Exploiting SNMP-MIB Data to Detect Network Anomalies using Machine Learning Techniques

09/04/2018
by   Ghazi Al-Naymat, et al.
0

The exponential increase in the number of malicious threats on computer networks and Internet services due to a large number of attacks makes the network security at continuous risk. One of the most prevalent network attacks that threaten networks is Denial of Service (DoS) flooding attack. DoS attacks have recently become the most attractive type of attacks to attackers and these have posed devastating threats to network services. So, there is a need for effective approaches, which can efficiently detect any intrusion in the network. This paper presents an efficient mechanism for network attacks detection and types of attack classification using the Management Information Base (MIB) database associated with the Simple Network Management Protocol (SNMP) through machine learning techniques. This paper also investigates the impact of SNMP-MIB data on network anomalies detection. Three classifiers, namely, Random Forest, AdaboostM1 and MLP are used to build the detection model. The use of different classifiers presents a comprehensive study on the effectiveness of SNMP-MIB data in detecting different types of attack. Empirical results show that the machine learning techniques were quite successful in detecting and classifying the attacks with a high detection rate.

READ FULL TEXT
04/05/2021

Performance Evaluation of Machine Learning Techniques for DoS Detection in Wireless Sensor Network

The nature of Wireless Sensor Networks (WSN) and the widespread of using...
05/14/2019

Detecting network anomalies using machine learning and SNMP-MIB dataset with IP group

SNMP-MIB is a widely used approach that uses machine learning to classif...
10/27/2020

Generalized Insider Attack Detection Implementation using NetFlow Data

Insider Attack Detection in commercial networks is a critical problem th...
05/26/2018

Intensive Preprocessing of KDD Cup 99 for Network Intrusion Classification Using Machine Learning Techniques

Network security engineers work to keep services available all the time ...
01/13/2019

A Machine-Synesthetic Approach To DDoS Network Attack Detection

In the authors' opinion, anomaly detection systems, or ADS, seem to be t...
12/04/2019

The method of detecting online password attacks based on high-level protocol analysis and clustering techniques

Although there have been many solutions applied, the safety challenges r...
06/02/2018

Scraping and Preprocessing Commercial Auction Data for Fraud Classification

In the last three decades, we have seen a significant increase in tradin...