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Performance Analysis, Comparative Survey of Various Classification Techniques in Spam Mail Filtering


Affiliations
1 D.C.S.A., M.D.U. ,Rohtak, India
2 D.C.S.A., M.D.U., Rohtak, India
 

One of the most common methods of communication involves the use of e-mail for personal messages or for business purposes. One of the major concerns of using the e-mails is the problem of e-mail spam. The worst part of the spam e-mails is that, these are invading the users without their consent and bombarding of these spam mails fills up the whole e-mail space of the user along with that, the issue of the wasting the network capacity and time consumption in checking and deleting the spam mails makes it even more concerning issue. With the increasing demand of removing the e-mail spams the area has become magnetic to the researchers. This paper intends to present the performance comparison analysis of various pre-existing classification technique. This paper discusses about spam mails in section (I), In section (II) various feature selection methods are discussed , In section (III) classification techniques concept in spam filtering has been elaborated, In section (IV) existing algorithms for classification are discussed and are compared. In section (V) concludes the paper giving brief summary of the work.

Keywords

Classification, E-mail Threats, Spam Filtering, Efficiency , Feature Selection.
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  • Omar Saad, Ashraf Darwish and Ramadan Faraj: “Asurvey of machine learning techniques for Spam filtering”, IJCSNS ,International Journal of Computer Science and Network Security, VOL.12 No.2, February 2012.
  • I. Androutsopoulos, J. Koutsias, “An evaluation of naïve Bayesian anti-spam filtering”, 11thEuropean Conference on Machine Learning (ECML 2000),pp 9–17, 2000.
  • Androutsopoulos, G. Paliouras, “Learning to filter spam E-mail: A comparison of a naïve Bayesian and a memory based approach”, 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, pp 1–13, 2000.
  • K. Schneider, “A comparison of event models for naive bayes anti-spam e-mail filtering”, 10th Conference of the European Chapter of the Association for Computational Linguistics, pp.307-314, 2003.
  • N. Cristianini, B. Schoelkopf, “Support vector machines and kernel methods, the new generation of learning machines”. Artificial Intelligence Magazine, pp 31–41, 2002 6. S. Amari, S. Wu, “Improving support vector machine classifiers by modifying kernel functions”. Neural Networks, pp 783–789, 1999.
  • C. Miller, “Neural Network-based Antispam Heuristics”, Symantec Enterprise Security (2011), www.symantec.com Retrieved December 28, 2011
  • Anirudh Harisinghaney, Aman Dixit, Saurabh Gupta, and Anuja Arora , “Text and image based spam e-mail classification using KNN, Naïve Bayes and reverse DBSCAN Algorithm, “ ICROIT 2014, India, Feb 6-8 2014.
  • Masurah Mohamad and Ali Selamat, “An evaluation on the efficiency of hybrid feature selection in spam e-mail classification,” IEEE International Conference on Computer Communication, and Control Technology (14CT 2015), April. 2015.
  • Rushdi Shams and Robert E. Mercer, “Classification spam e-mails using text and readability features,” IEEE 13th International Conference on Data Mining, pp. 657-666, 2013.
  • Megha Rathi and Vikas Pareek, “Spam E-mail Detection through Data Mining-A Comparative Performance Analysis,” I.J. Modern Education and Computer Science, pp. 31-39, 2013.
  • Ms.D. Karthika Renuka, Dr.T. Hamsapriya, Mr.M. Raja Chakkaravar t h i , Ms.P. Lakshmisurya, “Spam Classification based on Supervised Learning using Machine Learning Techniques,” IEEE, pp.1-7, 2011
  • V. Vaithiyanathan , K. Rajeswari , Kapil Tajan , Rahul Pitale, “Comparison Of Different Classification Techniques Using Different Data sets” , IJAET , ISSN: 2231-1963 ,Vol. 6, Issue 2, pp. 764-768 , May 2013

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  • Performance Analysis, Comparative Survey of Various Classification Techniques in Spam Mail Filtering

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Authors

Priti
D.C.S.A., M.D.U. ,Rohtak, India
Uma
D.C.S.A., M.D.U., Rohtak, India

Abstract


One of the most common methods of communication involves the use of e-mail for personal messages or for business purposes. One of the major concerns of using the e-mails is the problem of e-mail spam. The worst part of the spam e-mails is that, these are invading the users without their consent and bombarding of these spam mails fills up the whole e-mail space of the user along with that, the issue of the wasting the network capacity and time consumption in checking and deleting the spam mails makes it even more concerning issue. With the increasing demand of removing the e-mail spams the area has become magnetic to the researchers. This paper intends to present the performance comparison analysis of various pre-existing classification technique. This paper discusses about spam mails in section (I), In section (II) various feature selection methods are discussed , In section (III) classification techniques concept in spam filtering has been elaborated, In section (IV) existing algorithms for classification are discussed and are compared. In section (V) concludes the paper giving brief summary of the work.

Keywords


Classification, E-mail Threats, Spam Filtering, Efficiency , Feature Selection.

References





DOI: https://doi.org/10.13005/ojcst%2F10.03.21