首页|New Machine Learning Findings Has Been Reported by Investigators at Oklahoma Cit y University (Intrusion Detection System: a Comparative Study of Machine Learnin g-based Ids)
New Machine Learning Findings Has Been Reported by Investigators at Oklahoma Cit y University (Intrusion Detection System: a Comparative Study of Machine Learnin g-based Ids)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news reporting originating from Oklahoma City, Oklahoma , by NewsRx correspondents, research stated, "The use of encrypted data, the div ersity of new protocols, and the surge in the number of malicious activities wor ldwide have posed new chAllenges for intrusion detection systems (IDS). In this scenario, existing signaturebased IDS are not performing well." Our news editors obtained a quote from the research from Oklahoma City Universit y, "Various researchers have proposed machine learning-based IDS to detect unkno wn malicious activities based on behaviour patterns. Results have shown that mac hine learning-based IDS perform better than signaturebased IDS (SIDS) in identi fying new malicious activities in the communication network. In this paper, the authors have analyzed the IDS dataset that contains the most current common atta cks and evaluated the performance of network intrusion detection systems by adop ting two data resampling techniques and 10 machine learning classifiers."
Oklahoma CityOklahomaUnited StatesNorth and Central AmericaCybersecurityCyborgsEmerging TechnologiesMachin e LearningOklahoma City University
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