CN presentation

18
Security and Privacy Implications of Pervasive Memory Augmentation Authors: Nigel Davis, Adrian Friday, Sarah Clinch, Corina Sas, Marc Langheinrich, Geoff Ward, Albrecht Schmidt. Presented By: Aadil Ahmed Adam Sindhuja G Naik

Transcript of CN presentation

Page 1: CN presentation

Security and Privacy Implications of Pervasive Memory Augmentation

Authors: Nigel Davis, Adrian Friday, Sarah Clinch, Corina Sas,

Marc Langheinrich, Geoff Ward, Albrecht Schmidt.

Presented By: Aadil Ahmed Adam Sindhuja G Naik

Page 2: CN presentation

Contents

• Introduction

• Related work in memory augmentation

• Application domains

• Architecture of present system

• Future architecture system

• Security and privacy threats

Page 3: CN presentation

Introduction

What is Pervasive Computing? What is Memory Augmentation?

Page 4: CN presentation

Continued…..• New ways of augmenting human memory:

Near-continuous collection of memory cues.

Advances in data storage and processing enables mining of stored cues for proactive presentation.

Presence of ubiquitous displays.

• Capturing large amount of data of an individual’s experiences and using it to trigger recall is useful but raises many security concerns.

Page 5: CN presentation

Related work in memory augmentation

• Capturing of digital data for total recall, e.g. SenseCam photos.

• Questions against lifelogging’s total recall?

• Autobiographical memories are resilient to deliberate efforts to forget.

• Disposal of digital artifacts through selective deletion is suggested.

• Future work on forgetting needed to preserve privacy in lifelogging technologies.

Page 6: CN presentation

Application domains

1. Behavior change• Important objective in healthcare,

transportation etc.

• Difficulty in implementing planned behavior.

• Intentional behaviors are likely to be implemented when individuals are reminded of their own attitude.

• Realistic scheduling is important.

• Behavior is performed if its perceived as achievable and enjoyable.

Page 7: CN presentation

Continued….

2. Learning • Use of ambient displays, reinforcing the learning of a wide range of skills.

• E.g. A study-abroad student could learn culturally-significant facts as they explore a new city.

Page 8: CN presentation

Continued….3. Supporting failing memories• Un-cued recall vulnerable to age-related

decline.

• Provide older people with time-reverent

and context-appropriate cues.

• Enjoy greater self-confidence and better

relationships.

4. Selective recall• Attenuate the spontaneous retrieval of

related but un-reviewed memories.

Page 9: CN presentation

Continued….

5. Advertising• Users have memories triggered explicitly to

drive purchasing decisions.

6. Social acceptance• Image based lifelogging devices not accepted.

• Location information tracked by mobile devices improve memory construction.

• Non image based lifelogging devices provide wealth of information.

• Cultural differences exist in terms of technology acceptance.

Page 10: CN presentation

Architecture of present system

• Experience data was gathered by devices worn or carried by a user.• Stored or uploaded to cloud-based servers.

Page 11: CN presentation

Continued…..

• The visual and auditory channels are dominant and recording these are a focus in humans.

• Capturing meta information like time and location adds significant value to the data.

Disadvantage:• Relies on data captured exclusively by a specific user.

• Reduces the number of data streams available hence reducing the quality.

• E.g. using microphone on a mobile device in user’s pocket offers poorer results than using a high-quality audio conferencing microphone built into meeting room.

Page 12: CN presentation

Architecture of future system

• Rely on the ability to appropriate screen real-estate from the large number of displays that the user already looks at as part of their daily activities. E.g. Photo frames, google mail

• Forms complex eco-systems of experience capture, storage and presentation devices rather than the user-centric approaches employed.

Page 13: CN presentation

Security and privacy threats

1. Experience provenance• Data streams that constitute an individual’s memories are sourced from devices

not worn by the user.

• These data sources represent a point of attack against pervasive memory augmentation.

• The challenge is that user may review captured experience long after the event and it is impossible to detect that the original data stream was defective.

• Necessary to develop solutions that are able to provide end-to-end guarantees for the user of the provenance of the data.

Page 14: CN presentation

Continued…

2. Memory Protection• Data store is highly distributed and will be accessed by a wide range of

parties.

• Applications designed to support recall may require access to this data.

• Will require sophisticated access control mechanisms with simple user interactions.

• Managing digital assets after death is starting to attract research attention.

• Inheritance, ownership, and control issues pose challenge with regard to the range of stakeholders involved.

• In developing solutions to these challenges, researchers need to reassure users that their memories will be protected not just for short term but for years to come.

Page 15: CN presentation

Continued….3. Memory manipulation• Cued recall can be both used to re-enforce and attenuate human

memories.

• E.g. advertises and brand companies could pursue campaigns to forget bad experiences and “only remember the good times”.

• Cues and memory need not be generic but can be specific to each individual leading to more effective forms of memory manipulation.

• Key challenge – how can user tell if their memories are being manipulated?

• Necessary to enable users to instantiate real-time monitoring of the cues.

• E.g. virus checker for our memories monitoring activity to identify suspicious patterns.

Page 16: CN presentation

Continued….

4. Privacy of bystanders• Use of personal capture technology would impact the privacy of

bystanders.

• Challenge- how to protect bystanders while allowing substantial data collection for human memory augmentation?

• Focus on technologies that do not actually record anything but instead work like simple detectors. E.g. audio detectors.

• In video recording devices, instead of high-fidelity video capture, only certain abstract elements of scene is recorded.

• Solutions are likely to combine elements of new technologies for creating abstract recordings with a robust way of announcing recording practices and policies to users.

Page 17: CN presentation

Conclusion

• While benefits of pervasive memory augmentation are significant, such systems challenge areas of security and privacy.

• Despite increasing ability to produce and store information, our society still follows approach of selective capture and storage.

• Once memory augmentation systems become mainstream, we may see radical transition from selective preservation to preserve everything and only selectively remove parts which are inappropriate.

Page 18: CN presentation

THANK YOU……… !!!!!