Você confiaria a sua vida à nuvem ? Técnicas para a computação terceirizada com privacidade e segurança Hamish Hunt Flavio Bergamaschi Emerging Technologies, IBM Emerging Technologies,IBM
Cloud Computing and Security Security challenges in outsourced computation ▪ Landscape is now asymmetric ▪ Large number of mobile devices ▪ Large compute power in the cloud ▪ No control over the cloud servers ▪ No control over the communication channels ▪ Powerful servers …. untrusted …. or honest but curious
Cloud Computing and Security Security challenges in outsourced computation Input Data Bob Honest but curious Alice Looks at Alice’s data Perform the correct computation, sends Result result to Alice Eve Snoops the Comms Channel See Alice’s data
Cloud Computing and Security Securing the Communications Channel Input Data Bob Honest but curious Alice Looks at Alice’s data Decrypts, performs the Result correct computation, Encrypts/Decrypts encrypts the result before sending. Eve Snoops the Comms Channel Can’t see the data
Cloud Computing and Security Some Cryptographic Notions - 1 ▪ Verifiable delegation How to ensure the encrypted result we get back is the result of the intended computation “F”? Enc(F(x)) vs Enc(F’(x)) ▪ Functional privacy How to protect the computation “F” ▪ Server Privacy The computation being evaluated leaks nothing about the inputs. ▪ Functional encryption Reveals the result of the computation but nothing else. e.g. Spam filter for encrypted email
Cloud Computing and Security Some Cryptographic Notions - 2 ▪ Encrypted Searches Tokenization: **very little security Property preserving encryption Deterministic encryption Everytime Enc(x) generates same cyphertext **very little security Order preserving encryption Takes an ordered universe of plaintext and produces cyphertexts that can be compared/sorted ▪ Searchable Symetric Encryption Encrypts the data in a way that in a way that it can be privately queried Encrypts the search structure Protects the data with standard AES
Cloud Computing and Security Some Cryptographic Notions - 3 ▪ Secure Multi-party computation Multiple participants compute a public function on their private data without revealing the input data and only share the result. e.g. Millionaires problem. ▪ Fully Homomorphic encryption Allows for the computation to be preformed on encrypted data without ever decrypting it Enc(x) + Enc(y) = Enc(x+y) Enc(x) * Exc(y) = Enc(x*y)
Cloud Computing and Security Information Leakages ▪ Access Pattern Leakage ▪ Data Leakage ▪ Control Flow Leakage ▪ Size Leakage
Cloud Computing and Security Struggle between usefulness <-> security How to secure the data in the cloud in a way that we can perform computations on encrypted data ? Useful Security . Computation Homomorphic Secure Multi-party Encrypted Encryption Computation Searches
Computing on Encrypted Data Fully Homomorphic Encryption Input Data Bob Can’t see Alice’s data Alice Doesn’t learn anything. Performs the correct Result computation, without Encrypts/Decrypts decrypting the input or output(result) Eve Snoops the Comms Channel Can’t see the data
Fully Homomorphic Encryption - History Thought about since the 1970s. Can we perform operations on encrypted data without having to first decrypt it? Theoretical Solution first proposed by Craig Gentry (IBM) in 2009 • Prompted quotes like “ Not in my lifetime ” • Original scheme was inefficient and difficult to implement Rapid improvements to the theory have led to algorithmic efficiencies making practical implementations possible .
What can you do that is new? Real Oblivious Transfer Can the bank provide information to the police without knowing the query or the information returned?
Oblivious Genome Sequence Comparison Encrypted Genomes Encrypted Edit Distance IDASH PRIVACY & SECURITY Current Version. WORKSHOP 2015 • Using Commodity Intel-based hardware. • 100k entries ~5 mins on multi-threaded 4 core machine. • Ciphertexts for a security level of 80-100 bits (AES equivalence) are 1000 times larger than the plaintext.
Compute the Edit Distance Av Aw Bv Bw Expected Edit 0 V1 V1 1 1 1 V3 V2 1 1 V4 5 0 0 5 3 0 Vn 0 3 0 0 0 0 0 7 V6 7 V5 4 . Max COMP weight 0 1 1 1 1 5 1 3 0 0 1 7 . . Mult 0 1 5 3 0 7
Vector Comparison Vetor Criptografado FHE Match Engine FHE Base de Dados Resultado Criptografado Descriptografado
Oblivious Image Query Secret Top Secret Desempenho em relação à configurações de segurança de dados da NSA para 'Secret' e 'Top Secret' 16
Referencias ▪ HELIB - Biblioteca de Codigo Aberto para computacao Homomorfica https://github.com/shaih/HElib ▪ Fullu Homomorphic Encryption without Bootstrapping https://eprint.iacr.org/2011/277 ▪ Future Directions in Computing on Encrypted Data https://www.cs.bris.ac.uk/~nigel/ECRYPT-MPC/ ▪ Seminario: Computing on Encrypted Data http://people.csail.mit.edu/vinodv/6892-Fall2013/
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