Theses and Dissertations

Permanent URI for this collectionhttp://ir.daiict.ac.in/handle/123456789/1

Browse

Subject: search.filters.subject.Homomorphic Encryption

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    ItemOpen Access
    Scalable Privacy-Preserving Recommendation System
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2022) Tamboli, Rushabh; Das, Manik Lal
    Recommendation systems, which are used by e-business applications, play an essential role in our daily life. For example, companies like Amazon, Flipkart, YouTube use recommendation systems to generate customized recommendations from the user�s personal information. A personalized recommendation system�s primary purpose is to give users helpful suggestions on different things. The service provider has to access different kinds of user data in order to make suggestions, such as prior product buying history, demographic, and identifying details. Users, on the other hand, are wary about disclosing personal information since it may be readily abused by hostile third parties. To address this challenge, we propose a privacy-preserving recommendation system using homomorphic encryption, which is able to provide recommendations without revealing user rating information. Also, in this system, a service provider can use another service provider�s user rating database to improve the generated recommendation while protecting user�s privacy. The implementation of the proposed system on a publicly available database shows that the system is practical and achieves higher commendation accuracy.
  • Thumbnail Image
    ItemOpen Access
    SHELBRS: Location-Based Recommendation Services using Switchable Homomorphic Encryption
    (2021) Jain, Mishel; Singh, Priyanka
    Location-Based Recommendation Services (LBRS) has seen an unprecedented rise in its usage in recent years. LBRS facilitates a user by recommending services based on his location and past preferences. However, leveraging such services comes at a cost of compromising one’s sensitive information like their shopping preferences, lodging places, food habits, recently visited places, etc. to the thirdparty servers. Losing such information could be crucial and threatens one’s privacy. Nowadays, the privacy-aware society seeks solutions that can provide such services, with minimized risks. Recently, a few privacy-preserving recommendation services have been proposed that exploit the Fully Homomorphic Encryption (FHE) properties to address the issue. Though, it reduced privacy risks but suffered from heavy computational overheads that ruled out their commercial applications. Here, we propose SHELBRS, a lightweight LBRS that is based on Switchable Homomorphic Encryption (SHE), which will benefit the users as well as the service providers. A SHE exploits both the additive as well as the multiplicative homomorphic properties but with comparatively much lesser processing time as it’s FHE counterpart. The performance of our proposed scheme is analyzed with the other state-of-the-art approaches without compromising security
  • Thumbnail Image
    ItemOpen Access
    Private targeted advertising using homomorphic encryption
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2016) Dave, Ainish Juotindra; Das, Manik Lal
    Privacy of the user data in online setup is an important feature. The users of Internetdo not want to share their private information or interests with anybody.The targeted advertising domain clearly tracks the user activity by their browsinghistory or any other technique to do the necessary match-making to target correctadvertisements. The uesrs of the Internet have been using AdBlock or relatedsoftwares to opt out of the tracking/targeting process.In this work, we have applied the private information retrieval phenomenon toaddress the privacy issue in the domain of online targeted advertising. We are nottrying to replace the existing system, but rather suggesting a way around to preserveprivacy of the user and still target them with relevant advertisements. Wehave used a variant of homomorphic encryption to carry out operations, whichallows us to perform operations on encrypted data.A modified encryption scheme is proposed by mitigating the observed attack.Security analysis has been provided to support the security of proposed scheme.A new system of targeted advertising with underlying proposed scheme has beenincluded. We have performed basic experiments using the dummy data of integers,to present the response time of the proposed system. Communication cost,i.e. size of data transfer is very small which makes it feasible for real-world system.Response time achieved is also comparable with real-world scenario whichcan further be improved by setting up the system in distributed manner.