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Machine Learning for Network Security

With advancement in technology, organizations are now able to collect a large amount of data that are being generated and transferred over the network. Cybersecurity experts may have a hard time monitoring and analysing this data due to the sheer volume which is beyond their capacity to manage. One possible solution that is being widely explored is to use Machine Learning and Data Mining methods for cybersecurity related problems.

Methods of machine learning and data mining can help to build better detectors from massive amounts of complex data that is generated over the Internet. Such methods can also help discover the information required to build more secure systems.

Data can be gathered from a combination of software installed on customer workstations and sensors placed in network segments. This data can be fed to systems that use machine learning which can classify the incoming samples and can distinguish between normal behaviour and any anomalies. Historical data and patterns can be used to compare samples and identify evolving threats.

This course will give you a broad introduction to network security and related cybersecurity problems. It will also explore various machine learning and data mining solutions to cybersecurity problems. The module will focus on the following

  • Introduction to Network Security concepts
  • Basic Functions of Firewalls 
  • Intrusion Detection and Prevention Systems 
  • Collections of application and network data 
  • Apply machine learning solutions to cybersecurity problems

Each module will include a brief description of the related theoretical concepts followed by a related hands-on workshop.

HRDF SBL Claimable for Employers Registered with HRDF

HRDF claimable

Course Code: M553

Course Booking

MYR880.00

Course Date

Course Time

* Required Fields

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.

Course Details

Module 1: Introduction to Network Security Concepts

  • Challenges to Securing Information
  • Core principles of Information Security
  • Types of Network Attacks
  • Malware

Module 2: Introduction to Firewalls

  • Types of Firewalls
  • Firewall Design and Architecture
  • Configuring Firewalls

Module 3: Intrusion Detection and Prevention Systems

  • Types of IDS
  • Host and Network based IDS
  • IPS
  • Honeypots
  • Introduction to Snort


Module 4: Introduction to Data Mining and Machine Learning Concepts

  • Supervised /Unsupervised Machine Learning Methods
  • Challenges in Data Mining and Machine Learning


Module 5: Data Collection and Analysis

  • Machine Learning for Anomaly Detection
  • Machine Learning in Intrusion Detection
  • Machine Learning and Network Traffic
  • Emerging Challenges in Cybersecurity

Module 6: Network Forensics

  • Forensic Principles
  • Capturing Network Traffic
  • Use of Cyber Forensic Tools
  • Legal issues

Who Should Attend

  • Cyber Security Stuff
  • Network Engineers
  • IT Administrators

Prerequisite

Nil

Trainers

Cyber Security TrainerDr. Sarita Singh received her Ph.D. degree for her work done in the area of Information Security. She is the recipient of the prestigious Infosys fellowship for pursuing her Ph.D. Programme. She has more than twenty-five years of teaching and research experience in Singapore, Malaysia and India in the field of Programming, Information Security, Web-application Development, Computer Networks and Engineering related modules.

She has presented papers at several National and International Conferences and has written articles for magazines. She has authored text-books for Engineering courses as well.

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