D. Ageyev, T. Radivilova, Oleg Bondarenko, Othman Mohammed
{"title":"Traffic Monitoring and Abnormality Detection Methods for IoT","authors":"D. Ageyev, T. Radivilova, Oleg Bondarenko, Othman Mohammed","doi":"10.1109/aict52120.2021.9628954","DOIUrl":null,"url":null,"abstract":"Monitoring network traffic is an important issues for the networks reliability and security. The statistical model of traffic is at the heart of many methods for detecting traffic anomalies. Existing modern methods of detecting attacks in several cases turn out to be insufficiently reliable, for example, due to the missed moment of the attack, which makes it possible for an attacker to introduce errors into the operation of the system and make it unusable (for example, to carry out a DDOS attack). The main direction of the study was to reduce the impact of the lack of computing resources of IoT devices in the implementation of mechanisms for detecting anomalies. The paper proposes to achieve this through the use of a distributed structure, including cloud computing.","PeriodicalId":375013,"journal":{"name":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/aict52120.2021.9628954","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Monitoring network traffic is an important issues for the networks reliability and security. The statistical model of traffic is at the heart of many methods for detecting traffic anomalies. Existing modern methods of detecting attacks in several cases turn out to be insufficiently reliable, for example, due to the missed moment of the attack, which makes it possible for an attacker to introduce errors into the operation of the system and make it unusable (for example, to carry out a DDOS attack). The main direction of the study was to reduce the impact of the lack of computing resources of IoT devices in the implementation of mechanisms for detecting anomalies. The paper proposes to achieve this through the use of a distributed structure, including cloud computing.