Performance analysis of binary and multiclass models using azure machine learning

Network data is expanding and that too at an alarming rate. Besides, the sophisticated attack tools used by hackers lead to capricious cyber threat landscape. Traditional models proposed in the field of network intrusion detection using machine learning algorithms emphasize more on improving attack detection rate and reducing false alarms but time efficiency is often overlooked. Therefore, in order to address this limitation, a modern solution has been presented using Machine Learning-as-a-Service platform. The proposed work analyses the performance of eight two-class and three multiclass algorithms using UNSW NB-15, a modern intrusion detection dataset. 82,332 testing samples were considered to evaluate the performance of algorithms. The proposed two class decision forest model exhibited 99.2% accuracy and took 6 seconds to learn 1,75,341 network instances. Multiclass classification task was also undertaken wherein attack types like generic, exploits, shellcode and worms were classified with a recall percentage of 99%, 94.49%, 91.79% and 90.9% respectively by the multiclass decision forest model that also leapfrogged others in terms of training and execution time

Secure Outsourcing of Network Flow Data Analysis

In this paper, we identify a new and challenging application for the growing field of research on data anonymization and secure outsourcing of storage and computations to the cloud. Network flow data analysis is of high importance for network monitoring and management. Network monitoring applications reveal new challenges not yet addressed in the secure outsourcing literature. The secure and verifiable outsourcing of computation on anonymized network flow records provides a practical tool for network operators in order to harness the cloud benefits, which untapped until now because of privacy concerns. We present representative use-cases and problems, and identify sample related work that can be utilized for developing an effective solution