Fine‐Grained Access Through Attribute‐Based Encryption for Fog Computing
Malabika Das · 2024
Attribute-based encryption is a generalization of public key cryptography based on one-to-many encryptions that allow users to encrypt and decrypt data based on user attributes. It is different from identity-based encryption, in which access control is based on the identities of users such as their email addresses, and usernames. In ABE, each user is associated with a set of attributes. These attributes can be various characteristics such as jobs, organizations, age groups, or any other criteria. In decentralized attribute-based encryption, any party can create a public key and private key for different users which reflect their attributes without any collaboration. ABE has been widely used to impose fine-grained access control on encrypted data. Fine-grained access control is a method of controlling who can access certain data. It is essential because it sets access parameters for specific data even when data is stored together, which means it specifies the access rights of individual users. It is often used in cloud computing where a large amount of data is stored together and it gives each piece of data its own specified policy for access. For example, one individual may be given access to edit and make changes to a piece of data while another might be given access only to read the data without making any changes. Fog computing extends the cloud computing paradigm to the edge of the network. The main difference between fog computing and cloud computing is decentralization and flexibility. Fog computing brings computing to the networks’ edge by moving storage and computing systems as near as possible to the applications, components, and devices that need thus reducing processing latency and improving efficiencies. Fog computing implementation involves either writing or porting IoT devices at the network edge for fog nodes using fog tools. Those nodes take in the data from the other edge devices and then direct the data into the optimal location for analysis.