@conference {101, title = {Current and Future Trends in Social Media}, booktitle = {2011 IEEE Third Int{\textquoteright}l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int{\textquoteright}l Conference on Social Computing}, year = {2011}, abstract = {

Social networking has been the biggest cultural shift since the industrial revolution, attracting millions of people, creating an ever-expanding social web, and revolutionizing the way we communicate. Although many changes have occurred since the fledgling steps of social networking and what it has evolved into today, improvement is a never-ending cycle. Thus, in this paper, additional methods will be explored to advance social networking overall.

}, keywords = {Buildings, Electronic mail, Facebook, Media, Online Social Networks, Privacy, Social Media, Social Network Trends, Twitter}, doi = {10.1109/PASSAT/SocialCom.2011.125}, author = {Baatarjav, Enkh-Amgalan and Ram Dantu} } @conference {75, title = {Unveiling Hidden Patterns to Find Social Relevance}, booktitle = {Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 2011 IEEE Third International Conference on}, year = {2011}, month = {Oct}, abstract = {

Twitter is both a useful social networking device and an incredible marketing tool. However, it is also a venue for dangerous stalkers and a sub-world of internet users that most people would intuitively avoid if seeing them in real life. It would improve Twitter{\textquoteright}s safety to have filters available which would allow users to select an audience for their status updates without being forced into changing their profiles to a private setting. The hypothetical filter, or model, studied in this paper was based on two particular attributes: activity correlations and vocabulary similarities between users and followers. If implemented, this model would restrict the availability of status updates to an automatically generated group of socially relevant followers. The result of this study shows that both of the attributes can be used to define social relevance, however, it was found that activity patterns have better predictive capabilities than correlating vocabulary usage between users and followers.

}, keywords = {activity correlations, Correlation, dangerous stalkers, data privacy, Facebook, hidden patterns, Internet, Internet users, marketing tool, Online Social Networks, Polynomials, Privacy, social networking (online), social networking device, social relevance, Twitter, Twitter safety, Vocabulary, vocabulary similarities}, doi = {10.1109/PASSAT/SocialCom.2011.103}, author = {Baatarjav, Enkh-Amgalan and Ram Dantu} } @conference {57, title = {Are You My Friend?}, booktitle = {Proceedings of the 7th IEEE Conference on Consumer Communications and Networking Conference}, year = {2010}, publisher = {IEEE Press}, organization = {IEEE Press}, address = {Piscataway, NJ, USA}, abstract = {

With Twitters growing popularity, privacy has become a major concern for users wary of sensitive information falling in the wrong hands. A typical Twitter user carries hundreds of followers - people who have subscribed to users twitter feeds. Our goal is to target followers that a Twitter user deems safe. Therefore, selecting followers with a closer relationship could help decrease the risk of sensitive information being sent to unknown people. We propose a privacy management system that helps a Twitter user restrict information to only certain followers based on the strength of their social tie. This system would incorporate two tools: the Exclusivity meter and the Twitter Response Estimator. The Exclusivity Meter employs user{\textquoteright}s activity profile to guess similarities between users. Preliminary results have indicated that similarity in time and level of activity between user and follower does suggest a stronger social tie. The Twitter Response Estimator uses a measure of prestige to gauge the probability of response. When applied to a set of followers, the estimator separates real friends from recreational followers

}, keywords = {online social network, Privacy, Twitter}, isbn = {978-1-4244-5175-3}, url = {http://dl.acm.org/citation.cfm?id=1834217.1834342}, author = {Baatarjav, Enkh-Amgalan and Amin, Aliasgar and Ram Dantu and Gupta, Nikhil Kant} } @conference {53, title = {BBN-based Privacy Management System for Facebook}, booktitle = {Proceedings of the 2009 IEEE International Conference on Intelligence and Security Informatics}, year = {2009}, publisher = {IEEE Press}, organization = {IEEE Press}, address = {Piscataway, NJ, USA}, abstract = {

Online social networking sites (SNSs) has changed our lifestyle and become a main medium of communication among young adults to stay in touch with their friends, to organize events, to make friends, to promote themselves, to date, etc. To create content rich environment, SNSs make their platform available for third-party developers. The developers can build their applications based on users{\textquoteright} social graph containing their personal and social information. Unfortunately, any information users posted on their profile can be harvested and used for unethical purposes due to Facebook{\textquoteright}s lack of application privacy configuration. In this paper we propose a privacy-management system for Facebook applications. The system can take advantage of the correlation between some profile features and network privacy settings, in this way it can automatically configure a users privacy settings. Our preliminary result show promising result.

}, isbn = {978-1-4244-4171-6}, url = {http://dl.acm.org/citation.cfm?id=1706428.1706467}, author = {Baatarjav, Enkh-Amgalan and Ram Dantu and Tang, Yan and Cangussu, Jo{\~a}o} } @inbook {12, title = {Group Recommendation System for Facebook}, booktitle = {On the Move to Meaningful Internet Systems: OTM 2008 Workshops, Monterrey, Mexico, November 9-14, 2008. Proceedings}, year = {2008}, pages = {211{\textendash}219}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, abstract = {

Online social networking has become a part of our everyday lives, and one of the popular online social network (SN) sites on the Internet is Facebook, where users communicate with their friends, join to groups, create groups, play games, and make friends around the world. Also, the vast number of groups are created for different causes and beliefs. However, overwhelming number of groups in one category causes difficulties for users to select a right group to join. To solve this problem, we introduce group recommendation system (GRS) using combination of hierarchical clustering technique and decision tree. We believe that Facebook SN groups can be identified based on their members{\textquoteright} profiles. Number of experiment results showed that GRS can make 73\% accurate recommendation.

}, keywords = {decision tree, recommendation system, Social network}, isbn = {978-3-540-88875-8}, doi = {10.1007/978-3-540-88875-8_41}, url = {http://dx.doi.org/10.1007/978-3-540-88875-8_41}, author = {Baatarjav, Enkh-Amgalan and Phithakkitnukoon, Santi and Ram Dantu}, editor = {Meersman, Robert and Tari, Zahir and Herrero, Pilar} } @conference {30, title = {Privacy Management for Facebook}, booktitle = {4th International Conference on Information Systems Security (ICISS 2008)}, year = {2008}, month = {12/2008}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, address = {Hyderabad, India}, abstract = {

As more people adopt the Internet as a medium of communication, the Internet has developed into a virtual world and this has resulted in many online social networks (SN). MySpace and Facebook, two leading online SN sites, have a combined user base of 170 million as of 2008. SN sites started to offer developers open platforms that provide users{\textquoteright} profile information to the developers. Unfortunately, the applications can also be used to invade privacy and to harvest the users{\textquoteright} profile information without their acknowledgement. To address this vulnerability, we propose a privacy-management system that protects the accessibility of users{\textquoteright} profile. The system uses probabilistic approach based on information revelation of users. Our experimental result shows that the system can achieve high accuracy rate of 75\%.

}, keywords = {Facebook, Privacy, Privacy management, Social network}, doi = {10.1007/978-3-540-89862-7\_23}, author = {Baatarjav, Enkh-Amgalan and Ram Dantu and Phithakkitnukoon, Santi} } @conference {60, title = {Quantifying presence using calling patterns}, booktitle = {Communication Systems Software and Middleware and Workshops, 2008. COMSWARE 2008. 3rd International Conference on}, year = {2008}, month = {Jan}, abstract = {

Presence technology is going to be an integral part of the next generation of communication technology. It can eliminate telephone tag between two parties (caller and callee), which will increase productivity of the parties and reduce unnecessary bandwidth usage of unwanted calls. In this paper, we propose a Willingness Estimator that computes willingness level of a callee for receiving calls from a specified caller. By knowing the willingness value of the callee the caller can decide on proceeding with the call or not. The proposed Willingness Estimator is tested with real mobile user data, and these results are highly accurate. We measure willingness based on calling patterns (arrival time, location, day) of a caller to a callee and this could serve as one of the future presence based services. The results can be used in telecommunication networks such as PSTN, Cellular networks, and Voice over IP networks.

}, keywords = {cellular networks, Communications technology, Computer science, Computer security, Intrusion detection, Laboratories, Mobile handsets, mobile user data, Network servers, next generation communication, Next generation networking, presence technology, Productivity, PSTN, telecommunication networks, telephony, user calling pattern, voice over IP networks, willingness estimator}, doi = {10.1109/COMSWA.2008.4554403}, author = {Husna, Husain and Phithakkitnukoon, Santi and Baatarjav, Enkh-Amgalan and Ram Dantu} } @article {43, title = {VoIP Security: Attacks and Solutions}, journal = {Information Security Journal: A Global Perspective}, volume = {17}, year = {2008}, pages = {114{\textendash}123}, abstract = {

Voice over IP (VoIP) technology is being extensively and rapidly deployed. Flexibility and cost efficiency are the key factors luring enterprises to transition to VoIP. Some security problems may surface with the widespread deployment of VoIP. This article presents an overview of VoIP systems and its security issues. First, we briefly describe basic VoIP architecture and its fundamental differences compared to PSTN. Next, basic VoIP protocols used for signaling and media transport, as well as defense mechanisms are described. Finally, current and potential VoIP attacks along with the approaches that have been adopted to counter the attacks are discussed.

}, keywords = {attack, defense mechanism, PSTN, Security, VoIP}, issn = {1939-3555}, doi = {10.1080/19393550802308618}, url = {http://dx.doi.org/10.1080/19393550802308618}, author = {Phithakkitnukoon, Santi and Ram Dantu and Baatarjav, Enkh-Amgalan} }