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Title: :  To Detect Internal Attack by Using Data Mining and Forensic Technique
PaperId: :  1703
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 2 Issue 2 2016
DUI:    16.0415/IJARIIE-1703
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Geeta A. PadwalSanjivini College of Engineering,Kopargaon,Tal. Kopargaon,Dist. Ahmednagar
Shubhangi B. MateSanjivini College of Engineering,Kopargaon,Tal. Kopargaon,Dist. Ahmednagar
Manisha S. KotkarSanjivini College of Engineering,Kopargaon,Tal. Kopargaon,Dist. Ahmednagar
Shital B. RahaneSanjivini College of Engineering,Kopargaon,Tal. Kopargaon,Dist. Ahmednagar
Mr. M. B. Gawali Sanjivini College of Engineering,Kopargaon,Tal. Kopargaon,Dist. Ahmednagar

Abstract

Computer Engineering
Data mining, insider attack, intrusion detection and protection, system call (SC), users’ behaviors
Now a day’s lot of the users use ids and passwords as login pattern for the authenticate users. However making patterns is weakest point of computer security as so many user share the login pattern with the co-workers for the completed co-task, inside attacker is attacked internally and it will be valid attacker of system, As using intrusion detection systems and firewalls identify and isolate harmful behaviors generated from the outside world we can find out internal attacker of the system only. In some of the studied define examine that system calls generated by some commands and these command help to find detect accurate attacks, and attack patterns are the features of an attack. However in the paper security System defines as the Internal Intrusion Detection and Protection System (IIDPS), is help to detect internally attacks by using data mining and forensic technique at SC level. For the track the information of users usages the IIDPS creates users’ personal profiles as their forensic features and investigate that the valid login user is account holder can login or not by comparing his/her current computer usage behaviors with the patterns collected in the account holder’s personal profile. The experimental results demonstrate that the IIDPS’s user identification accuracy is 94.29%, whereas the response time is less than 0.45s, implying that it can prevent a protected system from insider attacks effectively and efficiently.

Citations

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IJARIIE Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, and Mr. M. B. Gawali . "To Detect Internal Attack by Using Data Mining and Forensic Technique" International Journal Of Advance Research And Innovative Ideas In Education Volume 2 Issue 2 2016 Page 352-358
MLA Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, and Mr. M. B. Gawali . "To Detect Internal Attack by Using Data Mining and Forensic Technique." International Journal Of Advance Research And Innovative Ideas In Education 2.2(2016) : 352-358.
APA Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, & Mr. M. B. Gawali . (2016). To Detect Internal Attack by Using Data Mining and Forensic Technique. International Journal Of Advance Research And Innovative Ideas In Education, 2(2), 352-358.
Chicago Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, and Mr. M. B. Gawali . "To Detect Internal Attack by Using Data Mining and Forensic Technique." International Journal Of Advance Research And Innovative Ideas In Education 2, no. 2 (2016) : 352-358.
Oxford Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, and Mr. M. B. Gawali . 'To Detect Internal Attack by Using Data Mining and Forensic Technique', International Journal Of Advance Research And Innovative Ideas In Education, vol. 2, no. 2, 2016, p. 352-358. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/To_Detect_Internal_Attack_by_Using__Data_Mining_and_Forensic_Technique_ijariie1703.pdf (Accessed : 13 April 2016).
Harvard Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, and Mr. M. B. Gawali . (2016) 'To Detect Internal Attack by Using Data Mining and Forensic Technique', International Journal Of Advance Research And Innovative Ideas In Education, 2(2), pp. 352-358IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/To_Detect_Internal_Attack_by_Using__Data_Mining_and_Forensic_Technique_ijariie1703.pdf (Accessed : 13 April 2016)
IEEE Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, and Mr. M. B. Gawali , "To Detect Internal Attack by Using Data Mining and Forensic Technique," International Journal Of Advance Research And Innovative Ideas In Education, vol. 2, no. 2, pp. 352-358, Mar-App 2016. [Online]. Available: https://ijariie.com/AdminUploadPdf/To_Detect_Internal_Attack_by_Using__Data_Mining_and_Forensic_Technique_ijariie1703.pdf [Accessed : 13 April 2016].
Turabian Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, and Mr. M. B. Gawali . "To Detect Internal Attack by Using Data Mining and Forensic Technique." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 2 number 2 (13 April 2016).
Vancouver Geeta A. Padwal, Shubhangi B. Mate, Manisha S. Kotkar, Shital B. Rahane, and Mr. M. B. Gawali . To Detect Internal Attack by Using Data Mining and Forensic Technique. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2016 [Cited : 13 April 2016]; 2(2) : 352-358. Available from: https://ijariie.com/AdminUploadPdf/To_Detect_Internal_Attack_by_Using__Data_Mining_and_Forensic_Technique_ijariie1703.pdf
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