CS573 Data privacy and security in the cloud

1. CS573 Data privacy and security in the cloud Slide credits: RagibHasan, Johns Hopkins University

2. What is Cloud Computing? Let’s hear from the “experts”

3. What is Cloud Computing? The infinite wisdom of the crowds (via Google Suggest)

4. What is Cloud Computing? We’ve redefined Cloud Computing to include everything that we already do. . . . I don’t understand what we would do differently in the light of Cloud Computing other than change the wording of some of our ads. Larry Ellison, founder of Oracle

5. What is Cloud Computing? It’s stupidity. It’s worse than stupidity: it’s a marketing hype campaign Richard Stallman GNU

6. What is Cloud Computing? Cloud Computing will become a focal point of our work in security. I’m optimistic … Ron Rivest The R of RSA

7. So, What really is Cloud Computing? Cloud computing is a new computing paradigm, involving data and/or computation outsourcing, with • Infinite and elastic resource scalability • On demand “just-in-time” provisioning • No upfront cost … pay-as-you-go That is, use as much or as less you need, use only when you want, and pay only what you use,

8. The real story “Computing Utility” – holy grail of computer science in the 1960s. Code name: MULTICS • Why it failed? • Ahead of time … lack of communication tech. (In other words, there was NO (public) Internet) • And personal computer became cheaper and stronger

9. The real story Mid to late ’90s, Grid computing was proposed to link and share computing resources

10. The real story … continued Post-dot-com bust, big companies ended up with large data centers, with low utilization Solution: Throw in virtualization technology, and sell the excess computing power And thus, Cloud Computing was born …

11. Cloud computing means selling “X as a service” IaaS: Infrastructure as a Service • Selling virtualized hardware PaaS: Platform as a service • Access to a configurable platform/API SaaS: Software as a service • Software that runs on top of a cloud

12. Cloud computing architecture e.g., Web browser SaaS, e.g., Google Docs PaaS, e.g., Google AppEngine IaaS, e.g., Amazon EC2

13. So, if cloud computing is so great, why aren’t everyone doing it? Clouds are still subject to traditional data confidentiality, integrity, availability, and privacy issues, plus some additional attacks

14. Companies are still afraidto use clouds [Chow09ccsw]

15. Anatomy of fear … Confidentiality • Will the sensitive data stored on a cloud remain confidential? Will cloud compromises leak confidential client data (i.e., fear of loss of control over data) • Will the cloud provider itself be honest and won’t peek into the data?

16. Anatomy of fear … Integrity • How do I know that the cloud provider is doing the computations correctly? • How do I ensure that the cloud provider really stored my data without tampering with it?

17. Anatomy of fear … Availability • Will critical systems go down at the client, if the provider is attacked in a Denial of Service attack? • What happens if cloud provider goes out of business?

18. Anatomy of fear … Privacy issues raised via massive data mining • Cloud now stores data from a lot of clients, and can run data mining algorithms to get large amounts of information on clients

19. Anatomy of fear … Increased attack surface • Entity outside the organization now stores and computes data, and so • Attackers can now target the communication link between cloud provider and client • Cloud provider employees can be phished

20. en.600.412 Spring 2011 Anatomy of fear … Legal quagmire and transitive trust issues • Who is responsible for complying with regulations (e.g., SOX, HIPAA, GLBA)? • If cloud provider subcontracts to third party clouds, will the data still be secure?

21. en.600.412 Spring 2011 What we need is to … • Adapt well known techniques for resolving some cloud security issues • Perform new research and innovate to make clouds secure

22. Traditional systems security vsCloud Computing Security Securing a cloud Securing a traditional system

23. Traditional systems security vsCloud Computing Security Analogy Securing a motel Securing a house Owner and user are often the same entity Owner and users are almost invariably distinct entities

24. Traditional systems security vsCloud Computing Security Securing a motel Securing a house Biggest user concerns Securing perimeter Checking for intruders Securing assets Biggest user concern Securing room against (the bad guy in next room | hotel owner)

25. Data Privacy and Security in Cloud: Overview • Novel attacks • Trustworthy cloud architectures • Data integrity and availability • Computation integrity • Data and computation privacy • Data forensics • Misbehavior detection • Malicious use of clouds

26. Co-tenancy in clouds creates new attack vectors A cloud is shared by multiple users Malicious users can now legally be in the same infrastructure Misusing co-tenancy, attackers can launch side channel attacks on victims Research question: How to prevent attackers from exploiting co-tenancy in attacking the infrastructure and/or other clients? Example: the Topology attack on Amazon EC2 (“Hey You! Get off of my Cloud …” CCS 2009)

27. Today’s cloud architectures act like big black boxes Clients have no idea of or control over what is happening inside the cloud Clients are forced to trust cloud providers completely Research Question: How do we design cloud computing architectures that are semi-transparent and provide clients with control over security? Existing Approaches: TCCP (uses TPM), CloudProof

28. Today’s clouds provide no guarantee about outsourced data Amazon’s Terms of services

29. Today’s clouds provide no guarantee about outsourced data Problem: Dishonest cloud providers can throw data away or lose data. Malicious intruders can delete or tamper with data. Clients need reassurance that the outsourced data is available, has not been tampered with, and remains confidential. Research Question: How can clients get assurance/proofs that the cloud provider is actually storing data, is not tampering with data, and can make the data available on-demand? Example Approaches: Provable Data Possession (PDP), Proof of Retrievability (PoR), HAIL

30. Ensuring confidentiality of data in outsourced computation is difficult Most type of computations require decrypting data before any computations If the cloud provider is not trusted, this may result in breach of confidentiality Research Question: How can we ensure confidentiality of data and computations in a cloud? Existing Approaches: Homomorphic encryption, TCCP

31. Clients have no way of verifying computations outsourced to a Cloud Scenario User sends her data processing job to the cloud. Clouds provide dataflow operation as a service (e.g., MapReduce, Hadoop etc.) Problem: Users have no way of evaluating the correctness of results Research question: How can we verify the accuracy of outsourced computation? Existing Approaches: Runtime Attestation, Majority voting, Redundant operations

32. Clouds can be used for malicious purposes Adversaries can rent clouds temporarily to create a large scale botnet very quickly Clouds can be used for spamming, Denial of service, brute force password breaking, and other attacks Example: WPACracker.com – a password cracking service that claims to test 300,000,000 words in 20 minutes for $17, using a cloud Research question: How can we rapidly detect misbehavior of clients in a cloud?

33. Final quote [Cloud Computing] is a security nightmare and it can't be handled in traditional ways. John Chambers CISCO CEO

34. Secure Data Outsourcing

35. Homomorphic encryption • The ability to perform computations on the ciphertext without decrypting it first • A specific algebraic operation performed on the plaintext is equivalent to another (possibly different) algebraic operation performed on the ciphertext

36. A Simple Example • Rot-13 is homomorphic with respect to concatenation

37. Homomorphic encryption schemes • Multiplicative homomorphic – e.g. RSA • Additive homomorphic, e.g. Paillier • Fully homomorphic encryption (FHE) (Gentry, 2010)

38. Alternative techniques • Search encrypted data • Fragmentation • Aggregation • …