首页|New Findings Reported from Jadavpur University Describe Advances in Machine Lear ning (Contextual Authentication of Users and Devices Using Machine Learning)
New Findings Reported from Jadavpur University Describe Advances in Machine Lear ning (Contextual Authentication of Users and Devices Using Machine Learning)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Machine Learning have been presented. According to news reporting originating from Kolkata, India, by NewsRx correspondents, research stated, "At the time of authentication, confide ntial data are exchanged between the user/device and the authentication server t o determine the legitimacy of the source requesting authentication. Safeguarding the authentication process from security attacks is of utmost importance, and v arious authentication methods exist depending on the system's requirements." Our news editors obtained a quote from the research from Jadavpur University, "H owever, no authentication process can guarantee full-proof security. This resear ch aimed to use the context of users and devices during authentication to detect anomalies and security-related attacks. In particular, denial-ofservice (DoS)/ distributed denial-of-service (DDoS) attacks and brute-force attacks have been a nalyzed in detail using contextual information. Extensive simulations were condu cted on the benchmark CICIDS2017 dataset using the Weka tool. The performance m etrics of recall, precision, accuracy, f-score, and model-built time were comput ed for the four machine-learning classifiers-J48, Random Forest, Multi-Layer Per ceptron, and Bayes Net-for different combinations of data splits and groups of d ata features. For both DoS/DDoS and brute-force attacks, some of the experimenta l results show a more than 99% value for recall, precision, accura cy, and f-score."
KolkataIndiaAsiaCybersecurityCyb orgsEmerging TechnologiesMachine LearningJadavpur University
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