MACHINE LEARNING MODELS FOR INTRUSION DETECTION SYSTEMS(IDS) Tips for developing academically sound IDS models and algorithms for Your IEEE Publication 2019 SEP 23, 2019 Copyright © 2019 PhD Assistance. All rights reserved
Tips for developing Academically sound IDS Models and algorithms for Your IEEE Publication 2019
Sep 23, 2019
1.AI is promising in the of detecting intrusions are cross-site scripting attacks, SQL injections, Denial of Service (DoS), Ransomware, etc.
2.Deep learning models able to accurately predict and recognize “normal activity” or malicious activity faster and generate a much lower percentage of false positives
3.Real-time IDS systems must not have a single fixed algorithm instead the algorithms must be updated regularly
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MACHINE LEARNING MODELS FOR INTRUSION DETECTION
SYSTEMS(IDS)Tips for developing academically sound IDS
models and algorithms for Your IEEE Publication 2019
SEP 23, 2019
Copyright © 2019 PhD Assistance. All rights reserved
TOPICS TO BE DISCUSSED
Intrusion Detection System
Types Of IDS Techniques
Pre-Processing IDS Data
IDS classification
Summary
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About Us
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PhD Lab @PhD AssistanceEngineering and Technology:E&T Lab at PhD Assistance is involved in exploring novel research areas by conducting dynamic research. It promotes innovation in all fields of engineering by advancing the technology with structured and continuous research. The problems and challenges faced by the existing technologies and trends are explored by our researchers exists in scholarly literature, in theory, or in practices that needs deliberate investigation. These problems are identified and fixed by our researchers by suggesting better novel alternatives with appropriate tools, technologies and approaches, thereby proving their effectiveness in real time applications.
INTRUSION
Unauthorised activities on the organisation's local
computer network
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MOST COMMON INTRUSIONS
Ransomware
Denial of Service (DoS)SQL
injections
Cross-site scriptingattacks
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Monitors network traffic for suspicious
activity and issues alerts.
INTRUSION DETECTION
SYSTEM
Scans a network or
a system for harmful activity.
It varies from a single
computer to large
network.
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IPS detect the intrusion &
prevent them
Creates a log
Restrict the access of intrusions
Blocks IP address source
INTRUSION PREVENTION
SYSTEM
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TYPES OF IDS TECHNIQUES
Network based(NIDS)
Host based intrusion
(HIDS)
Vulnerabilityassessment-
based(VIDS)Copyright © 2019 PhD Assistance. All rights reserved
PRE-PROCESSING IDS DATAPerformed through data set(KDD’99, DARPA dataset)
Dataset size should be huge & balanced
Prevent intrusions in real-time traffic
Easier to categorize, reduce operation time and improves classification performance and accuracy.
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IDS
CLAS
SIFI
CATI
ON
Machine learning (ML)algorithm [Artificial Neural Networks]
Statistical anomalydetection algorithms
Data mining Algorithms
Knowledge-based detection
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A constant update willimprove the accuracy and reduce the error rates.
SUMMARY
Building an IDS isextremely challenging
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