@conference {107, title = {An opportunistic encryption extension for the DNS protocol}, booktitle = {Intelligence and Security Informatics (ISI), 2015 IEEE International Conference on}, year = {2015}, month = {May}, abstract = {

Confidentiality for DNS transactions has been a low-priority concern in DNS security for a long time due to performance requirements for the functionality of DNS and the fact that data in the DNS is considered public. However, the information carried in DNS transactions, if collected and analyzed, can pose real threats to personal privacy. This makes DNS a good target for passive eavesdropping to collect data for many purposes some of which may be malicious. The protocol described in this document is intended to facilitate an opportunistic negotiation of encryption in the DNS to provide confidentiality for the last mile of DNS resolution. It defines procedures to discover encryption-aware servers and how to establish a relationship with them with minimum overhead.

}, keywords = {computer network security, cryptographic protocols, DNS protocol, DNS security, DNS transactions, encryption, Internet, opportunistic encryption extension, passive eavesdropping, performance requirements, personal privacy, pose real threats, Privacy, Protocols, Public key, servers}, doi = {10.1109/ISI.2015.7165976}, author = {Bucuti, Theogene and Ram Dantu} } @conference {232, title = {Random anonymization of mobile sensor data: Modified Android framework}, booktitle = {Intelligence and Security Informatics (ISI), 2015 IEEE International Conference on}, year = {2015}, month = {May}, abstract = {

With the increasing ability to accurately classify activities of mobile users from what was once viewed as innocuous mobile sensor data, the risk of users compromising their privacy has risen exponentially. Currently, mobile owners cannot control how various applications handle the privacy of their sensor data, or even determine if a service provider is adversarial or trustworthy. To address these privacy concerns, third party applications have been designed to allow mobile users to have control over the data that is sent to service providers. However, these applications require users to set flags and parameters that place restrictions on the anonymized or real sensor data that is sent to the requestor. Therefore, in this paper, we introduce a new framework, RANDSOM, that moves the decision-making from the application level to the operating system level.

}, keywords = {Accelerometers, Android, anonymized, application level, Data models, data privacy, Hidden Markov models, Mobile communication, mobile computing, mobile sensor data, mobile users, modified Android framework, operating system level, pervasive, Privacy, privacy concerns, provider, random anonymization, RANDSOM, RANDSOM framework, sensor data privacy, service providers, smart phone, smart phones, telecommunication security, third party applications}, doi = {10.1109/ISI.2015.7165968}, author = {Claiborne, Cynthia and Ncube, Cathy and Ram Dantu} } @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} } @article {51, title = {A Testbed for Large Mobile Social Computing Experiments}, journal = {Int. J. Sen. Netw.}, volume = {8}, year = {2010}, pages = {89{\textendash}97}, abstract = {

We present a testbed for mobile social computing that can be used to perform research in security, privacy and context-awareness policies and mechanisms appropriate for a wide range of applications. We compare several mobile platforms and present the rational for our design choices and reasons we chose Android as the primary smartphone for the testbed. We also discuss some of the experiments that can be conducted using this testbed.

}, keywords = {context awareness, mobile communications, mobile computing, mobile devices, Privacy, Security, sensor information, sensors, smartphones, social computing, testbed, ubiquitous devices}, issn = {1748-1279}, doi = {10.1504/IJSNET.2010.034618}, url = {http://dx.doi.org/10.1504/IJSNET.2010.034618}, author = {Alazzawe, Ahmed and Alazzawe, Anis and Wijesekera, Duminda and Ram Dantu} } @conference {55, title = {A testbed for mobile social computing}, booktitle = {Testbeds and Research Infrastructures for the Development of Networks Communities and Workshops, 2009. TridentCom 2009. 5th International Conference on}, year = {2009}, month = {April}, abstract = {

We present a testbed for mobile social computing that can be used to perform research in security, privacy, and context-awareness policies and mechanisms appropriate for a wide range of applications. We compare several mobile platforms and present the rational for our design choices and reasons we chose Android as the primary smartphone for this testbed. We also discuss some of the possible experiments that can be conducted using the testbed.

}, keywords = {Acoustic sensors, Computer science, Computer security, context-awareness policy, data privacy, Feedback, Global Positioning System, mobile computing, mobile social computing, Performance evaluation, Privacy, privacy policy, security of data, security policy, Social network services, Testing}, doi = {10.1109/TRIDENTCOM.2009.4976250}, author = {Alazzawe, Ahmed and Alazzawe, Anis and Wijesekera, Duminda and Ram Dantu} } @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} }