@conference {90, title = {Experiences in building a multi-university testbed for research in multimedia communications}, booktitle = {Parallel and Distributed Processing, 2008. IPDPS 2008. IEEE International Symposium on}, year = {2008}, month = {April}, abstract = {

The next generation Internet needs to support multimedia services such as voice/video over IP (VoIP) and IP-based television (IPTV) and media distribution. The goal of the project is to develop a testbed for understanding and analysis of vulnerabilities of IP-based multimedia networks. This is a collaborative project between University of North Texas, Columbia University, Purdue University, and University of California at Davis. This project was awarded in 2006 and in one year, we have developed a multi-university testbed with variety of PBX solutions including Asterisk, a multitude of voice and video IP phones, and multiple universities were connected through a secure VPN and Internet!. As with any endeavor, experiences and we have many unique issues, which sometimes cause setbacks. We have dealt with issues concerning interoperability between phones and servers, network address translation (NAT) connectivity issues, and many other collaboration issues concerning people and technology. An interworking of students from multiple universities, faculty, system administrators and support personnel has brought the testbed resources together for a working environment. In this paper we described our progress and experiences in more detail and how to fulfill our mission statement while supporting the various collaborative efforts involved with this project. In addition, we described the current research activities based on the testbed. Finally we described the next steps in the testbed development.

}, keywords = {Asterisk, Collaboration, Collaborative work, digital television, Internet telephony, IP-based television, IPTV, media distribution, Multimedia communication, Multimedia communications, multiuniversity testbed, Network address translation, network address translation connectivity issues, Network servers, next generation Internet, open systems, PBX solutions, phones-servers interoperability, private telephone exchanges, Testing, TV, video IP phones, video over IP, virtual private network, virtual private networks, voice over IP, Web and internet services}, doi = {10.1109/IPDPS.2008.4536392}, author = {Ram Dantu and Schulzrinne, Henning and Sroufe, Paul} } @conference {56, title = {Quantifying the Presence of Phone Users}, booktitle = {2008 5th IEEE Consumer Communications and Networking Conference}, year = {2008}, month = {Jan}, abstract = {

Presence-enabled telephony services can reduce telephone tag and improve customer satisfaction. In this paper we proposed the Bayesian inference model to calculate the willingness level of the callee to accept calls. Before making a call, the caller may use the willingness calculator to find out whether the callee is available. Based on this level the user can make a decision whether to make a call. For validation of our results, we used actual call logs of 100 users collected at MIT by the Reality Mining Project group for a period of 8 months. We used time of the day, day of the week, talk-time and location for calculating the willingness level Our results show a good agreement between computed willingness level and the number of missed/rejected calls. This service can be included as part of the presence server. When deployed, this service can increase productivity, avoid unwanted calls and reduce the call traffic congestion. This service is beneficial to both subscribers and phone service providers. However, in order to make this service a reality, we need to take into account other factors such social closeness, proximity, multiplexity and reputation of the caller.

}, keywords = {Bayes methods, Bayesian inference model, Bayesian methods, call traffic congestion, Computer science, Context, customer satisfaction, Multimedia communication, Multimedia systems, Network servers, phone service provider, presence-enabled telephony service, Productivity, Roads, telecommunication congestion control, telecommunication traffic, telephony, willingness calculator}, doi = {10.1109/ccnc08.2007.206}, author = {Zhang, Huiqi and Ram Dantu} } @conference {86, title = {Unwanted SMTP Paths and Relays}, booktitle = {2007 2nd International Conference on Communication Systems Software and Middleware}, year = {2007}, month = {Jan}, abstract = {

Based on the social interactions of an email user, incoming email traffic can be divided into different categories such as, telemarketing, Opt-in family members and friends. Due to a lack of knowledge in the different categories, most of the existing spam filters are prone to high false positives and false negatives. Moreover, a majority of the spammers obfuscate their email content inorder to circumvent the content-based spam filters. However, they do not have access to all the fields in the email header. Our classification method is based on the path traversed by email (instead of content analysis) since we believe that spammers cannot forge all the fields in the email header. We based our classification on three kinds of analyses on the header: i) EndToEnd path analysis, which tries to establish the legitimacy of the path taken by an email and classifies them as either spam or non-spam; ii) Relay analysis, which verifies the trustworthiness of the relays participating in the relaying of emails; iii) Emails wantedness analysis, which measure the recipients wantedness of the senders emails. We use the IMAP message status flags such as, message has been read, deleted, answered, flagged, and draft as an implicit feed back from the user in Emails wantedness analysis. Finally we classify the incoming emails as i) socially close (such as, legitimate emails from family, and friends), ii) socially distinct emails from strangers, iii) spam emails (for example, emails from telemarketers, and spammers) and iv) opt-in emails. Based on the relation between spamminess of the path taken by spam emails and the unwantedness values of the spammers, we classify spammers as i) prospective spammers, ii) suspects, iii) recent spammers and iv) serial spammers. Overall, our method resulted in far less false positives compared to current filters like SpamAssassin. We achieved a precision of 98.65\% which is better than the precisions achieved by SPF and DNSBL blacklists.

}, keywords = {Computer science, content-based spam filters, Counterfeiting, Credit cards, email spam filters, emails wantedness analysis, end-to-end path analysis, Filters, IMAP message status flags, information filtering, information filters, Information security, Legislation, Multimedia communication, relay analysis, Relays, SMTP paths analysis, unsolicited e-mail, Unsolicited electronic mail, Web page design}, doi = {10.1109/COMSWA.2007.382440}, author = {Palla, Srikanth and Ram Dantu} }