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Gefördert durch das Kompetenzzentrenprogramm DI Alfred Wertner 19. September 2014 Ubiquitous Personal Computing © Know-Center 2014 www.know-center.at Security.

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Presentation on theme: "Gefördert durch das Kompetenzzentrenprogramm DI Alfred Wertner 19. September 2014 Ubiquitous Personal Computing © Know-Center 2014 www.know-center.at Security."— Presentation transcript:

1 gefördert durch das Kompetenzzentrenprogramm DI Alfred Wertner 19. September 2014 Ubiquitous Personal Computing © Know-Center 2014 www.know-center.at Security Concepts for a Distributed Architecture for Activity Logging and Analysis

2 © Know-Center 2014 2 Overview  Activity Logging and Analysis  Use case  Privacy concerns  Focus here: prevent unauthorised access  System Architecture  Security analysis  Assets  Vulnerabilities  Attackers  Threats  Security concepts

3 © Know-Center 2014 3 Activity Logging and Analysis  From data to activity

4 © Know-Center 2014 4 Activity Logging and Analysis  Use Case: Support Time Management  Help people to reflect on time management issues  Detect „Types of Activity“  E.g. Application Use, Travelling, Communicating, Reading, Writing  Trigger reflection  Show history of activities  Reflection diary

5 © Know-Center 2014 5 Activity Logging and Analysis  Privacy Concerns  Data is highly sensitive  Need Privacy-Respecting Systems  Privacy-Respecting Systems  Protect user identity  Control what kind of data is collected  Control data collection  Protect against unauthorised access

6 © Know-Center 2014 6 Activity Logging and Analysis  Privacy Concerns  Data is highly sensitive  Need Privacy-Respecting Systems  Privacy-Respecting Systems  Protect user identity  Control what kind of data is collected  Control data collection  Protect against unauthorised access

7 © Know-Center 2014 7 System Architecture  Sensors  Log data  From Hardware Sensors  E.g. accelerometer  By itself  E.g. logging foreground windows  Send data to Sensor Hub

8 © Know-Center 2014 8 System Architecture  Sensors  Sensor Hub  Sensor configuration  Local data storage  Data transmission to server

9 © Know-Center 2014 9 System Architecture  Sensors  Sensor Hub  Server  Receives data from Sensor Hub, Client Services and Applications  Stores data  Answers requests from Client Services and Applications

10 © Know-Center 2014 10 System Architecture  Sensors  Sensor Hub  Server  Client Services and Applications  Access/Modify data on the server

11 © Know-Center 2014 11 Security Analysis  Asset = Data  Vulnerabilities  Physical access  Logical access  Physical access  Log into or steal device  Network cable infrastructure  Logical access  Installation of Malware

12 © Know-Center 2014 12 Security Analysis  Asset = Data  Vulnerabilities  Physical access  Logical access  Physical access  Log into or steal device  Network cable infrastructure  Logical access  Installation of Malware Who will be attackers with a strong motivation?

13 © Know-Center 2014 13 Security Analysis - Attackers

14 © Know-Center 2014 14 Security Analysis - Attackers

15 © Know-Center 2014 15 Security Analysis - Threats High Risk Threats  By Management  Physical access of victim‘s device  Read/Modify logged data

16 © Know-Center 2014 16 Security Analysis - Threats High Risk Threats  By Management  Physical access of victim‘s device  Read/Modify logged data  By Management + Sys. Admin.  Physical access of victim‘s device and server  Read/Modify logged data

17 © Know-Center 2014 17 Security Analysis - Threats High risk Medium risk  By Management + Sys. Admin.  Intercept network communication  More effort to implement  Limited to information sent

18 © Know-Center 2014 18 Security Analysis - Threats High risk Medium risk  By Management + Sys. Admin.  Intercept network communication  More effort to implement  Limited to information sent  By Management + Sys. Admin.  Intercept communication between sensors and hub  More effort to implement

19 © Know-Center 2014 19 Security Analysis - Threats High risk Medium risk Low risk  By Cyber Criminal  Malware reads logged data

20 © Know-Center 2014 20 Security Concepts – Data Collection I  Hub encrypts data prior storing  Using a stream cipher  Initialisation with server‘s public key  Pro‘s  Protects against unauthorised reads  Need only one key pair  Private key resides on the server  Con‘s  User can not edit data locally  No protection against Malware

21 © Know-Center 2014 21 Security Concepts – Data Collection II  Encrypted storage of data  Use stream cipher  Initialisation with user‘s public key  Pro‘s  Protects against unauthorised reads  User can edit data locally  Con‘s  Security depends on password strength of user‘s private key  No protection against Malware

22 © Know-Center 2014 22 Security Concepts – Communication  Encrypted data communication  Standard HTTPS  Data Collection I  Authentication at server  Authentication of Sensor Hub  On start up  Prior to sending data

23 © Know-Center 2014 23 Security Concepts – Server I  Encrypted storage of data  Trusted Platform Module  Pro‘s  High security  Protection against unauthorised reads + Malware  No user interaction for data decryption necessary  Con‘s  Relatively new technology  Harder to implement

24 © Know-Center 2014 24 Security Concepts – Server II  Encrypted storage of data  Pro‘s  Easier to implement  Con‘s  User interaction required on server start up  No Malware protection


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