B
Balachander Krishnamurthy
Researcher at AT&T Labs
Publications - 172
Citations - 14399
Balachander Krishnamurthy is an academic researcher from AT&T Labs. The author has contributed to research in topics: The Internet & Server. The author has an hindex of 61, co-authored 171 publications receiving 13973 citations. Previous affiliations of Balachander Krishnamurthy include AT&T & Alcatel-Lucent.
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Proceedings ArticleDOI
A few chirps about twitter
TL;DR: A detailed characterization of Twitter, an application that allows users to send short messages, is presented, which identifies distinct classes of Twitter users and their behaviors, geographic growth patterns and current size of the network.
Proceedings ArticleDOI
Flash crowds and denial of service attacks: characterization and implications for CDNs and web sites
TL;DR: An enhancement to CDNs is proposed that offers better protection to Web sites against flash events and trace-driven simulations are used to study the effect of the enhancement on CDNs and Web sites.
Key Differences between Web1.0 and Web2.0
TL;DR: In this paper, the authors identify the primary differences leading to the properties of interest in 2.0 to be characterized and identify novel challenges due to the different structures of Web2.0 sites, richer methods of user interaction, new technologies and fundamentally different philosophy.
Proceedings ArticleDOI
Sketch-based change detection: methods, evaluation, and applications
TL;DR: This work designs a variant of the sketch data structure, k-ary sketch, which uses a constant, small amount of memory, and has constant per-record update and reconstruction cost, and enables it to summarize traffic at various levels and detects significant changes by looking for flows with large forecast errors.
Proceedings ArticleDOI
Analyzing facebook privacy settings: user expectations vs. reality
TL;DR: A survey is deployed to 200 Facebook users recruited via Amazon Mechanical Turk, finding that 36% of content remains shared with the default privacy settings, and overall, privacy settings match users' expectations only 37% of the time, and when incorrect, almost always expose content to more users than expected.