuclear power plant Machine learning Social media activity System security. Nuclear power plants--Safety measures. Neaz, Fabiha Ahmed, Hasan Tawqir Granthi, Marium Tasnuva Saha, Shuvro Dev Personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis. |
| description |
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. |
| author2 |
Alam, Dr. Md. Ashraful |
| author_facet |
Alam, Dr. Md. Ashraful Neaz, Fabiha Ahmed, Hasan Tawqir Granthi, Marium Tasnuva Saha, Shuvro Dev |
| format |
Thesis |
| author |
Neaz, Fabiha Ahmed, Hasan Tawqir Granthi, Marium Tasnuva Saha, Shuvro Dev |
| author_sort |
Neaz, Fabiha |
| title |
Personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis. |
| title_short |
Personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis. |
| title_full |
Personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis. |
| title_fullStr |
Personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis. |
| title_full_unstemmed |
Personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis. |
| title_sort |
personnel security system of nuclear power plants using machine learning for psychological, behavioral and social media activity analysis. |
| publisher |
Brac University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/11726 |
| work_keys_str_mv |
AT neazfabiha personnelsecuritysystemofnuclearpowerplantsusingmachinelearningforpsychologicalbehavioralandsocialmediaactivityanalysis AT ahmedhasantawqir personnelsecuritysystemofnuclearpowerplantsusingmachinelearningforpsychologicalbehavioralandsocialmediaactivityanalysis AT granthimariumtasnuva personnelsecuritysystemofnuclearpowerplantsusingmachinelearningforpsychologicalbehavioralandsocialmediaactivityanalysis AT sahashuvrodev personnelsecuritysystemofnuclearpowerplantsusingmachinelearningforpsychologicalbehavioralandsocialmediaactivityanalysis |
| _version_ |
1814309108230127616 |