Computer Science
Purdue University
2601 Soldiers Home Road, Apt 42,
West Lafayette, Indiana,
USA-47906
Phone: +1-765-491-9719
Email Addresses:
hitesh@purdue.edu
hitesh.iitk@gmail.com
Background
I'm a second year graduate student at Computer Science, Purdue University. I completed my undergrad from Indian Institute of Technology, Kanpur.
Publications
-
A Dynamic Reputation Service for Spotting Spammers
Anirudh Ramachandran, Hitesh Khandelwal, Shuang Hao, Nick Feamster, Santosh Vempala
Draft in preparation
+Abstract
This paper presents the design, implementation, evaluation, and initial deployment of SpamSpotter, the first open, large-scale, real-time reputation system for filtering spam. Existing blacklists (e.g., SpamHaus) have trouble keeping pace with spammers’ increasing ability to send spam from “fresh” IP addresses, and filters based purely on content are easily evadable. In contrast, SpamSpotter dynamically classifies email senders in real time based on their global sending behavior, rather than based on ephemeral features such as an IP address or the content of the message.
In implementing SpamSpotter, we address significant challenges involving both dynamism (i.e., determining when to “retrain” our dynamic classification algorithms) and scale (i.e., maintaining fast, accurate performance in the face of tremendous email message volume). We have evaluated the performance and accuracy of SpamSpotter using traces from a large email-hosting provider and a spam appliance vendor that receives 300 million messages a day. Our evaluation shows that SpamSpotter is scalable, fast, and accurate. SpamSpotter is also operational today: it will currently answer queries from existing spam filtering software (e.g., SpamAssassin) with only minor configuration changes. -
M-Torrent-A Multicast Enabled BitTorrent Protocol
Piyush Agrawal, Hitesh Khandelwal, R K Ghosh
IEEE COMSNETS 2010
+Abstract
In this paper we address the problem of repetitive data transmission in BitTorrent. and propose a new protocol called MTorrent to restrict the same by exploiting IP Multicast functionality wherever available. A prototype system of our protocol have been implemented, and large scale measurement studies were conducted over Emulab network consisting of 44 nodes, spread over 9 LANs and 36 end clients. MTorrent leads to 44% reduction in download time, 65% reduction in traffic load on the Internet links and 40% reduction in download of redundant packets when compared to the BitTorrent. MTorrent is interoperable with BitTorrent, and requires only a few changes at the client end.