Why?
Every data scientist handles sensitive data. Understanding threats, laws, risk and the technical controls that protect information is part of doing the job responsibly.
What?
An introduction to information security and privacy: the need for security and the main threats, legal, ethical and professional issues, risk management, access control and authentication, database security, security technologies (firewalls, VPNs, IDS/IPS, backups) and cryptographic tools.
Curriculum:
Introduction to Data Security and Privacy
Core security concepts, the CIA triad, security models and why data security and privacy matter.
The Need for Security
Threats to data and information systems, common attacks, and the primary mission of data security.
Legal, Ethical and Professional Issues
Laws and regulations, ethical responsibilities, professional codes and how organisations limit liability.
Risk Management
Identifying, classifying and prioritising assets, threat assessment, risk assessment and controls to reduce risk.
Access Control and User Authentication
Mandatory and discretionary access control, authentication factors, and how systems decide who may enter a trusted area.
Database Security
Why databases need dedicated protection, attacks and defences such as SQL injection, and database encryption.
Security and Backup Technologies
Firewalls, VPNs, intrusion detection and prevention systems, other security tools and backup technologies.
Using Encryption
Cryptography and cryptanalysis, symmetric and asymmetric encryption, hashing and digital signatures as tools for data security.
Notes
Mostly theory with short exercises. Based on Whitman and Mattord's Principles of Information Security and Stallings' Computer Security.