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Graph-based learning model for detection of SMS spam on smart phones.

, and . IWCMC, page 1046-1051. IEEE, (2012)

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Stranger danger: exploring the ecosystem of ad-based URL shortening services., , , , , , , , and . WWW, page 51-62. ACM, (2014)Application of evolutionary algorithms in detecting SMS spam at access layer., , and . GECCO, page 1787-1794. ACM, (2011)FIRMA: Malware Clustering and Network Signature Generation with Mixed Network Behaviors., and . RAID, volume 8145 of Lecture Notes in Computer Science, page 144-163. Springer, (2013)xMiner: Nip the Zero Day Exploits in the Bud., and . NCA, page 99-106. IEEE Computer Society, (2011)Graph-based learning model for detection of SMS spam on smart phones., and . IWCMC, page 1046-1051. IEEE, (2012)A Framework for Detecting Malformed SMS Attack., , , and . STA, volume 186 of Communications in Computer and Information Science, page 11-20. Springer, (2011)Embedding High Capacity Covert Channels in Short Message Service (SMS)., , , and . STA, volume 186 of Communications in Computer and Information Science, page 1-10. Springer, (2011)A Data Mining Framework for Securing 3G Core Network from GTP Fuzzing Attacks., , and . ICISS, volume 7093 of Lecture Notes in Computer Science, page 280-293. Springer, (2011)Driving in the Cloud: An Analysis of Drive-by Download Operations and Abuse Reporting., , and . DIMVA, volume 7967 of Lecture Notes in Computer Science, page 1-20. Springer, (2013)Securing IP-Multimedia Subsystem (IMS) against Anomalous Message Exploits by Using Machine Learning Algorithms., , , and . ITNG, page 559-563. IEEE Computer Society, (2011)