Presentation by Akla-Esso Tchao and Giovanna Di Marzo Serugendo at the 2nd Awareness Workshop on Challenges for Achieving Self-awareness in Autonomic Systems @ SASO 2012, Lyon, France

1. SmartContent: A self-protecting and context-
aware active content
Akla-Esso Tchao, Giovanna Di Marzo Serugendo
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2. Overview
 Introduction
 SmartContent Model
 SmartContent Protection
 SmartContent Adaptability
 Conclusion
SmartContent: A self-protecting and context-aware active content
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3. Introduction :: Context
 Development of communications systems:
 Anyone can be a content producer
 Almost everyone carries a personal computing device
 Easier than ever to publish content over the Internet or among
devices
Facebook Podcast
Blogs
Flickr Personal
Content
You Tube File sharing
Twitter sites
SmartContent: A self-protecting and context-aware active content
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4. Introduction :: Problem
 Problem:
 Information theft and personal content redistributed without content
owner authorization
 Propagation of content and copies are hard to control
 Example:
 Lost of sensitive data by banks or administrations
 No control of private data on social networks (Facebook, etc…)
 Unauthorized copyrighted file sharing. According to IFPI report 2010,
one in five people across Europe’s top markets are engaged in
unauthorized file sharing
SmartContent: A self-protecting and context-aware active content
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5. Introduction :: Existing solutions and problem
 Existing solutions
 Cryptography
 DRM
 Digital watermarking
 Problems
 No persistent content protection
 Too expensive to deploy
 Too much restriction and lack of flexibility
 No context information taken into account in the decision process
 No adaptability
SmartContent: A self-protecting and context-aware active content
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6. Introduction :: Targeted example
 Sensitive data held by banks or administrations
Home: Access to content denied Office: access to content granted on
any device, in presence of appropriate
customers, within corporate perimeters
SmartContent: A self-protecting and context-aware active content
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7. Introduction :: Targeted example
SmartContent: A self-protecting and context-aware active content
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8. Introduction :: Targeted example
 A location based content protection
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9. Introduction :: Objective
 Content that can protect itself against unauthorized
access
 Content that has the notion of context
 Content that can adapt to unforeseen situations
 Easy to deploy and use
 Solution  SmartContent
SmartContent: A self-protecting and context-aware active content
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10. Overview
 Introduction
 SmartContent Model
 SmartContent Protection
 SmartContent Adaptability
 Conclusion
SmartContent: A self-protecting and context-aware active content
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11. SmartContent Model
 SmartContent is an agent, embedded with:
 Protected content
 Sensed context Policies
 Policies
 Reasoning entity Crypto Protected Sensed
entity Content context
 Cryptographic entity Renderer
 The Renderer Reasoning
entity
SmartContent
SmartContent: A self-protecting and context-aware active content
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12. SmartContent Model :: Interaction
SmartContent: A self-protecting and context-aware active content
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13. SmartContent Model :: Targeted example
SmartContent: A self-protecting and context-aware active content
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14. SmartContent Model :: Example
 SmartContent
 Sensed context
 Policies
SmartContent: A self-protecting and context-aware active content
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15. SmartContent Model :: Example
 Reasoning entity
 Action (A), Location (L) and Policy (P)  Decision
SmartContent: A self-protecting and context-aware active content
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16. Overview
 Introduction
 SmartContent Model
 SmartContent Protection
 SmartContent Adaptability
 Conclusion
SmartContent: A self-protecting and context-aware active content
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17. SmartContent Protection
 Several levels of protection
 First level using cryptographic algorithms
 Second level using obfuscation technique
SmartContent: A self-protecting and context-aware active content
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18. SmartContent Protection
SmartContent: A self-protecting and context-aware active content
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19. Overview
 Introduction
 SmartContent Model
 SmartContent Protection
 SmartContent Adaptability
 Conclusion
SmartContent: A self-protecting and context-aware active content
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20. SmartContent adaptability
 Controlled environment, adaptability through:
 Several policies and reasoning algorithms inside SmartContent
 Dynamic update and modification of policies
P3
P2 P4
P1
Crypto Protected Sensed
entity Content context
Renderer
R1
R2 R3 R4
SmartContent
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21. SmartContent adaptability
 Uncontrolled environment, adaptability through:
 Use of Negative selection algorithm of AIS
 Co-stimulation signal
 Negative Selection mechanism:
 Ability of the human immune system to distinguish from cells of the
organism : self and the foreign elements known as non-self
 Two phases
 Censoring Phase  Generation of self and non-self set
 Monitoring phase  Detector set (non-self set) put to work
 Co-stimulation signal
 Signal from external entity, confirm or not if a foreign body is self or
not
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22. SmartContent adaptability :: Targeted example
SmartContent: A self-protecting and context-aware active content
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23. Examples :: A location based content protection
 SmartContent with AIS
 Sensed context
 Policies
Self
Self
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24. Examples :: A location based content protection
 Non-self patterns generation (Censoring phase of AIS)
Non-Self
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25. Examples :: A location based content protection
 Reasoning (Monitoring phase of AIS)
SmartContent: A self-protecting and context-aware active content
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26. Overview
 Introduction
 SmartContent Model
 SmartContent Protection
 SmartContent Adaptability
 Conclusion
SmartContent: A self-protecting and context-aware active content
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27. Conclusion
 Proposed a model for context aware self-protecting content
 Flexible model that support adaptability
 Future work:
 Implementation focus on context as location
 Indoor localization
 Exploit existing technologies RFID for indoor localization and experiment
with SmartContent
 Develop an indoor positioning algorithm to retrieve precise GPS
positions using readily available sensors in mobiles devices
 Map SmartContent into SAPERE framework
 Experiment with different adaptability mechanisms
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28. ACKNOWLEDGEMENT
 EU-FP7-FET Proactive project SAPERE — Self-aware
Pervasive Service Ecosystems, under contract
no.256873
 Collaboration: University of Geneva, University of
Bologna, University of Modena, University of Linz and
University of St-Andrews
 More information: http://www.sapere-project.eu
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29. Thank you!
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