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Title: Studying And Improving Techniques To Mitigate EMail Threats
Researcher: Dhanalakshmi R
Guide(s): Chellappan C
Keywords: directory harvesting
EMail Threats
malicious users
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
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File171.57 kBAdobe PDFView/Open
02_certificate.pdf973.99 kBAdobe PDFView/Open
03_abstract.pdf51.48 kBAdobe PDFView/Open
04_acknowledgement.pdf61.62 kBAdobe PDFView/Open
05_contents.pdf156.47 kBAdobe PDFView/Open
06_chapter 1.pdf504.36 kBAdobe PDFView/Open
07_chapter 2.pdf916.52 kBAdobe PDFView/Open
08_chapter 3.pdf924.62 kBAdobe PDFView/Open
09_chapter 4.pdf1.39 MBAdobe PDFView/Open
10_chapter 5.pdf1.57 MBAdobe PDFView/Open
11_chapter 6.pdf499.44 kBAdobe PDFView/Open
12_chapter 7.pdf2.06 MBAdobe PDFView/Open
13_chapter 8.pdf234.25 kBAdobe PDFView/Open
14_chapter 9.pdf76.6 kBAdobe PDFView/Open
15_references.pdf124.08 kBAdobe PDFView/Open
16_publications.pdf69.17 kBAdobe PDFView/Open
17_vitae.pdf53.7 kBAdobe PDFView/Open

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