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Fuzzy Rule based Novel Approach to Spam Filtering

G. Santhi, S. Maria Wenisch, P. Sengutuvan
2013 International Journal of Computer Applications  
Rapid growth rate of the use of the internet has dramatically increased the spam mails. More methods are adopted for filtering spam.  ...  The spam mails are used by spammer which amounts to be a headache to the internet users and organizations using online.  ...  [15] proposed a method of trainable fuzzy filters for filtering spam mails automatically.  ... 
doi:10.5120/12427-8995 fatcat:rcbwewmzjnguhlbqj5t4hiozgq

A Model for Fuzzy Logic Based Machine Learning Approach for Spam Filtering

Mehdi Samiei yeganeh
2012 IOSR Journal of Computer Engineering  
E-mail provides a perfect way to send these millions of advertisements without any for a sender, and this fortunate fact is nowadays extensively exploited by several organizations.  ...  As a result, the e-mail boxes of millions of people get cluttered with all these so-called Unsolicited Bulk  ...  Using a fuzzy similarity approach, a classification model is built from a set of pre-classified e-mail instances [5] . In this method we have three stages for filtering the spam.  ... 
doi:10.9790/0661-0450710 fatcat:rf4olav5unbpfhzarxwsd7hldm

An Anti-Spam Engine using Fuzzy Logic with Enhanced Performance Tuning

Vijayan R, Viknesh S T G M, Subhashini S
2011 International Journal of Computer Applications  
Fuzzy Evaluation Fig. 2 Fuzzy Evaluation Process To address this problem, the fuzzy inference methods follow hyperlinks contained in the email body, fetch contents of a remote web page, and extract hints  ...  To address this problem, Fuzzy inference [7] method follow hyperlinks contained in the email body, fetch contents of a remote webpage and extract hints from both original email body and fetched web pages  ... 
doi:10.5120/1992-2685 fatcat:7iko4qmuvngebmjl7l6igyajmi

Spam E-mail Filtering using ECOS Algorithms

Ammar Almomani, Atef Obeidat, Karim Alsaedi, M. Al-Hazaimeh Obaida, Mohammed Al-Betar
2015 Indian Journal of Science and Technology  
Our proposed is a novel system called Spamming Dynamic Evolving Neural Fuzzy System (SDENFS), which adapts the Evolving Connectionist System (ECoS) based on a hybrid (supervised/unsupervised) learning  ...  Two datasets composed of 6612 samples of spam and legitimate E-mails were used to assess the proposed system. The proposed system showed a high level of performance in detecting spam E-mail attacks.  ...  Finally, the Dynamic Evolving Neural Fuzzy Inference System (DENFIS) 14 is utilized in online mode as a fuzzy inference system to create, update, or delete a fuzzy rule while the system is running.  ... 
doi:10.17485/ijst/2015/v8is9/55320 fatcat:mek4fvldqbdbtk26o2m44j3him

ANFIS based Spam filtering model for Social Networking Websites

Dhananjay Kalbande, Harsh Panchal, Nisha Swaminathan, Preeti Ramaraj
2012 International Journal of Computer Applications  
We plan to use an adaptive neuro fuzzy inference system (ANFIS) that incorporates the advantages of both the neural networking concepts and fuzzy logic to identify the spam messages on such websites.  ...  For the purpose of this paper, we would like to concentrate more on social networking spam (SNS).  ...  [2] In this paper, we explore yet another method based on Adaptive Neuro Fuzzy Inference System (ANFIS) to detect and filter spam in social networking websites.  ... 
doi:10.5120/6310-8635 fatcat:qw7jtozwb5bo7jiuysldnh7ag4

Automated Spam Filtering through Data Mining Approach

Deepika Mallampati, Amitesh Madhur, Gundari Abhinay, Gopalam Tanuja
2017 Sreyas International Journal of Scientists and Technocrats  
Spam messages can be referred as those mails which come into act in the absence of a standard agreement among the senders and receivers for receiving e-mail solicitation.  ...  For preventing the spam delivery, an automatic system based spam filter tool is employed. The objectives of spam filters and spam are contradicted diametrically.  ...  This is trained with the examination of use of fuzzy clustering algorithm to construct a spam mail filter.  ... 
doi:10.24951/ fatcat:cfv33n7vhvejnh7anw733r22q4

Fuzzy Logic Approach for Email SPAM Detection System

Damian Prihadi, Vivin Trisyanti
2020 Zenodo  
This research was conducted with the aim of utilizing fuzzy logic in the e-mail spam detection process.  ...  The final result of the whole process is the formation of a cluster or group of e-mails that are identified as SPAM and those that are not SPAM.  ...  For that we need a media that can detect and filter spam, so that it can separate spam e-mail. Research to detect the presence of spam has been developed.  ... 
doi:10.5281/zenodo.4059517 fatcat:q6r3k2lnvjdgxjsqo4vdojdgny

Clustering Spam Campaigns with Fuzzy Hashing

Jianxing Chen, Romain Fontugne, Akira Kato, Kensuke Fukuda
2014 Proceedings of the AINTEC 2014 on Asian Internet Engineering Conference - AINTEC '14  
In this paper we propose a new method based on fuzzy hashing to cluster spam with common goals into the same spam campaign.  ...  Using the proposed method we process a three year long dataset that consists of 540 thousand spam emails.  ...  In this work we infer botnets from the list of IP addresses accountable for a same spam campaign.  ... 
doi:10.1145/2684793.2684803 dblp:conf/aintec/ChenFKF14 fatcat:xoxtlslgobfmle24tsrqquky3a

Phishing Dynamic Evolving Neural Fuzzy Framework for Online Detection Zero-day Phishing Email [article]

Ammar ALmomani, B. B. Gupta, Tat-Chee Wan, Altyeb Altaher, Selvakumar Manickam
2013 arXiv   pre-print
Phishing is a kind of attack in which criminals use spoofed emails and fraudulent web sites to trick financial organization and customers.  ...  Finally, DENFIS is utilized in online mode as a fuzzy inferences system to create, update, or delete a fuzzy rule while the system is running.  ...  The implementation of the proposed framework adapts the evolving clustering method (ECM) as a part of the dynamic evolving neural fuzzy inference system (DENFIS) in an online mode(N.  ... 
arXiv:1302.0629v1 fatcat:u6kwl3cfeze37b3fpfslz7fl4e

A Review of Text Classification Approaches for E-mail Management

Upasana Pandey, S. Chakraverty
2011 International Journal of Engineering and Technology  
E-mail filtering and email organization is an application rife with the potential to streamline the management of the vast amount of information that accumulates in the inbox.  ...  This paper attempts to categorize the prevalent popular techniques for classifying email as spam or legitimate and suggests possible techniques to fill in the lacunae in the arena of automatic management  ...  Bayesian spam filtering is a form of e-mail filtering that uses the naïve Bayesian classifier to identify spam e-mail [2] . Suppose the suspected e-mail message contains the word W.  ... 
doi:10.7763/ijet.2011.v3.212 fatcat:ngwc2hkbo5dvfjwc53yzdgnz2i

Privacy-Aware Collaborative Spam Filtering

K. Li, Z. Zhong, L. Ramaswamy
2009 IEEE Transactions on Parallel and Distributed Systems  
Toward addressing these challenges, this paper presents ALPACAS-a privacy-aware framework for collaborative spam filtering. In designing the ALPACAS framework, we make two unique contributions.  ...  While the concept of collaboration provides a natural defense against massive spam e-mails directed at large numbers of recipients, designing effective collaborative anti-spam systems raises several important  ...  The authors would like to thank the anonymous reviewers for their insightful comments.  ... 
doi:10.1109/tpds.2008.143 fatcat:lxgoo75cuvhe7ca7tsozzcdcpa

Adaptive e-mail intention finding mechanism based on e-mail words social networks

Che-Fu Yeh, Ching-Hao Mao, Hahn-Ming Lee, Tsuhan Chen
2007 Proceedings of the 2007 workshop on Large scale attack defense - LSAD '07  
Through the rapid evaluation of spam, no fully successful solution for filtering spam has been found.  ...  In this investigation, we propose a mechanism of Email Words Social Network (EWSN) for profiling users' intentions related to interesting and uninteresting e-mails.  ...  Boykin and Roychowdhury [8] proposed a concise method for applying personal e-mail network to filter spam. O'Donnel et al.  ... 
doi:10.1145/1352664.1352670 fatcat:e74xqgfkyjghrmlnw5rlieluuy

Machine Learning for E-mail Spam Filtering: Review,Techniques and Trends [article]

Alexy Bhowmick, Shyamanta M. Hazarika
2016 arXiv   pre-print
We present a comprehensive review of the most effective content-based e-mail spam filtering techniques.  ...  The initial exposition of the background examines the basics of e-mail spam filtering, the evolving nature of spam, spammers playing cat-and-mouse with e-mail service providers (ESPs), and the Machine  ...  tool for e-mail spam filtering.  ... 
arXiv:1606.01042v1 fatcat:cblnuc4knfhehjwzjeeekbgf3m

Approaches for Web Spam Detection

Kanchan Hans, Laxmi Ahuja, S. K. Muttoo
2014 International Journal of Computer Applications  
Web Security being a prime challenge for search engines has motivated the researchers in academia and industry to devise new techniques for web spam detection.  ...  Spam is a major threat to web security. The web of trust is being abused by the spammers through their ever evolving new tactics for their personal gains.  ...  Authors have combined the fuzzy logic with data mining algorithms to design an anti-spam filter.  ... 
doi:10.5120/17655-8467 fatcat:vjlkkwa6wbeupe6afkstqeeday


Arshey M, Dr. K.S Angel Viji
2021 Indian Journal of Computer Science and Engineering  
Detection of phishing attacks and classifying the mails still remains a challenging issue.  ...  This research presents an effective strategy by developing a newly proposed method called Fractional-EarthWorm Algorithm (EWA) based Deep Convolutional Neural Network.  ...  Anuj Kumar Singh [8] et al. devised a method to recognize the best classifier for spam mail classification using Fuzzy C-Means algorithm.  ... 
doi:10.21817/indjcse/2021/v12i5/211205014 fatcat:m6ibnxehkrdhbggcicc6vkg3km
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