Mapa mental
Wk 12 Cryptography and Network
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Wk 12 Cryptography and Network
Homomorphic and Functional Encryption
- Homomorphic: Computing on Encrypted Data
- FULLY HOMOMORPHIC ENCRYPTION “Anything you can do on plain text data, FHE can do on encrypted data” (fully = any function F) (additive = only additions) (multiplicative = only multiplications) (somewhat/partially = circuits of small depth)
- MULTIPLICATIVE HOMOMORPHISM: El Gamal Encryption
- ADDITIVE HOMOMORPHISM: Goldwasser Micali Encryption
- OTHER SCHEMES: Additively Homomorphic: – Paillier – Damgard-Jurik (both addition of large numbers) • Additions + a single Multiplication: – Boneh-Goh-Nissim (based on gap groups) – Gentry-Halevi-Vaikuntanathan (based on lattices) • HE with Large ciphertext blowup: – Sander-Young-Yung
- LEARNING WITH ERRORS (LWE)
- HOMOMORPHIC OPERATIONS: Homomorphic addition: C1 + C2 Homomorphic multiplication*: C1C2
- APPLICATIONS: ─ Encrypted machine learning (SVMs, decision trees) ─ Encrypted AES and stream cipher computations ─ Encrypted VoIP Interactive Methods: Secure Computation
- Functional Encryption: A method of releasing partial information about the encrypted data to third parties. But a controlled form of partial information.
- FULLY HOMOMORPHIC ENCRYPTION “Anything you can do on plain text data, FHE can do on encrypted data” (fully = any function F) (additive = only additions) (multiplicative = only multiplications) (somewhat/partially = circuits of small depth)
- Homomorphic: Computing on Encrypted Data
Multi Party Computation and Distributing Trust
- Goal: Compute arbitrary functions g(x,y) without revealing x or y to each other
- Applications of MPC: Electronic Election, Auctions, E-commerce applications, Medical Research, Risk Prediction for Global Economy, Data Mining
- Intersection without revealing individual Lists
- Applications of MPC: Electronic Election, Auctions, E-commerce applications, Medical Research, Risk Prediction for Global Economy, Data Mining
- Key Tool: Secret Sharing
- Secret Sharing Using Polynomials
- Distributing Trust and Power: Don’t store keys in 1 place: Don’t do Computation in 1 place Key escrow Cloud Application: remote storage and computation
- DISTRIBUTE INFORMATION AND POWER
- Two Party Computation: Two Party computation: certified mail, PIR, secret exchange
- APPLICATIONS Certified e-mail Secret Exchange Private Information Retrieval
- Goal: Compute arbitrary functions g(x,y) without revealing x or y to each other
Security problems
- Trusting users try to communicate
- Use Cryptography.
- Use Transport Layer Security (TLS)
- Use a Cartificate issues by a Cert Auth.
- Use Transport Layer Security (TLS)
- Use Cryptography.
- One user attacks another
- Untrustworthy users
- Most communication on the Internet is among parties that do not trust each other and with good reason.
- Most communication on the Internet is among parties that do not trust each other and with good reason.
- Untrustworthy users
- The network itself is attacked.
- One part of the network attacks another
- Denial of service attacks.
- Use many computers to send unwanted traffic toward a host or region of the network, thus overwhelming it.
- Trusting users try to communicate
Public-Key Cryptography
- RSA
- El Gamal
- Semantic Security
- Digital Signatures
- Elliptic Curvatures
Información
- Descripción
- Challenges of big data Mapa Mental sobre Wk 12 Cryptography and Network, creado por Victor Vergara el 21/11/2017.
- Creado por
- Victor Vergara
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