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Identification of Spoofed Emails by applying Email Forensics and Memory Forensics

Published: 13 March 2021 Publication History

Abstract

Email forensics is the subdomain of network forensics, and email spoofing is the most common type of email attack. Email spoofing is a process of creating a forged message by manipulating the sender’s email address so that it appears to the recipient that the originating email is coming from a genuine sender. Spoofed email attack and its detection is a challenging problem in email forensic investigation. Research in the past has tried to address email detection by different mechanisms. This paper tries to improve and fill some of the research gaps from the base paper of R.P Iyer [11]. In our work, we detect spoofed emails received by the user by applying memory forensic approach. Instead of capturing the complete memory dump, we only capture the browser’s live running processes from memory and extract the email header for analysis. This reduces the size of the memory dump and makes detection fast. Also proposed detection algorithm overcomes messageID based detection failures by applying nslookup to fetch MX record to identify the genuine emails. The advantage of memory forensic application for spoofed email detection is that we get guaranteed non-repudiation of the user’s digital footprint in physical memory. The results of the performance analysis show that the entire task can be completed in approximately 1 min with high accuracy with minimum false positives. The proposed method detects spoofed emails without disrupting the regular operation of the testing machine.

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Cited By

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  • (2024)Email bombing attack detection and mitigation using machine learningInternational Journal of Information Security10.1007/s10207-024-00871-723:4(2939-2949)Online publication date: 13-Jun-2024
  • (2023)Forensic Analysis and Detection of Spoofing Based Email Attack Using Memory Forensics and Machine LearningSecurity and Privacy in Communication Networks10.1007/978-3-031-25538-0_26(491-509)Online publication date: 4-Feb-2023
  • (2022)MemInspect2: OS-Independent Memory Forensics for IoT Devices in Cybercrime Investigations2022 IEEE/ACIS 22nd International Conference on Computer and Information Science (ICIS)10.1109/ICIS54925.2022.9882517(162-169)Online publication date: 26-Jun-2022
  • Show More Cited By

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cover image ACM Other conferences
ICCNS '20: Proceedings of the 2020 10th International Conference on Communication and Network Security
November 2020
145 pages
ISBN:9781450389037
DOI:10.1145/3442520
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 March 2021

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Author Tags

  1. Email Forensics.
  2. Email Spoofing
  3. Memory Forensics

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Cited By

View all
  • (2024)Email bombing attack detection and mitigation using machine learningInternational Journal of Information Security10.1007/s10207-024-00871-723:4(2939-2949)Online publication date: 13-Jun-2024
  • (2023)Forensic Analysis and Detection of Spoofing Based Email Attack Using Memory Forensics and Machine LearningSecurity and Privacy in Communication Networks10.1007/978-3-031-25538-0_26(491-509)Online publication date: 4-Feb-2023
  • (2022)MemInspect2: OS-Independent Memory Forensics for IoT Devices in Cybercrime Investigations2022 IEEE/ACIS 22nd International Conference on Computer and Information Science (ICIS)10.1109/ICIS54925.2022.9882517(162-169)Online publication date: 26-Jun-2022
  • (2022)Advanced Analysis of Email Sender Spoofing Attack and Related Security Problems2022 IEEE 9th International Conference on Cyber Security and Cloud Computing (CSCloud)/2022 IEEE 8th International Conference on Edge Computing and Scalable Cloud (EdgeCom)10.1109/CSCloud-EdgeCom54986.2022.00023(80-85)Online publication date: Jun-2022
  • (2021)Pattern Recognition and Reconstruction: Detecting Malicious Deletions in Textual Communications2021 IEEE International Conference on Big Data (Big Data)10.1109/BigData52589.2021.9671921(2574-2582)Online publication date: 15-Dec-2021
  • (2021)A Forensic Framework for Webmail Threat Detection Using Log AnalysisInnovative Security Solutions for Information Technology and Communications10.1007/978-3-031-17510-7_5(57-69)Online publication date: 25-Nov-2021
  • (2021)Multi Layer Detection Framework for Spear-Phishing AttacksInformation Systems Security10.1007/978-3-030-92571-0_3(38-56)Online publication date: 16-Dec-2021

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