A threshold-based, real-time analysis in early detection of endpoint anomalies using SIEM expertise

Author:

Eswaran Sivaraman1,Srinivasan Aruna1,Honnavalli Prasad1

Affiliation:

1. PES University, Bangalore

Abstract

IT functions in organisations produce enormous quantities of data, logs and events. In the current IT world, handling a large amount of data is a challenging task and it is the responsibility of network administrators to transmit and store the data securely. If any data is disclosed or tampered with by an attacker, either locally or remotely, then the impact can be very high. To overcome this, firewall and intrusion detection system (IDS) and intrusion prevention system (IPS) solutions are used to verify all packets on the network.

Publisher

Mark Allen Group

Subject

Information Systems and Management,Computer Networks and Communications,Safety, Risk, Reliability and Quality

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1. Design and Development of Scalable SIEM as a Service using Spark and Anomaly Detection;2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE);2024-06-19

2. Research on Data Pollution Prevention in Network Intrusion Detection Systems Based on Naive Bayes;Proceedings of the 2024 3rd International Conference on Cryptography, Network Security and Communication Technology;2024-01-19

3. A method for satellite time series anomaly detection based on fast-DTW and improved-KNN;Chinese Journal of Aeronautics;2023-02

4. Malicious Traffic Compression and Classification Technique for Secure Internet of Things;Computers, Materials & Continua;2023

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