Details
| Original language | English |
|---|---|
| Title of host publication | CIKM'05 |
| Subtitle of host publication | Proceedings of the 14th ACM International Conference on Information and Knowledge Management |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 373-380 |
| Number of pages | 8 |
| ISBN (print) | 1595931406, 9781595931405 |
| Publication status | Published - 31 Oct 2005 |
| Event | CIKM'05 - 14th ACM International Conference on Information and Knowledge Management - Bremen, Germany Duration: 31 Oct 2005 → 5 Nov 2005 |
Publication series
| Name | International Conference on Information and Knowledge Management, Proceedings |
|---|
Abstract
Can we use social networks to combat spam? This paper investigates the feasibility of MailRank, a new email ranking and classification scheme exploiting the social communication network created via email interactions. The underlying email network data is collected from the email contacts of all MailRank users and updated automatically based on their email activities to achieve an easy maintenance. MailRank is used to rate the sender address of arriving emails such that emails from trustworthy senders can be ranked and classified as spam or non-spam. The paper presents two variants: Basic MailRank computes a global reputation score for each email address, whereas in Personalized MailRank the score of each email address is different for each MailRank user. The evaluation shows that MailRank is highly resistant against spammer attacks, which obviously have to be considered right from the beginning in such an application scenario. MailRank also performs well even for rather sparse networks, i.e., where only a small set of peers actually take part in the ranking of email addresses.
Keywords
- Email Reputation, MailRank, Personalization, SPAM
ASJC Scopus subject areas
- Decision Sciences(all)
- General Decision Sciences
- Business, Management and Accounting(all)
- General Business,Management and Accounting
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CIKM'05: Proceedings of the 14th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery (ACM), 2005. p. 373-380 (International Conference on Information and Knowledge Management, Proceedings).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - MailRank
T2 - CIKM'05 - 14th ACM International Conference on Information and Knowledge Management
AU - Chirita, Paul Alexandru
AU - Diederich, Jörg
AU - Nejdl, Wolfgang
PY - 2005/10/31
Y1 - 2005/10/31
N2 - Can we use social networks to combat spam? This paper investigates the feasibility of MailRank, a new email ranking and classification scheme exploiting the social communication network created via email interactions. The underlying email network data is collected from the email contacts of all MailRank users and updated automatically based on their email activities to achieve an easy maintenance. MailRank is used to rate the sender address of arriving emails such that emails from trustworthy senders can be ranked and classified as spam or non-spam. The paper presents two variants: Basic MailRank computes a global reputation score for each email address, whereas in Personalized MailRank the score of each email address is different for each MailRank user. The evaluation shows that MailRank is highly resistant against spammer attacks, which obviously have to be considered right from the beginning in such an application scenario. MailRank also performs well even for rather sparse networks, i.e., where only a small set of peers actually take part in the ranking of email addresses.
AB - Can we use social networks to combat spam? This paper investigates the feasibility of MailRank, a new email ranking and classification scheme exploiting the social communication network created via email interactions. The underlying email network data is collected from the email contacts of all MailRank users and updated automatically based on their email activities to achieve an easy maintenance. MailRank is used to rate the sender address of arriving emails such that emails from trustworthy senders can be ranked and classified as spam or non-spam. The paper presents two variants: Basic MailRank computes a global reputation score for each email address, whereas in Personalized MailRank the score of each email address is different for each MailRank user. The evaluation shows that MailRank is highly resistant against spammer attacks, which obviously have to be considered right from the beginning in such an application scenario. MailRank also performs well even for rather sparse networks, i.e., where only a small set of peers actually take part in the ranking of email addresses.
KW - Email Reputation
KW - MailRank
KW - Personalization
KW - SPAM
UR - http://www.scopus.com/inward/record.url?scp=33745785709&partnerID=8YFLogxK
U2 - 10.1145/1099554.1099671
DO - 10.1145/1099554.1099671
M3 - Conference contribution
AN - SCOPUS:33745785709
SN - 1595931406
SN - 9781595931405
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 373
EP - 380
BT - CIKM'05
PB - Association for Computing Machinery (ACM)
Y2 - 31 October 2005 through 5 November 2005
ER -