Formalization of the feature space for detection of attacks on wireless sensor networks
The article describes the formalization of the feature space in order to detect abnormal behaviour of nodes in wireless sensor network using statistical methods. The main methods of destructive impact on the infrastructure of wireless sensor networks based on ZigBee Protocol stack are considered. Sp...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
FRUCT
2017-04-01
|
| Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| Subjects: | |
| Online Access: | https://fruct.org/publications/fruct20/files/Zik.pdf |
| _version_ | 1828239230464163840 |
|---|---|
| author | Igor A. Zikratov Victoria Korzhuk Ilya Shilov Alexey Gvozdev |
| author_facet | Igor A. Zikratov Victoria Korzhuk Ilya Shilov Alexey Gvozdev |
| author_sort | Igor A. Zikratov |
| collection | DOAJ |
| description | The article describes the formalization of the feature space in order to detect abnormal behaviour of nodes in wireless sensor network using statistical methods. The main methods of destructive impact on the infrastructure of wireless sensor networks based on ZigBee Protocol stack are considered. Special attention is paid to attacks on integrity and availability, which theoretically can be detected using the methods of machine learning and mathematical statistics. On the basis of standards and specifications, as well as considered attacks, the space of more than 50 features is developed. Using the methods of Shannon, Kullback and accumulated frequencies, informative value of formalized signs was evaluated. Conclusions about the existing dependencies between the information content of features, the statistics collection period and sample size used to calculate the information content are drawn. Received the results can be used as a basis for further evaluation of the most suitable characteristics for the classification of attacks depending on the network characteristics. In the future the main aim of the study is to build an intrusion detection system that uses statistics of the interactions for a certain period of time as a source of information about the system. |
| first_indexed | 2024-04-12T21:19:11Z |
| format | Article |
| id | doaj.art-86b6ed037cd14cfe9fd3792e2a64ed82 |
| institution | Directory Open Access Journal |
| issn | 2305-7254 2343-0737 |
| language | English |
| last_indexed | 2024-04-12T21:19:11Z |
| publishDate | 2017-04-01 |
| publisher | FRUCT |
| record_format | Article |
| series | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| spelling | doaj.art-86b6ed037cd14cfe9fd3792e2a64ed822022-12-22T03:16:20ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372017-04-017762052653310.23919/FRUCT.2017.8071358Formalization of the feature space for detection of attacks on wireless sensor networksIgor A. Zikratov0Victoria Korzhuk1Ilya Shilov2Alexey Gvozdev3ITMO University, Saint Petersburg, RussiaITMO University, Saint Petersburg, RussiaITMO University, Saint Petersburg, RussiaITMO University, Saint Petersburg, RussiaThe article describes the formalization of the feature space in order to detect abnormal behaviour of nodes in wireless sensor network using statistical methods. The main methods of destructive impact on the infrastructure of wireless sensor networks based on ZigBee Protocol stack are considered. Special attention is paid to attacks on integrity and availability, which theoretically can be detected using the methods of machine learning and mathematical statistics. On the basis of standards and specifications, as well as considered attacks, the space of more than 50 features is developed. Using the methods of Shannon, Kullback and accumulated frequencies, informative value of formalized signs was evaluated. Conclusions about the existing dependencies between the information content of features, the statistics collection period and sample size used to calculate the information content are drawn. Received the results can be used as a basis for further evaluation of the most suitable characteristics for the classification of attacks depending on the network characteristics. In the future the main aim of the study is to build an intrusion detection system that uses statistics of the interactions for a certain period of time as a source of information about the system.https://fruct.org/publications/fruct20/files/Zik.pdf information securitywireless sensor networkattackZigBeeintegrityavailabilityfeature spaceinformativeness |
| spellingShingle | Igor A. Zikratov Victoria Korzhuk Ilya Shilov Alexey Gvozdev Formalization of the feature space for detection of attacks on wireless sensor networks Proceedings of the XXth Conference of Open Innovations Association FRUCT information security wireless sensor network attack ZigBee integrity availability feature space informativeness |
| title | Formalization of the feature space for detection of attacks on wireless sensor networks |
| title_full | Formalization of the feature space for detection of attacks on wireless sensor networks |
| title_fullStr | Formalization of the feature space for detection of attacks on wireless sensor networks |
| title_full_unstemmed | Formalization of the feature space for detection of attacks on wireless sensor networks |
| title_short | Formalization of the feature space for detection of attacks on wireless sensor networks |
| title_sort | formalization of the feature space for detection of attacks on wireless sensor networks |
| topic | information security wireless sensor network attack ZigBee integrity availability feature space informativeness |
| url | https://fruct.org/publications/fruct20/files/Zik.pdf |
| work_keys_str_mv | AT igorazikratov formalizationofthefeaturespacefordetectionofattacksonwirelesssensornetworks AT victoriakorzhuk formalizationofthefeaturespacefordetectionofattacksonwirelesssensornetworks AT ilyashilov formalizationofthefeaturespacefordetectionofattacksonwirelesssensornetworks AT alexeygvozdev formalizationofthefeaturespacefordetectionofattacksonwirelesssensornetworks |