{"title":"基于云的分布式拒绝服务攻击的人工智能检测","authors":"Sabah Alzahrani, Liang Hong","doi":"10.1109/SERVICES.2018.00031","DOIUrl":null,"url":null,"abstract":"This research proposes a system for detecting known and unknown Distributed Denial of Service (DDoS) Attacks. The proposed system applies two different intrusion detection approaches anomaly-based distributed artificial neural networks(ANNs) and signature-based approach. The Amazon public cloud was used for running Spark as the fast cluster engine with varying cores of machines. The experiment results achieved the highest detection accuracy and detection rate comparing to signature based or neural networks-based approach.","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Detection of Distributed Denial of Service (DDoS) Attacks Using Artificial Intelligence on Cloud\",\"authors\":\"Sabah Alzahrani, Liang Hong\",\"doi\":\"10.1109/SERVICES.2018.00031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research proposes a system for detecting known and unknown Distributed Denial of Service (DDoS) Attacks. The proposed system applies two different intrusion detection approaches anomaly-based distributed artificial neural networks(ANNs) and signature-based approach. The Amazon public cloud was used for running Spark as the fast cluster engine with varying cores of machines. The experiment results achieved the highest detection accuracy and detection rate comparing to signature based or neural networks-based approach.\",\"PeriodicalId\":130225,\"journal\":{\"name\":\"2018 IEEE World Congress on Services (SERVICES)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE World Congress on Services (SERVICES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SERVICES.2018.00031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE World Congress on Services (SERVICES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERVICES.2018.00031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of Distributed Denial of Service (DDoS) Attacks Using Artificial Intelligence on Cloud
This research proposes a system for detecting known and unknown Distributed Denial of Service (DDoS) Attacks. The proposed system applies two different intrusion detection approaches anomaly-based distributed artificial neural networks(ANNs) and signature-based approach. The Amazon public cloud was used for running Spark as the fast cluster engine with varying cores of machines. The experiment results achieved the highest detection accuracy and detection rate comparing to signature based or neural networks-based approach.