NDLI: Privacy-preserving content-based recommender system

Please wait, while we are loading the content...

Batch steganography in the real world

Embedding cylinder quality measures into minutia cylinder-code based latent fingerprint matching

Privacy-preserving content-based recommender system

A universal technique to hide traces of histogram-based image manipulations

A methodological framework for investigating age factors on the performance of biometric systems

Steganalysis with mismatched covers: do simple classifiers help?

On using flat bed scanners for the age determination of latent fingerprints: first results for the binary pixel feature

Length-preserving bit-stream-based JPEG encryption

Recognizing pornographic images

Enhancing face recognition at a distance using super resolution

Frame-accurate temporal registration for non-blind video watermarking

A first approach for the contactless acquisition and automated detection of toolmarks on pins of locking cylinders using 3D confocal microscopy

Automatic telephone handset identification by sparse representation of random spectral features

Unexpected artefacts in PRNU-based camera identification: a 'Dresden Image Database' case-study

An evaluation of biometric fingerprint matchers in a forensic context using latent impressions

Performance and code length optimization of joint decoding tardos fingerprinting

First approach for a computer-aided textile fiber type determination based on template matching using a 3D laser scanning microscope

An adaptive system for gait recognition in multi-view environments

Forensic ballistic analysis using a 3D sensor device

Frontal gait recognition combining 2D and 3D data

Appearance-based people recognition by local dissimilarity representations

Experimental results on the feature-level fusion of multiple fingerprint liveness detection algorithms

Privacy preserving ECG quality evaluation

Privacy-preserving content-based recommender system

Content Provider	ACM Digital Library
Author	Lagendijk, Reginald L. Beye, Michael Veugen, Thijs Erkin, Zekeriya
Abstract	By offering personalized content to users, recommender systems have become a vital tool in e-commerce and online media applications. Content-based algorithms recommend items or products to users, that are most similar to those previously purchased or consumed. Unfortunately, collecting and storing ratings, on which content-based methods rely, also poses a serious privacy risk for the customers: ratings may be very personal or revealing, and thus highly privacy sensitive. Service providers could process the collected rating data for other purposes, sell them to third parties or fail to provide adequate physical security. In this paper, we propose technological mechanisms to protect the privacy of individuals in a recommender system. Our proposal is founded on homomorphic encryption, which is used to obscure the private rating information of the customers from the service provider. While the user's privacy is respected by the service provider, by generating recommendations using encrypted customer ratings, the service provider's commercially valuable item-item similarities are protected against curious entities, in turn. Our proposal explores simple and efficient cryptographic techniques to generate private recommendations using a server-client model, which neither relies on (trusted) third parties, nor requires interaction with peer users. The main strength of our contribution lies in providing a highly efficient solution without resorting to unrealistic assumptions.
Starting Page	77
Ending Page	84
Page Count	8
File Format	PDF
ISBN	9781450314176
DOI	10.1145/2361407.2361420
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-09-06
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Privacy Content-based recommender systems Homomorphic encryption
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Privacy-preserving Hybrid Recommender System

Preserving Privacy in Joining Recommender Systems

APPLET: a privacy-preserving framework for location-aware recommender system

Privacy-preserving collaborative filtering based on horizontally partitioned dataset

An efficient privacy-preserving comparison protocol in smart metering systems

Privacy-preserving content-based recommender system.

Toward Better Recommender System by Collaborative Computation with Privacy Preserved

A Multilayer Evolutionary Homomorphic Encryption Approach for Privacy Preserving over Big Data

Pistis: A Privacy-Preserving Content Recommender System for Online Social Communities

Privacy-preserving content-based recommender system

Similar Documents

Privacy-preserving Hybrid Recommender System

Preserving Privacy in Joining Recommender Systems

APPLET: a privacy-preserving framework for location-aware recommender system

Privacy-preserving collaborative filtering based on horizontally partitioned dataset

An efficient privacy-preserving comparison protocol in smart metering systems

Privacy-preserving content-based recommender system.

Toward Better Recommender System by Collaborative Computation with Privacy Preserved

A Multilayer Evolutionary Homomorphic Encryption Approach for Privacy Preserving over Big Data

Pistis: A Privacy-Preserving Content Recommender System for Online Social Communities

Privacy-preserving content-based recommender system