程序代写 python data structure database deep learning data mining information theory algorithm Subject Overview & Introduction to Cybersecurity – cscodehelp代写
Subject Overview & Introduction to Cybersecurity
COMP90073 Security Analytics
Dr. & Dr. , CIS Semester 2, 2021
COMP90073 Security Analytics © University of Melbourne 2021
General Information
Lecturers:
• Dr , MC Level 3, Room 3.3321, • Dr ,
Tutor:
• Yujing Mark Jiang,
Lectures:
• Tuesdays and Thursdays, 14:15–15:15pm, Zoom Tutorials: (per your registration) Start in Week 2 Consultation session:
• Fridays 2-3pm, Zoom
COMP90073 Security Analytics © University of Melbourne 2021
General Information
Lecture Materials:
• Lecture slides available on LMS, lectures recorded on Lecture Capture
Feedback:
• During/after lecture
• Tutorials
• Discussion board
• Consultation sessions
• Assignment feedback
• Sarah/Yi (by announcement or by appointment)
COMP90073 Security Analytics © University of Melbourne 2021
Prerequisites
Subjects:
• COMP90049 Introduction to Machine Learning
(Knowledge Technologies), or COMP30027 Machine Learning
• COMP90007 Internet Technology, or COMP30023 Computer Systems
Skills:
• Data structures & algorithms coding in Python
• Familiarity with formal mathematical notation
• Basic understanding of statistics and information theory
This subject does not include programming language tuition.
COMP90073 Security Analytics © University of Melbourne 2021
Assessment
Assessment:
• 60% exam, 40% project Requirements:
• 20/40 project hurdle, 30/60 exam hurdle, 50/100 overall
Projects:
• Project 1 will be released in week 2 and due in week 5. • Project 2 will be released in week 5 and due in week 11.
(Dates to be confirmed in project specification on subject LMS site) • You are expected to complete these individually.
• We will discuss the project in more detail over the coming weeks. Note that the non-teaching week is between weeks 8 and 9.
COMP90073 Security Analytics © University of Melbourne 2021
COMP90073 Subject Overview from Handbook
• Aim:
“Security Analytics will examine how we can automate the analysis of our data to better detect and predict security incidents and vulnerabilities within our networks and organisations.”
• Indicative Content:
“The subject will first introduce the types of data sources that are relevant
to detecting different types of security threats in practice.
The second part of the subject will introduce methods from machine learning that are widely used for cyber security analysis.
The third part of the subject will introduce some of the theoretical challenges and emerging issues for security analytics research, based on recent trends in the evolution of security threats.”
COMP90073 Security Analytics © University of Melbourne 2021
What the Subject Covers
• Exposure to a range of computing technologies for:
– Understanding network traffic.
– Accomplishing tasks that may not be well-specified or well- understood.
– Exploring vulnerabilities of machine learning.
• A broader understanding of the kinds of things that can – and can’t – be
accomplished computationally.
• Insight into some research activities in computing, why they are undertaken, and how.
COMP90073 Security Analytics © University of Melbourne 2021
Content
Week 1-4 (Yi):
• Cybersecuritylandscape
• Networksecurity&attacks • BotnetandDDoS
Week 5-8 (Sarah):
• Unsupervisedmachinelearning • Anomalydetection
• Alertmanagement
Week 9-12 (Yi):
• Adversarialmachinelearning–vulnerabilities
• Adversarialmachinelearning–explanation,detectionanddefence • Adversarialreinforcementlearning
COMP90073 Security Analytics © University of Melbourne 2021
Texts and references
There is no prescribed text. You may find these useful:
• and Xian Du, Data Mining and Machine Learning in Cybersecurity, 2011.
• Chio and Freeman, Machine Learning and Security, 2018.
• Goodfellow et al., Deep Learning, 2016.
https://www.deeplearningbook.org/
• Bhattacharyya et al., Network Traffic Anomaly Detection and Prevention: Concepts, Techniques, and Tools, 2017.
• Han et al., Data Mining Concepts and Techniques, 2000
• . Tipton, Official (ISC)2 guide to the CISSP CBK, 2010
COMP90073 Security Analytics © University of Melbourne 2021
Outline
• Rising Cybersecurity Attacks
• Current Cyber Security Talent Gap • Core Cyber Security Principles
• Key Access Control Concepts
• Access Control Principles
COMP90073 Security Analytics © University of Melbourne 2021
Rising Cybersecurity Attacks
• Overall trend
– Cybercrime costs globally: $3 trillion in 2015$10.5 trillion in 2025 – 3rd largest economy
Cybercrime costs.
Source: https://www.embroker.com/blog/cyber-attack-statistics/
https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)
COMP90073 Security Analytics © University of Melbourne 2021
Rising Cybersecurity Attacks
• Cyber incidents by industry
COMP90073 Security Analytics © University of Melbourne 2021
Rising Cybersecurity Attacks
• Incidents
– Oil pipeline hit by DarkSide ransomware group
Source: https://www.rt.com/usa/524269-colonial-pipeline-ransom-hackers/
COMP90073 Security Analytics © University of Melbourne 2021
Rising Cybersecurity Attacks
