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Title: :  MALWARE ANALYSIS TOOL
PaperId: :  21811
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 5 2023
DUI:    16.0415/IJARIIE-21811
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
BHUVANESH V TBANNARI AMMAN INSTITUTE OF TECHNOLOGY
MUKESH NBANNARI AMMAN INSTITUTE OF TECHNOLOGY
PRAVEEN SBANNARI AMMAN INSTITUTE OF TECHNOLOGY
LAKSHMANAPRAKASHBANNARI AMMAN INSTITUTE OF TECHNOLOGY

Abstract

INFORMATION SECURITY
Malware analysis, Reverse engineering, Machine learning, Malware detection, Dimensionality reduction, Malware classification, Cybersecurity
The proliferation of malware threats in the digital landscape has posed significant challenges to cybersecurity practitioners. In response to this evolving threat landscape, this research paper explores a holistic approach to malware analysis that leverages both reverse engineering and machine learning techniques. Reverse engineering allows for the in-depth examination of malicious code, enabling a deeper understanding of its functionality and evasion techniques. Concurrently, machine learning models are employed to automate the classification and detection of malware based on extracted features and behavioral patterns. This research investigates various aspects of malware analysis, including the reverse engineering of malware binaries to uncover their inner workings, identification of malicious code patterns, and extraction of relevant features. Additionally, machine learning algorithms are trained on these features to distinguish between benign and malicious software efficiently. Furthermore, this paper discusses the advantages and challenges of combining reverse engineering and machine learning in the context of malware analysis. It highlights the benefits of increased accuracy and scalability in detecting emerging malware threats, as well as the potential pitfalls and limitations of the approach. Moreover, the paper explores the significance of continuously updating machine learning models to adapt to evolving malware tactics. The experimental results presented in this study demonstrate the effectiveness of the proposed methodology in detecting previously unknown malware samples and improving overall threat intelligence. By fusing reverse engineering expertise with machine learning capabilities, this research offers a promising avenue for enhancing the resilience of cybersecurity systems against ever-evolving malware threats.

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IJARIIE BHUVANESH V T, MUKESH N, PRAVEEN S, and LAKSHMANAPRAKASH. "MALWARE ANALYSIS TOOL" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 5 2023 Page 1891-1897
MLA BHUVANESH V T, MUKESH N, PRAVEEN S, and LAKSHMANAPRAKASH. "MALWARE ANALYSIS TOOL." International Journal Of Advance Research And Innovative Ideas In Education 9.5(2023) : 1891-1897.
APA BHUVANESH V T, MUKESH N, PRAVEEN S, & LAKSHMANAPRAKASH. (2023). MALWARE ANALYSIS TOOL. International Journal Of Advance Research And Innovative Ideas In Education, 9(5), 1891-1897.
Chicago BHUVANESH V T, MUKESH N, PRAVEEN S, and LAKSHMANAPRAKASH. "MALWARE ANALYSIS TOOL." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 5 (2023) : 1891-1897.
Oxford BHUVANESH V T, MUKESH N, PRAVEEN S, and LAKSHMANAPRAKASH. 'MALWARE ANALYSIS TOOL', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, 2023, p. 1891-1897. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/MALWARE_ANALYSIS_TOOL_ijariie21811.pdf (Accessed : ).
Harvard BHUVANESH V T, MUKESH N, PRAVEEN S, and LAKSHMANAPRAKASH. (2023) 'MALWARE ANALYSIS TOOL', International Journal Of Advance Research And Innovative Ideas In Education, 9(5), pp. 1891-1897IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/MALWARE_ANALYSIS_TOOL_ijariie21811.pdf (Accessed : )
IEEE BHUVANESH V T, MUKESH N, PRAVEEN S, and LAKSHMANAPRAKASH, "MALWARE ANALYSIS TOOL," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, pp. 1891-1897, Sep-Oct 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/MALWARE_ANALYSIS_TOOL_ijariie21811.pdf [Accessed : ].
Turabian BHUVANESH V T, MUKESH N, PRAVEEN S, and LAKSHMANAPRAKASH. "MALWARE ANALYSIS TOOL." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 5 ().
Vancouver BHUVANESH V T, MUKESH N, PRAVEEN S, and LAKSHMANAPRAKASH. MALWARE ANALYSIS TOOL. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(5) : 1891-1897. Available from: https://ijariie.com/AdminUploadPdf/MALWARE_ANALYSIS_TOOL_ijariie21811.pdf
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