Bloom Cookies: Web Search Personalization without User Tracking

Mor, Nitesh; Riva, Oriana; Nath, Suman; Kubiatowicz, John

doi:10.14722/ndss.2015.23108

Cited by 17 publications

(7 citation statements)

References 41 publications

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“…Similarly, SplixX uses differentially private queries over distributed user data. Furthermore, another noisy technique 'Bloom cookies' [66] presents a framework for privacy preserving personalization of web searches of locally derived profile. In our previous works, we propose 'ProfileGuard' [5], [15] that is an app-based profile obfuscation mechanism and a privacy-preserving mobile advertising system based on various implementation of Private Information Retrieval (PIR) [2].…”

Section: Privacy and Mobile Analytics Servicesmentioning

confidence: 99%

Privacy-preserving targeted mobile advertising:A Blockchain-based framework for mobile ads

Ullah¹

2020

Preprint

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The targeted advertising is based on preference profiles inferred via relationships among individuals, their monitored responses to previous advertising and temporal activity over the Internet, which has raised critical privacy concerns. In this paper, we present a novel proposal for a Blockchain-based advertising platform that provides: a system for privacy preserving user profiling, privately requesting ads from the advertising system, the billing mechanisms for presented and clicked ads, the advertising system that uploads ads to the cloud according to profiling interests, various types of transactions to enable advertising operations in Blockchain-based network, and the method that allows a cloud system to privately compute the access policies for various resources (such as ads, mobile user profiles). Our main goal is to design a decentralized framework for targeted ads, which enables private delivery of ads to users whose behavioral profiles accurately match the presented ads, defined by the ad system. We implement a POC of our proposed framework i.e. a Bespoke Miner and experimentally evaluate various components of Blockchain-based in-app advertising system, implementing various critical components; such as, evaluating user profiles, implementing access policies, encryption and decryption of users' profiles. We observe that the processing delay for traversing policies of various tree sizes, the encryption/decryption time of user profiling with various key-sizes and user profiles of various interests evaluates to an acceptable amount of processing time as that of the currently implemented ad systems.<br><br>

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Section: Privacy and Mobile Analytics Servicesmentioning

confidence: 99%

Privacy-preserving targeted mobile advertising:A Blockchain-based framework for mobile ads

Ullah¹

2020

Preprint

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“…A novel noisy technique for privacy preserving personalisation of web searches was also recently proposed [166]. In this work, the authors use 'Bloom' cookies that comprise a noisy version of the locally derived profile.…”

Section: Randomisationmentioning

confidence: 99%

Privacy in targeted advertising: A survey

Ullah¹,

Boreli²,

Kanhere³

2020

Preprint

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Targeted advertising has transformed the marketing trend for any business by creating new opportunities for advertisers to reach prospective customers by delivering them personalised ads using an infrastructure of a variety of intermediary entities and technologies. The advertising and analytics companies collect, aggregate, process and trade a rich amount of user's personal data, which has prompted serious privacy concerns among individuals and organisations. This article presents a detailed survey of privacy risks including the information flow between advertising platform and ad/analytics networks, the profiling process, the advertising sources and criteria, the measurement analysis of targeted advertising based on user's interests and profiling context and ads delivery process in both in-app and in-browser targeted ads. We provide detailed discussion of challenges in preserving user privacy that includes privacy threats posed by the advertising and analytics companies, how private information is extracted and exchanged among various advertising entities, privacy threats from third-party tracking, re-identification of private information and associated privacy risks, in addition to, overview data and tracking sharing technologies. Following, we present various techniques for preserving user privacy and a comprehensive analysis of various proposals founded on those techniques and compare them based on the underlying architectures, the privacy mechanisms and the deployment scenarios. Finally we discuss some potential research challenges and open research issues.<br>

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“…Ada banyak penelitian yang berkaitan dengan pendeteksian lalu lintas HTTP dan penggunaan aplikasi yang membaca lalu lintas permintaan dari server. Hal yang paling sederhana terletak pada protokol jaringan HTTP yang banyak di akses ke aplikasi berbasis web sudah semakin meluas (Mor, Riva, Nath, & Kubiatowicz, 2015). Hal ini disebabkan kinerja protokol jaringan HTTP lebih ringan dibandingkan protokol jaringan HTTPS menggunakan protokol SSL yang memiliki tiga tingkat pengamanan data.…”

Section: Pendahuluanunclassified

Evaluasi Teknik Penyadapan Lalu Lintas Data Dengan Session Hijacking Pada Protokol HTTP

Munadi

Purnandi

Arif

2019

JIM

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Hyper Text Transfer Protocol (HTTP) merupakan protokol jaringan aplikasi yang digunakan pada aplikasi berbasis web. Kerentanan protokol ini yang mengekspoitasi web server secara tidak aman, memberikan peluang peretas untuk melakukan serangan, salah satunya dengan serangan session hijacking. Oleh karena itu, dalam penelitian ini dilakukan survei kerentanan terhadap session hijacking dengan menguji beberapa web. Untuk mendapatkan data, maka digunakan Wi-fi UC browser untuk membaca lalulintas data protokol jaringan HTTP yang sedang dibuka oleh pengguna. Dalam pengujian diperoleh cookies yang digunakan oleh pengguna. Informasi session id yang terekam dalam penyadapan, dapat disalahgunakan oleh attacker untuk melakukan tindakan illegal. Hasil penelitian menunjukkan kelemahan pada protokol jaringan HTTP yang rentan terhadap penyadapan lalulintas data dengan cara penyerangan session hijacking. Untuk mengatasi kelemahan ini, dapat digunakan metode pengacakan seperti algoritme Fisher-Yates shuffle atau pun algoritme Linear Congruent Method yang dapat meningkatkan keamanan.

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Bloom Cookies: Web Search Personalization without User Tracking

Cited by 17 publications

References 41 publications

Privacy-preserving targeted mobile advertising:A Blockchain-based framework for mobile ads

Privacy-preserving targeted mobile advertising:A Blockchain-based framework for mobile ads

Privacy in targeted advertising: A survey

Evaluasi Teknik Penyadapan Lalu Lintas Data Dengan Session Hijacking Pada Protokol HTTP

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