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Dialectal substitution as an adversarial approach for evaluating Arabic NLP robustness. [PDF]
Sci RepAlshemali B.
europepmc +1 more source
A review of organization-oriented phishing research. [PDF]
PeerJ Comput SciAlthobaiti K, Alsufyani N.
europepmc +1 more source
Semi-supervised novelty detection with one class SVM for SMS spam detection [PDF]
2022 29th International Conference on Systems, Signals and Image Processing (IWSSIP), 2022 The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
Abul Bashar
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Comparison of Term Weighting Techniques in Spam SMS Detection
2020 28th Signal Processing and Communications Applications Conference (SIU), 2020Short message services are one of the most widely used communication services. The increased use of mobile devices and the lowering of SMS costs by operators enable short message services to remain popular. However, this popularity causes tens of users to be exposed to spam SMS every day.
Sercan Demirci, Oguz Emre Kural
exaly +2 more sources
SMS Spam Detection Using Noncontent Features
IEEE Intelligent Systems, 2012Short Message Service text messages are indispensable, but they face a serious problem from spamming. This service-side solution uses graph data mining to distinguish spammers from nonspammers and detect spam without checking a message's contents.
Xu, Qian +4 more
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Detection of SMS spam messages on mobile phones
2012 20th Signal Processing and Communications Applications Conference (SIU), 2012 In this study, a novel “SMS spam message filter” utilizing effective feature selection and pattern classification techniques is proposed. The proposed filter detects and filters out SMS spam messages in a smart manner rather than black/white list approaches that require intervention of phone users.
Alper Kursat Uysal +3 more
openaire +3 more sources
A Lightweight Deep Neural Model for SMS Spam Detection
2020 International Symposium on Networks, Computers and Communications (ISNCC), 2020The short messaging service (SMS) is one of the most popular and also most affordable telecommunication services. The popularity and affordability of SMS, however, have made it an ideal target for spamming. Spam is a major nuisance to mobile subscribers, but can also lead to security breaches or criminal activities.
Feng Wei 0002, Uyen Trang Nguyen
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SMS spam detection for Indian messages
2015 1st International Conference on Next Generation Computing Technologies (NGCT), 2015The growth of the mobile phone users has led to a dramatic increase in SMS spam messages. Though in most parts of the world, mobile messaging channel is currently regarded as “clean” and trusted, on the contrast recent reports clearly indicate that the volume of mobile phone spam is dramatically increasing year by year.
Sakshi Agarwal +2 more
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A comparative study of word embedding techniques for SMS spam detection
2022 14th International Conference on Computational Intelligence and Communication Networks (CICN), 2022E-mail and SMS are the most popular communication tools used by businesses, organizations and educational institutions. Every day, people receive hundreds of messages which could be either spam or ham. Spam is any form of unsolicited, unwanted digital communication, usually sent out in bulk. Spam emails and SMS waste resources by unnecessarily flooding
Joseph, Prashob, Yerima, Suleiman
openaire +2 more sources