Uppsats

Attribute-Based Encryption with dynamic attribute feature applied in Vehicular Ad Hoc Networks

Master-uppsats

KTH/Skolan för elektroteknik och datavetenskap (EECS)

Publicerad: 2022

Språk: Engelska

Sammanfattning

The Vehicular Ad Hoc Network (VANET) is a promising approach for future Intelligent Transportation Systems (ITS) implementation. The data transmission is wireless primarily in the VANET system. The secure data transmission in VANET attracts research attention without any doubt. The Ciphertext-Policy Attribute-Based Encryption (CP-ABE) provides an encrypted access control mechanism for broadcasting messages in VANET. The user’s attributes stand for its current property. However, if we apply vehicle location as the attribute, this attribute has to keep up-to-date with the vehicle’s movement. It is not easy for current CP-ABE algorithms because whenever one attribute changes, the entire private key, which is based on all the attributes, must be changed. In this thesis, we apply fading function to realize the “dynamic attribute” feature in CP-ABE. The dynamic attribute allows the user to update each attribute separately, and fading function gives each attribute a valid period. We introduce the dynamic attribute feature to three different CP-ABE algorithms. Then we design a VANET system that applies the CP-ABE with dynamic attribute feature. We evaluate the processing time of three different CP-ABE algorithms. We apply two different pairing curves for different security requirements. Our results show that the introduction of fading function does not cause significant extra time cost to current CP-ABE algorithms. The fading function causes extra 0.2ms on average for each attribute that participates in encryption and decryption. The sum-up time for encryption and decryption is between 100ms to 200ms when there are ten attributes participating in encryption and decryption.

Information

Författare
Huang, Zijian
Lärosäte / institution
KTH/Skolan för elektroteknik och datavetenskap (EECS)
Publiceringsdatum
2022
Uppsatstyp
Master-uppsats
Språk
Engelska

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