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E-Mail Spam Detection Using Refined MLP with Feature Selection
2017
International Journal of Modern Education and Computer Science
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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
2020
Zenodo
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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
2018
International Journal for Research in Applied Science and Engineering Technology
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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
2016
International Journal of Information Technology and Computer Science
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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
2008
ACM Transactions on the Web
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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
2015
Journal of Intelligent Learning Systems and Applications
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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
2018
International Journal on Advanced Science, Engineering and Information Technology
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(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
2008
Zenodo
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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
2020
Journal of Information Processing
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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
2007
Zenodo
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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
2008
ACM Transactions on Privacy and Security
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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
2015
ACM Computing Surveys
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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
2011
Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics
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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
2008
Biosystems (Amsterdam. Print)
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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
2012
IEEE Transactions on Information Forensics and Security
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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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