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Microsoft Cloud Computing Research Centre

Microsoft Cloud Computing Research Centre. Cloud Panopticon: Technical History. 1 st Annual Symposium, Cambridge 2014. Jon Crowcroft j on.crowcroft@cl.cam.ac.uk. Brief History of Surveillance Immune System. We’ve been here before

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Microsoft Cloud Computing Research Centre

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  1. Microsoft Cloud Computing Research Centre Cloud Panopticon: Technical History 1st Annual Symposium, Cambridge 2014 Jon Crowcroft jon.crowcroft@cl.cam.ac.uk

  2. Brief History of Surveillance Immune System • We’ve been here before • mid 1990s lawful intercept agencies pressured Internet Community to weaken its tech • Response was (aptly numbered) rfc1984 • http://tools.ietf.org/html/rfc1984 • IAB/IESG/Internet Society/IETF • Attacks included • Weakened keys, Key escrow • Weaknesses included • “Conflicting International Policies • Use of multiple layered encryption

  3. What happened next? IETF “won” • TLS/HTTPS started to become routine • DNSSec & Certifcates • Cryptography • Better securing of infrastructure

  4. Surveillance and DPI • Tech for deep packet inspection, e.g. Endace • Initially developed for traffic engineering • to reveal popular application sest and traffic matrix • Became widely used for full packet capture at IXPs • Port mirrors all the data to security agency • Response: accelerate default use of HTTPs/TLS • Together with NATs, makes network intercept worthless • Even for “meta-data”

  5. What happens next? • Around this time, dominant traffic became • Mobile Device (many) <-> Cloud provider (few) • Key changes are: • Even more obfucasted (and secure) end points, but • Far far less, highly visible end points • instead of 100M NATd desktops talking to 100M websites, • we have a billion smart phones talking to a dozen cloud providers, almost all of latter in the US • Attack surface very very obvious

  6. Surveillance on Cloud • Was easy because: • Easy to find cloud data centers • Data stored in plain, so that analytics can work • Data between cloud machines was txferred in plain • Data is processed in the plain, so that targeted adverts can work • i.e. the main (2 sided) business model of cloud makes them idea to be weaponised.

  7. What happened next • Those revelations… • Embarrassed & annoyed “libertarian” tech cloudsters • Vancouver IETF plenary response vehement • Tech “solutions” • Crypt data between data centers (google) • Crypt data in storage (most) • Client side decrypt (apple) • Research in cryptic processing is ongoing

  8. Future • Securing key distribution (see RFC1984) • Viable solutions for cloud service on crypted data • Search, targeted ads, solutions exist • Analytics – could use trusted 3rd party now • Later, we’ll see

  9. What happens to lawful intercept? • Two extremes • They lose • They have to do their job properly and • Have probable cause • get warrants • Do intelligence… • Law mandates client side trapdoors (against RFC1984)

  10. Conclusion • The arms race between • security agencies and bad guys on the one hand • And the public on the other • Is not new • Is not over • Is not transparent • or informed by good cost benefit analysis; • see for example this Cato report • Responsible Counterterrorism Policy • http://www.cato.org/publications/policy-analysis/

  11. Microsoft Cloud Computing Research Centre Regional clouds: technical considerations 1st Annual Symposium, Cambridge 2014 Jon Crowcroft jon.crowcroft@cl.cam.ac.uk Jat Singh jatinder.singh@cl.cam.ac.uk

  12. Regional Clouds • Hard to define, many outstanding issues • Management and control underpins the rhetoric • Who has the power (capability), who is trusted. • Technical mechanisms for management • Offerings in a regional-cloud context • Implications - does this make sense? • Research, improving industrial ‘best-practices’

  13. Outline Explore different levels of the technical stack Focus: • Network-level routing • Cloud provisioning • Cryptography • Flowcontrols (‘data tagging’)

  14. Internet & Routing Controls • Autonomous Systems (AS): ‘sections’ of the network • Internet exchange points: exchange between AS • Border Gateway Protocol encapsulates the routing policy between networks • In practice, routing policy reflects peering/service/business arrangements

  15. Internet & routing controls (regional clouds) • Cloud providers manage their infrastructure • Many already account for geography for better service provisioning (performance, latency, etc.) • Bigger providers already involved in peering arrangements • Technically feasible with right incentives to ensure that data is routed within a geographical boundary E.g. economic benefits, regulation, … • But such an approach is blunt • applies to all traffic, regardless

  16. Cloud provisioning: service levels • Provider manages that below, tenants above • Different management concerns for each service offering Maybe Illustrate Tenants/users

  17. Cloud provisioning: service offerings • Already work on tailoring services to particular constraints • Differential privacy: tailor query results to not reveal too much private information • Already offer services based on user/tenant locale • Not only for performance, but also security, rights management, etc. (e.g. iPlayer) • Providers already manage their infrastructure • Customising service and content for regional concerns • Thus, already the capability to tailor services for particular regional and/or jurisdictional concerns

  18. Cloud provisioning: Unikernels • Cloud exists to leverage shared infrastructure • Isolation is important: • VMs – Separate for tenants, complete OS, managed by hypervisor • Containers – shared OS, isolated users • Deployment heavy, isolation overheads, … • Future? Unikernels: • library OS, build/compile a VM with only that required • Hypervisor managed, removes user-space isolation concerns

  19. Cloud provisioning: Unikernels (2) • Very small, lightweight easily deployed VMs: • Easily moved around the infrastructure • Deploy in locales/jurisdictions when/where relevant • Facilitates customised services • Specific unikernels for particular services • Encapsulating specific jurisdictional requirements? • Transparency: Natural audit trail • “Pulls” that what is required to build, on demand

  20. Data-centric controls

  21. Cryptography • Range of purposes: • Data protection: storage, transit, comm. channels • Authentication, certification, attestation, etc. • Encryption • Unintelligible, except those with the keys • encrypt(plaintext, key) => ciphertext • decrypt(ciphertext, key) => plaintext • Regional Q: Who can (potentially) access the keys?

  22. Client-side encryption Cloud provider • Cloud services • Computation generally on plaintext • Fully homomorphic encryption not practicable (yet) • Encrypted search, privacy-preserving targeted ads Client C P

  23. Encryption and keys • Who could access the keys? • Trust and legal regime(s) • Client-held keys • Cloud providers holding client keys • Providers now (internally) use crypto provisioning • Trusted third-parties: CAs, Key-escrows • Key management isn’t easy • Vulnerabilities: compromised keys, broken schemes and/or implementations • Transparency: when was data decrypted?

  24. Flow controls: data tagging • ‘Tag’ data to • track, and • control where it flows • Metadata ‘stuck’ to data to effect data management policy • Cloud benefits: • Management within the provider’s realm • Control and/or assurance, transparency • Various approaches • E.g. CSN @ Imperial: tenants collaborate to find leaks • Information Flow Control (IFC)

  25. IFC: Regional isolation at application-level • Entities run in a ‘security context’ (tagged) • Tags: <concern, specifier> Service X <zone, EU> Database <zone, EU> ✔ ✔ Application 1 <zone, EU> <zone, EU> <zone, EU> <zone, EU> Service X <zone, US> ✖ • All context and flows audited • Mechanisms for EU->US, but trusted, privileged (audited!)

  26. IFC: Ongoing work • Experimenting at the OS level, all application-level I/O • System-calls within, messaging across machines • Requires a trusted-computing base • Protects at levels above enforcement • Much more to do! • Enforcement: Small as possible, verifiable, hardware • Policy specification • Privilege management • Tag specifications and naming

  27. IFC in the cloud • Control and transparency • Within the realm of the cloud provider • Data-centric, fine-grained isolation • Enforcement naturally leads to audit • Aims at compliance/assurance, generally not spooks • Potential for virtual jurisdiction? • Cloud isolates/offers services for specific jurisdictions

  28. Conclusion • Regional cloud issues concern data management • Technical mechanisms for control, and transparency • Different mechanisms at different technical levels • Different capabilities, visibility • Developments in this space • Improve cloud best practice • May address concerns underpinning the balkanisationrhetoric

  29. To summarise • Nearly 20 yrs ago, CALEA asked us to colludge in weaker security for everyone • This would be bad for civil society, so • We said no! • Now Snowden reveals that we were ignored • Tit-for-tat is optimal strategy: • This time we will make it no!

  30. Technical workshop CLaw: Legal and technical issues in cloud computing IC2E: IEEE International Conference on Cloud Engineering (Mar 2015) http://conferences.computer.org/IC2E/2015

  31. Information Flow Control: Regional example (2) • Only privileged, trusted, entities may change context • Encrypt EU data before sending Context change Audit <zone, US> Application 1 <zone, EU> Application 1 <zone, US> Application 2 <zone, US> ✔

  32. Information Flow Control: Regional example (2) • More accurate… zone-mixer <zone, EU> <zone, US> ✔ NB this isn’t “application 1”, as it’s previous outputs would have had US and EU tagged outputs… Context change <zone, US> <zone, EU> Application 2 <zone, US> Audit ✔ zone-mixer <zone, US>

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