Attribute Based Encryption
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Attribute Based Encryption

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Attribute Based Encryption Attribute Based Encryption Document Transcript

  • Public Key Infrastructure:Encryption & Decryption: 1. Bob Request Alices Public key Public Key Infrastructure from KDC 4. Alice uses her private key to Alice decrypt messages encrypted by Bob. Public Key 2.PKI signs the Public key & send Private Key Bob it to Bob 3. Bob uses her public key to encrypt message for Alice.Disadvantage: 1. To communicate with Alice, Bob, at first, has to communicate with the PKI.
  • Identity Based Encryption (IDE): In IDE, one’s publicly known identity (ex. email address) is being used as his/her public key where ascorresponding private key is generated from the known identity.IDE encryption scheme is a four algorithms/steps scheme where the algorithms are i. Setup Algorithm ii.Key (private key) Generation Algorithm iii. Encryption Algorithm iv. Decryption Algorithm.Setup and Key Generation: Private Key Generator (PKG) 1. Set up Algorithm generate a master key for Alice Master Key 2. Alice show & Prove her 3. Given the identity, Key Generation Algorithm Identity to PKG generate Private key for Alice. Identity Private Key Ex: alice@example.orgEncryption & Decryption: 1. Bob knows & uses Alices Private Key Generator Identity to encrypt the message (PKG) Bob Alice Master Key 2. Alice uses her Private Key to decrypt the message Identity Private Key Ex.alice@example.orgAdvantage: 1. Bob does not need to contact KDC / CA for Alice’s Public Key. He knows Alice’s Identity which he uses to encrypt message for Alice.
  • Fuzzy Identity Based Encryption (Fuzzy-IDE):Fuzzy Identity of a person is a set of descriptive attributes which a predefined error tolerance capability.In Fuzzy-IDE, these attributes are used as one’s known public key.Setup & Key Generation Private Key Generator (PKG) 1. Given a Error Tolerance factor d, set up algorithm generates a Master key for Alice. Master Key 2. Alices Identity w is being decided Fuzzy Identity (w) Private Key 3. Given Identity w, Key Generation Algorithm generates Alices Private Attr1 ... AttrN key.Advantage: With her private key, Alice can decrypt messages encrypted with her own identity (w). She canalso decrypt messages encrypted with other’s identity (w’) if |w ∩w’| >= d.Encryption & Decryption in Fuzzy IDE System 1. Charlie encrypt Message(M) 3. Alice can also decrypt M with her with Bobs Identity w private Key with (|w∩w| >= d) Charlie Bob Alice (Identity w) (Identity w) (Identity w) 2. Bob can decrypt M with his private KeyExample: Person Fuzzy Identity d Comment Alice w={“exam-committee”, “chair”, 2 Alice can decrypt everything that Bob & “system”} Charile can Decrypt. Because |w ∩w’|>=2 and |w ∩w’’|>=2 Bob w’={“exam-committee”, 3 Bob can only decrypt message encrypted “faculty”, “system”, “usa”} with Charlie’s identity as |w’ ∩w’’|>=3 Charlie w’’={“exam-committee”, 4 Charlie cannot decrypt any message that “student”, “system”, “usa”} are encrypted with others identity.
  • Attribute-based Encryption (or Key-policy ABE):Access Tree / Key-policy(Ƭ):Access Policy to be associated with private key where leaf nodes are attributes coming from fuzzyidentity. OR AND Dean 2 out of 3 Computer Science Admission- Computer Science Admission- faculty committee committeeAccount Setup & Key-generation: Private Key Generator (PKG) 1. Setup Algorithm generates Alices Master Key Master Key 4. Given the Key-policy, Key Generation Algorithm generates 2. Alices Identity is being decided Private key for Alice. Fuzzy Identity (w) Private Key 3. Alices Key Policy is being decided from her identity Attr1 ... AttrN Key PolicyEncryption & Decryption: 3. Alice can decrypt M if her key policy is satisfied with γ. ie Ƭ(γ)=1 Bob Alice Charlie (Identity w) (Identity w) (Identity w) 2. Bob can decrypt M if his 1. Charlie encrypt Message(M) key policy is satisfied with γ. with a set of attributes γ (not ie Ƭ(γ)=1 with anyones identity )
  • Example:Assuming, Alice has the following key policy OR AND Dean 2 out of 3 Computer Science Admission- Computer Science Admission- faculty committee committeeAlice can decrypt a file encrypted with the attribute set {“Computer Science”, “Admission committee”}.But she cannot decrypt another ciphertext associated with attributes {“Computer Science”, “program-committee”}.Variations of ABE:Ciphertext-Policy ABE vs. Key-policy ABE:While in original ABE (key-policy ABE) access policy is associated with the private key, in Ciphertext–policy ABE, access policy is associated in the ciphertext. Key-policy ABE Ciphertext-policy ABE pon B E s ts Ciphertext Private key ent com y A en Ciphertext Private key pon ed t-polic ed y ABE com Sel hertex Attribute sel -polic Policy Association Association Policy Attribute e ct e ct Association K ey Cip Association
  • ABE with monotonic Access Structure vs. ABE with non-monotonic Access Structure:Monotonic Access structure uses ‘AND gate’, ‘OR gate’, or ‘k out of N’ threshold gate.Non-Monotonic Access structure uses Monotonic Access structure and additional ‘NOT gate’.Example: ORMonotonicAccess Dean 2 out of 3 ANDstructure Computer Science Admission- Computer Science Admission- faculty committee committeeExample: ORNon-Monotonic AND Dean 2 out of 3Accessstructure Computer Science Admission- Computer Science program- NOT committee committee StudentHierarchical ABE (HABE):In HABE, the attributes are classified into trees according to their relationship defined in the accesscontrol system. Every node in this tree is associated with an attribute, and an ancestral node can deriveits descendant’s key, but the reverse is not allowed. Attribute1 Attribute1 can be used instead of any or all the attributes of this tree Attribute2 can be used instead of attribute4 or attribute 5 or both of them but not vice versa. Attribute2 Attribute3 Attribute4 Attribute5Single Authority ABE vs. Multi-authority ABE: