Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/22921
Title: | Studying And Improving Techniques To Mitigate EMail Threats |
Researcher: | Dhanalakshmi R |
Guide(s): | Chellappan C |
Keywords: | directory harvesting EMail Threats malicious users Mitigate Techniques |
Upload Date: | 19-Aug-2014 |
University: | Anna University |
Completed Date: | n.d. |
Abstract: | EMail an Internet application is the vital communication medium newlineof the modern information society It has become the most essential newlineinfrastructure for organizations to share information easily rapidly and newlinepromptly Due to its widespread ease of use it poses many threats such as newlinespam phishing denial of service attacks identity theft directory harvesting newlineattacks data leakage distribution of illegal content and so on The various newlinechallenges may compromise the entire organization and may take control of newlineeverything including the users which also causes loss of productivity newlineResearchers deploy solutions but the malicious users adopt various newlinetechniques to overcome them for financial benefits and other malicious newlinepurposes The email threats that emerge in the organization via users inbox newlineare inbound email threats which include spam phishing mails newlineviruseswormsmalicious code denial of service attacks relay hijacking and newlinedirectory harvesting The outbound email threat as a confidential data leakage newlineoccurs by policy violations and masquerading file extensions Hence the newlineongoing battle against email threats continues and this thesis focuses on newlinemitigating spam and phishing mails as inbound email threat and preventing newlineconfidential data leakage as outbound email threat newlineThe first mitigation model in the proposed architecture is the source newlinebased filtering based on the header analysis and trust based classification to newlineidentify the spam and phishing mails and also for identifying spoofed mails newlineand thus prevents impersonation The second model Content Analyzer is to newlineanalyze the email contents and find the suspicious keywords using different newlineclassifiers to identify legitimate mails The third model is the URL analyzer to newlinedetect the malicious URLs leading to phishing attacks embedded in the email newlinebody content newlineThe security features of the email are carefully analyzed and are newlinefurther improved with the wellestablished cryptographic primitives such as newlineencryption decryption and digital signature functions newline newline |
Pagination: | xix, 193p |
URI: | http://hdl.handle.net/10603/22921 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 171.57 kB | Adobe PDF | View/Open |
02_certificate.pdf | 973.99 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 51.48 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 61.62 kB | Adobe PDF | View/Open | |
05_contents.pdf | 156.47 kB | Adobe PDF | View/Open | |
06_chapter 1.pdf | 504.36 kB | Adobe PDF | View/Open | |
07_chapter 2.pdf | 916.52 kB | Adobe PDF | View/Open | |
08_chapter 3.pdf | 924.62 kB | Adobe PDF | View/Open | |
09_chapter 4.pdf | 1.39 MB | Adobe PDF | View/Open | |
10_chapter 5.pdf | 1.57 MB | Adobe PDF | View/Open | |
11_chapter 6.pdf | 499.44 kB | Adobe PDF | View/Open | |
12_chapter 7.pdf | 2.06 MB | Adobe PDF | View/Open | |
13_chapter 8.pdf | 234.25 kB | Adobe PDF | View/Open | |
14_chapter 9.pdf | 76.6 kB | Adobe PDF | View/Open | |
15_references.pdf | 124.08 kB | Adobe PDF | View/Open | |
16_publications.pdf | 69.17 kB | Adobe PDF | View/Open | |
17_vitae.pdf | 53.7 kB | Adobe PDF | View/Open |
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