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E-Mail Spam Detection Using Refined MLP with Feature Selection

Harjot Kaur, Er. Prince Verma
2017 International Journal of Modern Education and Computer Science  
This paper will discuss the process of filtering the emails into spam and ham using various techniques.  ...  E-Mails are used as a major and important mode of information sharing because emails are faster and effective way of communication.  ...  ACKNOWLEDGMENT The author expresses its humble thanks to CT group of Engineering, Management, and Technology for their motivational participation and encouragement in the research field.  ... 
doi:10.5815/ijmecs.2017.09.05 fatcat:gxxzb7bv55g3tjxgxjz4mmn7be

CLASSIFICATION OF VULGAR COMMENTS USINGCONVOLUTIONAL NEURAL NETWORKWITH GLUON NATURAL LANGUAGE PROCESSING

Mohsinul Bari Shakir Rufyda Jahan, Surovi Zinia And Md. Iftekharul Mobin
2020 Zenodo  
The system shows 95.4% accuracy to detect and classify the vulgar comments.  ...  Withthe advancement of technology, the virtual platform and social media have become an important part of peoples daily life.  ...  Junk fax :Junk fax is similar to email spam. The main distinction lies is that spam in junk fax is obtained as faxes through fax transmission.  ... 
doi:10.5281/zenodo.4108306 fatcat:4mwrzdgyxnhsfgwyngoouoe6ka

A Comparative Study of Classification Algorithms on Spam Detection

G. V. Gayathri
2018 International Journal for Research in Applied Science and Engineering Technology  
Here we are going to check the performance of many classifiers with the use of feature selection algorithm and we found that in the result analysis part the Random Forest classifier provides finer accuracy  ...  Here we are going to experiment many data mining techniques to the dataset of spam in an attempt to search the most suitable classifier to text message classification as spam and non-spam.  ...  exploration of science and control of production, retention of customer and detection of fraud and for analysis of market .It is combination of fields such as database systems, statics, machine learning  ... 
doi:10.22214/ijraset.2018.4785 fatcat:wlagzjilhbhrdbpspogz2wntm4

Study on the Effectiveness of Spam Detection Technologies

Muhammad Iqbal, Malik Muneeb Abid, Mushtaq Ahmad, Faisal Khurshid
2016 International Journal of Information Technology and Computer Science  
This work focuses on systematically analyzing the strength and weakness of current technologies for spam detection and taxonomy of known approaches is introduced.  ...  Currently, a large volume of received emails are spam.  ...  by mobile phone, by fax, Web spam and etc.  ... 
doi:10.5815/ijitcs.2016.01.02 fatcat:2lao7w3mkzck3dyacxfej4i5wi

Link analysis for Web spam detection

Luca Becchetti, Carlos Castillo, Debora Donato, Ricardo Baeza-YATES, Stefano Leonardi
2008 ACM Transactions on the Web  
The issue of Web spam is widespread and difficult to solve, mostly due to the large size of the Web which means that, in practice, many algorithms are infeasible.  ...  We perform a statistical analysis of a large collection of Web pages.  ...  We also thank Karen Whitehouse for a thorough revision of the English.  ... 
doi:10.1145/1326561.1326563 fatcat:6zbrk6u4fbdjpbg7hmmfl3uuua

An Online Malicious Spam Email Detection System Using Resource Allocating Network with Locality Sensitive Hashing

Siti-Hajar-Aminah Ali, Seiichi Ozawa, Junji Nakazato, Tao Ban, Jumpei Shimamura
2015 Journal of Intelligent Learning Systems and Applications  
The results confirm that the proposed spam email detection system has capability of detecting with high detection rate.  ...  In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious  ...  (UTHM) and the Ministry of Education Malaysia (KPM).  ... 
doi:10.4236/jilsa.2015.72005 fatcat:egjfkkrghjbetlsg7xnixlhy6m

An Immunological-Based Simulation: A Case Study of Risk Concentration for Mobile Spam Context Assessment

Kamahazira Zainal, Mohd Zalisham Jali
2018 International Journal on Advanced Science, Engineering and Information Technology  
(DCA) and Deterministic Dendritic Cell Algorithm (dDCA).  ...  Besides the factor of integration of Internet and mobile technology, this issue is also due to the human's reaction towards spam.  ...  The employment of AIS in computational intelligence includes spam classification, virus detection [3] , anomaly detection [4] , intrusion detection [5] , [6] and optimization.  ... 
doi:10.18517/ijaseit.8.3.2719 fatcat:llk74visqvb6be6vzetmkz2qey

A Content Vector Model For Text Classification

Eric Jiang
2008 Zenodo  
email classifiers based on the well-known SVM and naïve Bayes algorithms.  ...  The model integrates the class discriminative information from the training data and is equipped with several pertinent feature selection and text classification algorithms.  ...  The experiments on PU1 have demonstrated that the proposed content vector model is very effective for spam detection and filtering, and represents a very competitive alternative to other well-known classifiers  ... 
doi:10.5281/zenodo.1078288 fatcat:ptd4hleikrgrnn77chuq6qwp5a

Zero-day Malicious Email Investigation and Detection Using Features with Deep-learning Approach

Sanouphab Phomkeona, Koji Okamura
2020 Journal of Information Processing  
We succeeded in obtaining a satisfactory accuracy rate for detection results for both zero-day malicious email types and normal spam.  ...  In this paper, we introduce a way to classify and detect zero-day malicious emails by using deep-learning with data investigated from the email header and body itself, combined with dynamic analysis information  ...  Above the popular well-known algorithms NB, SVN, or K-Nearest Neighbor (KNN), running the MPL neural network algorithm on test data seems to be the best way to detect spam in terms of efficiency.  ... 
doi:10.2197/ipsjjip.28.222 fatcat:c5ae5ykwmvf7zkafyntttvpv3m

Layout Based Spam Filtering

Claudiu N.Musat
2007 Zenodo  
We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.  ...  This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision.  ...  CONCLUSION AND FUTURE WORK In this paper, we have proposed a new algorithm for spam detection based solely on the email message structural similarities, this being, to the best of our knowledge, the first  ... 
doi:10.5281/zenodo.1085252 fatcat:vfc4au6t2nb4bapyqzxqvrsbvy

Thwarting E-mail Spam Laundering

Mengjun Xie, Heng Yin, Haining Wang
2008 ACM Transactions on Privacy and Security  
We implement a prototype of DBSpam based on libpcap, and validate its efficacy on spam detection and suppression through both theoretical analyses and trace-based experiments.  ...  Based on the packet symmetry exhibited in spam laundering, we propose a simple and effective technique, DBSpam, to online detect and break spam laundering activities inside a customer network.  ...  In contrast, detecting spam proxies is the major task of DBSpam, and proxy identification and spam tracking can only be accomplished through traffic analysis.  ... 
doi:10.1145/1455518.1455525 fatcat:7qf7ezl275d2zjmq3fzmctdsau

Collaborative Security

Guozhu Meng, Yang Liu, Jie Zhang, Alexander Pokluda, Raouf Boutaba
2015 ACM Computing Surveys  
Thus far, collaboration has been used in many domains such as intrusion detection, spam filtering, botnet resistance, and vulnerability detection.  ...  We then present a comprehensive study with respect to their analysis target, timeliness of analysis, architecture, network infrastructure, initiative, shared information and interoperability.  ...  -The domains of intrusion detection, spam filtering, malware blocking, the detection of internal attackers, and the detection of botnets.  ... 
doi:10.1145/2785733 fatcat:mu6hd7jk4vgjxhdhkpvjuose4e

Proactive defense for evolving cyber threats

Richard Colbaugh, Kristin Glass
2011 Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics  
Department of Defense, the U.S. Department of Homeland Security, The Boeing Company, and the Laboratory Directed Research and Development program at Sandia National Laboratories.  ...  Fruitful discussions regarding aspects of this work with Curtis Johnson of Sandia National Laboratories, Paul Ormerod of Volterra Partners, and Anne Kao of Boeing are gratefully acknowledged.  ...  Spam more difficult to detect.  ... 
doi:10.1109/isi.2011.5984062 dblp:conf/isi/ColbaughG11 fatcat:o3jnwuqicjd2hosgjn5ygwy6hq

Identification of SPAM messages using an approach inspired on the immune system

T.S. Guzella, T.A. Mota-Santos, J.Q. Uchôa, W.M. Caminhas
2008 Biosystems (Amsterdam. Print)  
An implementation of the algorithm was capable of identifying more than 99% of legitimate or SPAM messages in particular parameter configurations.  ...  In this paper, an immune-inspired model, named innate and adaptive artificial immune system (IA-AIS) is proposed and applied to the problem of identification of unsolicited bulk e-mail messages (SPAM).  ...  The authors would like to thank an anonymous reviewer and the editor-in-chief for their insightful comments, which helped improve the quality of the paper.  ... 
doi:10.1016/j.biosystems.2008.02.006 pmid:18395967 fatcat:nhqnwr65qnc2pcswlalkgkhd2u

From Blind to Quantitative Steganalysis

Tomáš Pevny, Jessica Fridrich, Andrew D. Ker
2012 IEEE Transactions on Information Forensics and Security  
To demonstrate the generality of the proposed approach, quantitative steganalyzers are constructed for a variety of steganographic algorithms in both JPEG transform and spatial domains.  ...  Since for most algorithms the number of embedding changes correlates with the message length, quantitative steganalyzers are important forensic tools.  ...  -PEV features), and LSB matching (using SPAM features).  ... 
doi:10.1109/tifs.2011.2175918 fatcat:d2n4ehju6zcujgd3jlvqkq4r6q
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