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Twitter Content-Based Spam Filtering [chapter]

Igor Santos, Igor Miñambres-Marcos, Carlos Laorden, Patxi Galán-García, Aitor Santamaría-Ibirika, Pablo García Bringas
2014 Advances in Intelligent Systems and Computing  
In this paper, we propose a content-based approach to filter spam tweets. We have used the text in the tweet and machine learning and compression algorithms to filter those undesired tweets.  ...  In this context, spam in Twitter has emerged in the last years, becoming an important problem for the users.  ...  The training documents are previously labelled in n different classes, dividing our training documents D in n different document sets D = (D 1 , D 2 , ..., D n−1 , D n ) depending on their labelled class  ... 
doi:10.1007/978-3-319-01854-6_46 fatcat:z63s7qxkqncgpdzfv6rbcjq4hu

Machine Learning Techniques for Spam Detection in Email and IoT Platforms: Analysis and Research Challenges

Naeem Ahmed, Rashid Amin, Hamza Aldabbas, Deepika Koundal, Bader Alouffi, Tariq Shah
2022 Security and Communication Networks  
Among all the techniques developed for detecting and preventing spam, filtering email is one of the most essential and prominent approaches.  ...  This paper surveys the machine learning techniques used for spam filtering techniques used in email and IoT platforms by classifying them into suitable categories.  ...  One of the well-known and conventional machine learning methods for spam detection is the case-based or sample-based spam filtering system [32] .  ... 
doi:10.1155/2022/1862888 doaj:27c7fab9297747cba125d6dff8deb631 fatcat:fsasq7gapbhd7lv66wwgxveyyq

Efficient E-Mail Spam Detection Strategy Using Genetic Decision Tree Processing with NLP Features

Safaa S. I. Ismail, Romany F. Mansour, Rasha M. Abd El-Aziz, Ahmed I. Taloba, Anastasios D. Doulamis
2022 Computational Intelligence and Neuroscience  
A voice-mail-enabled system allows users to communicate with one another based on speech input which the sender can communicate to the receiver via voice conversations, which is used to deliver voice information  ...  another or globally share some important official documents and reports.  ...  Related Works A method for spam e-mail message filtering based on hybrid schemes is proposed in [1] .  ... 
doi:10.1155/2022/7710005 pmid:35371228 pmcid:PMC8970896 fatcat:oxfhe3dawzclbea3c6xkodv5km

Machine Learning based Spam E-Mail Detection

Priti Sharma, Uma Bhardwaj
2018 International Journal of Intelligent Engineering and Systems  
This paper aims to propose a machine learning based hybrid bagging approach by implementing the two machine learning algorithms: Naïve Bayes and J48 (decision tree) for the spam email detection.  ...  Spam email is one of the biggest issues in the world of internet. Spam emails not only influence the organisations financially but also exasperate the individual email user.  ...  of particular algorithm for the spam email filtering system.  ... 
doi:10.22266/ijies2018.0630.01 fatcat:of7y7mmhyjbdvinsmyu5k4gepy

Spam Detection Using Machine Learning

2020 Computer Engineering and Intelligent Systems  
Regular rule-based classifiers have been overwhelmed and less effective by the geometric growth in spam messages, hence the need to develop a more reliable and robust model.  ...  However, for this project, the Bayesian was employed using Python programming language to develop a classification model.  ...  For this project two set of data was used, one for machine learning and the other for deep learning. Naïve Bayes Classifier This is a method of classification based on Bayes theorem.  ... 
doi:10.7176/ceis/11-3-04 fatcat:nfyzhh23ubfhzoewyuvqwh6ka4

Security Evaluation of Pattern Classifiers under Attack

Battista Biggio, Giorgio Fumera, Fabio Roli
2014 IEEE Transactions on Knowledge and Data Engineering  
Pattern classification systems are commonly used in adversarial applications, like biometric authentication, network intrusion detection, and spam filtering, in which data can be purposely manipulated  ...  In this paper, we address one of the main open issues: evaluating at design phase the security of pattern classifiers, namely, the performance degradation under potential attacks they may incur during  ...  As the name implies, rule based methods classify documents based on whether or not they meet a particular set of criteria.  ... 
doi:10.1109/tkde.2013.57 fatcat:7euny7uekvapvbxtejmpip3hnq

Utilizing Multi-Field Text Features for Efficient Email Spam Filtering

Wuying Liu, Ting Wang
2012 International Journal of Computational Intelligence Systems  
index for labeled emails storing.  ...  The experimental results in the TREC spam track show that the proposed approach can complete the filtering task in low space cost and high speed, whose overall performance 1-ROCA exceeds the best one among  ...  Acknowledgements The authors thank the anonymous reviewers for helping to greatly improve the paper. This research is supported by the National Natural Science Foundation of China  ... 
doi:10.1080/18756891.2012.696915 fatcat:cfuwvpqlxvawbj7jm3qtpkwomy

Intelligent Security Schema for SMS Spam Message Based on Machine Learning Algorithms

Ali Alshahrani
2021 International Journal of Interactive Mobile Technologies  
The proposed system is heavily based on machine learning to explore various types of messages.  ...  To resolve this issue, a new intelligent security system is proposed to reduce the number of spam messages. It can detect novel spam messages that have a direct and negative impact on networks.  ...  Acknowledgments The author would like to thank Arab Open University, Saudi Arabia for supporting this study.  ... 
doi:10.3991/ijim.v15i16.24197 fatcat:mdiwrtrpfzd4rgnyhqntm2662i

A Comparative Analysis of Machine Learning Techniques for Spam Detection

Syed Ishfaq Manzoor, Lovely Professional University Punjab, India
2019 International Journal of Advanced Trends in Computer Science and Engineering  
The current study evaluates the effectiveness and efficiency of various machine learning techniques which include K-NN, Decision tree, random forest, Naive Bayes and SVM for spam detection.  ...  Some deep learning techniques for classification of spams is also suggested for better performance.  ...  It is a sub domain of Artificial Intelligence based on fact that machines can learn from data, machines can identify patterns, extract key features for decision making with a minimal human intervention  ... 
doi:10.30534/ijatcse/2019/73832019 fatcat:c7t3houioze35bgjuszaw7tpya

Spam detection by using machine learning based binary classifier

Mohd Fadzil Abdul Kadir, Ahmad Faisal Amri Abidin, Mohamad Afendee Mohamed, Nazirah Abdul Hamid
2022 Indonesian Journal of Electrical Engineering and Computer Science  
This research shows the machine learning algorithm in the Azure-based platform predicts the score more accurately compared to the machine learning algorithm in visual studio, hybrid analysis and JoeSandbox  ...  This project will discuss how machine learning can help in spam detection.  ...  ACKNOWLEDGEMENTS This work was supported by the Center for Research Excellence and Incubation Management, Universiti Sultan Zainal Abidin.  ... 
doi:10.11591/ijeecs.v26.i1.pp310-317 fatcat:bepk4q5jhzcyrk3yvyd7znnvcq

A Multiobjective Evolutionary Algorithm for spam e-mail filtering

A.G. Lopez-Herrera, E. Herrera-Viedma, F. Herrera
2008 2008 3rd International Conference on Intelligent System and Knowledge Engineering  
In this paper a well known Multiobjective Evolutionary Algorithm, NSGA-II, is first time used for spam e-mail filtering.  ...  Unsolicited Commercial Email, also known as spam, has been a major problem on the Internet.  ...  In recent years, personalized anti-spam filters of email client applications based on content filters have now become the standard for spam filters [7, 8] .  ... 
doi:10.1109/iske.2008.4730957 fatcat:5cm2qojj45d5djn5u2gdwazsvy

A systematic literature review on spam content detection and classification

Sanaa Kaddoura, Ganesh Chandrasekaran, Daniela Elena Popescu, Jude Hemanth Duraisamy
2022 PeerJ Computer Science  
The various techniques involved in spam detection and classification involving Machine Learning, Deep Learning, and text-based approaches are discussed in this paper.  ...  This paper presents a detailed survey on the latest developments in spam text detection and classification in social media.  ...  The importance of machine learning techniques for spam text classification is studied by Al-Zoubi et al. ( 2018 Based on the prior work on spam classification with Machine Learning approaches presented  ... 
doi:10.7717/peerj-cs.830 pmid:35174265 pmcid:PMC8802784 fatcat:qv74jetor5eddncvkfpfxshln4

Feature Extraction aligned Email Classification based on Imperative Sentence Selection through Deep Learning

Nashit Ali, Department of Computer Science, COMSATS University Islamabad, Vehari Campus, Vehari 61100, Pakistan, Anum Fatima, Hureeza Shahzadi, Aman Ullah, Kemal Polat, Department of Computer Science, COMSATS University Islamabad, Vehari Campus, Vehari 61100, Pakistan, Department of Computational Science & Engineering, National University of Sciences and Technology, Islamabad, School of Computer Science and Engineering, Central South University, Changsha, 410083, China, Department of Electrical and Electronics Engineering, Bolu Abant Izzet Baysal University, Bolu 14280, Turkey
2021 Journal of Artificial Intelligence and Systems  
The problem with spam filtration is that sometimes person mistakenly mark an important email received from high authority as spam and according to previous research, this email will be filtered as spam  ...  Previous research has done work on email categorization in which they have mostly done spam filtration.  ...  [13] Many methods are available to filter spam emails.  ... 
doi:10.33969/ais.2021.31007 fatcat:ftlmennccjebpmx5telyrbfq5e

Incremental Learning for Spam Detection

Amin Shams, Touraj Banirostam
2017 IJARCCE  
approach based on collective learning.  ...  filtering such junk emails.  ...  Heidari [6] discussed "intelligent spam filtering system using machine learning algorithms" in his paper.  ... 
doi:10.17148/ijarcce.2017.6101 fatcat:bvnr7kxbzra4jjvfqj6itbkclq

A Comprehensive Survey for Intelligent Spam Email Detection

Asif Karim, Sami Azam, Bharanidharan Shanmugam, Krishnan Kannoorpatti, Mamoun Alazab
2019 IEEE Access  
Based on the number the relevance of an emerging intelligent method, papers representing each method were identified, read, and summarized.  ...  The tremendously growing problem of phishing e-mail, also known as spam including spear phishing or spam borne malware, has demanded a need for reliable intelligent anti-spam e-mail filters.  ...  As explained earlier, labelled documents contain labelled data; that is data for which the target answer is already known.  ... 
doi:10.1109/access.2019.2954791 fatcat:ikt6cayggbb2dkrm52fxzz2dqm
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