Behavior Decomposition: Aspect-Level Browser Extension Clustering and Its Security Implications

2013 ◽  
pp. 244-264 ◽  
Author(s):  
Bin Zhao ◽  
Peng Liu
Keyword(s):  
Browser Extension

scholarly journals Associative Blockchain for Decentralized PKI Transparency

Cryptography ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 14
Author(s):  
Xavier Boyen ◽  
Udyani Herath ◽  
Matthew McKague ◽  
Douglas Stebila
Keyword(s):  
Formal Analysis ◽  
Fraud Detection ◽  
Public Key Infrastructure ◽  
Public Key ◽  
The Internet ◽  
Security Model ◽  
User Adoption ◽  
Browser Extension ◽  
History Of ◽  
Client Side

The conventional public key infrastructure (PKI) model, which powers most of the Internet, suffers from an excess of trust into certificate authorities (CAs), compounded by a lack of transparency which makes it vulnerable to hard-to-detect targeted stealth impersonation attacks. Existing approaches to make certificate issuance more transparent, including ones based on blockchains, are still somewhat centralized. We present decentralized PKI transparency (DPKIT): a decentralized client-based approach to enforcing transparency in certificate issuance and revocation while eliminating single points of failure. DPKIT efficiently leverages an existing blockchain to realize an append-only, distributed associative array, which allows anyone (or their browser) to audit and update the history of all publicly issued certificates and revocations for any domain. Our technical contributions include definitions for append-only associative ledgers, a security model for certificate transparency, and a formal analysis of our DPKIT construction with respect to the same. Intended as a client-side browser extension, DPKIT will be effective at fraud detection and prosecution, even under fledgling user adoption, and with better coverage and privacy than federated observatories, such as Google’s or the Electronic Frontier Foundation’s.

Semi-Automatic Online Tagging with K-Medoid Clustering

2014 ◽  
Vol 24 (08) ◽  
pp. 1115-1130 ◽  
Author(s):  
He Hu ◽  
Xiaoyong Du
Keyword(s):  
Clustering Algorithm ◽  
Prototype System ◽  
Web Pages ◽  
Web Page ◽  
Web Browser ◽  
User Input ◽  
Browser Extension ◽  
Annotation Process ◽  
Efficiency And Effectiveness ◽  
Automatic Mechanism

Online tagging is crucial for the acquisition and organization of web knowledge. We present TYG (Tag-as-You-Go) in this paper, a web browser extension for online tagging of personal knowledge on standard web pages. We investigate an approach to combine a K-Medoid-style clustering algorithm with the user input to achieve semi-automatic web page annotation. The annotation process supports user-defined tagging schema and comprises an automatic mechanism that is built upon clustering techniques, which can automatically group similar HTML DOM nodes into clusters corresponding to the user specification. TYG is a prototype system illustrating the proposed approach. Experiments with TYG show that our approach can achieve both efficiency and effectiveness in real world annotation scenarios.

scholarly journals Secureweb: Protecting sensitive information through the web browser extension with a security token

2018 ◽  
Vol 23 (5) ◽  
pp. 526-538 ◽  
Author(s):  
Shuang Liang ◽  
Yue Zhang ◽  
Bo Li ◽  
Xiaojie Guo ◽  
Chunfu Jia ◽  
...  
Keyword(s):  
Sensitive Information ◽  
Web Browser ◽  
Browser Extension ◽  
The Web

scholarly journals The binge-watcher’s journey: Investigating motivations, contexts, and affective states surrounding Netflix viewing

2019 ◽  
pp. 135485651989085 ◽  
Author(s):  
Deborah Castro ◽  
Jacob M Rigby ◽  
Diogo Cabral ◽  
Valentina Nisi
Keyword(s):  
Exploratory Study ◽  
Objective Data ◽  
Affective States ◽  
Individual Activity ◽  
Subjective Data ◽  
Mixed Methods Approach ◽  
Browser Extension ◽  
Novel Approach ◽  
Before And After ◽  
Viewing Sessions

The growth of Internet-distributed TV services has transformed video consumption, enhancing the level of control that viewers have over what they watch. Along with the release of entire seasons of programming at once, this has led to the phenomenon of ‘binge-watching’, in which several episodes of a program are viewed in one sitting. This article presents the results of a novel exploratory study focused on 40 Netflix viewing sessions from 11 millennials in their homes. Methodologically, we employed a novel mixed-methods approach that combines objective data (collected through a browser extension) and subjective data (collected via questionnaires completed before and after viewing). This novel approach allowed us to describe the binge-watcher’s experience in a holistic fashion. Results suggest that binge-watching is an individual activity mainly performed at the end of the day to relax, for boredom relief purposes, or for escapism. Furthermore, a binge-watching session lasts for an average of 2 h and 10 min, and variations on binge-watchers’ affective states were identified after Netflix exposure. Participants’ levels of valence (unhappy–happy) significantly decreased after binge-watching; their positive affect values increased primarily after watching sci-fi, while their negative affect values decreased after watching comedy and slightly increased after watching drama. However, the levels of arousal (relaxed–stimulated) remained the same. This study extends our current understanding of binge-watching in terms of viewer motivations, how it affects their viewing experiences, and participants’ subjective affective states. The investigation contributes, thus, to a relatively new domain of research concerned with the understanding of binge-watching behavior of serialized TV fiction.

Sign in / Sign up

Export Citation Format

Share Document