Security of IT systems 1000-OG-EN-SITS

• Types of network security: Firewalls, Email security, Antivirus and antimalware protection, Cloud Security, Mobile device security, etc.
• Cybersecurity threats: Phishing, Ransomware, Malware, Social engineering, Denial-of-service (DoS) attacks, Man-in-the-middle (MitM) attacks
• Email security, Email spoofing, Money scams, Email Encryption, Spam
• Application security, Computer viruses, antivirus and antimalware protection, Data loss prevention
• User Authentication and Authorisation, Encryption, VPN
• Web security, Wireless network security
• Internet of Things devices (IoT devices), Smart Home, Smartphones and Cloud Security
• Social engineering methods

Total student workload

Contact hours with teacher: - participation in lectures - 30 hrs - participation in the laboratory - 30 hrs Self-study hours: - preparation for lectures - 15 hrs - preparation for laboratory - 20 hrs - reading literature - 20 hrs - preparation for written examination - 20 hrs - preparation for test - 15 hrs Altogether: 150 hrs (6 ECTS)

Learning outcomes - knowledge

Student W1: knows basic concepts of network security W2: possesses advanced knowledge of the most pervasive cybersecurity threats W3: is familiar with the current problems related to the security of recently created products and technologies These realize the following learning outcomes of studies in computer science: W1 – K_W12 W2 – K_W12, K_W13 W3 – K_W12, K_W13

Learning outcomes - skills

Student U1: is able to recognize the most pervasive cybersecurity threats U2: is capable of formulating the basic authentication methods U3: can use protocols (such as email) and software (such as office suite) responsibly U4: can analyze the social engineering methods These realize the following learning outcomes of studies in computer science: U1 – K_U01, K_U25 U2 – K_U13 U3 – K_U01, K_U13 U4 – K_U02, K_U13

Learning outcomes - social competencies

Student K1: understands the significance of security of IT systems K2: identifies the cybersecurity threats K3: is prepared to identify social engineering methods These realize the following learning outcomes of studies in computer science: K1 – K_K01, K_K02 K2 – K_K01, K_K02 K3 – K_K01, K_K02

Teaching methods

Expository teaching methods: - description - informative (conventional) lecture - participatory lecture - problem-based lecture Exploratory teaching methods: - classic problem-solving - laboratory

Observation/demonstration teaching methods

- display

Expository teaching methods

- description
- informative (conventional) lecture
- discussion

Exploratory teaching methods

- classic problem-solving
- situational

Online teaching methods

- content-presentation-oriented methods
- evaluative methods
- methods referring to authentic or fictitious situations
- methods developing reflexive thinking

Prerequisites

Basic computer skills

Course coordinators

Term 2023/24L:

Marcin Gąsiorek
Katarzyna Zając

Term 2025/26Z:

Marcin Gąsiorek
Katarzyna Zając

Term 2022/23L:

Katarzyna Zając

Term 2024/25Z:

Katarzyna Zając

Assessment criteria

Assessment methods:
Lectures - written examination - W1, W2, W3, K1, K2
Laboratory - test - U1, U2, U3, U4, K1, K2
Assessment criteria:
fail: 0% - 39%
satisfactory: 40% - 49%
satisfactory plus: 50% - 59%
good: 60% - 69%
good plus: 70% - 79%
very good: 80% - 100%

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 1000-OG-EN-SITS in USOSweb