Malware detection using machine learning
*Gauri DhongadeCorresponding authorgauridhongade13@gmail.comDepartment of Information TechnologyMATS UniversityRaipur, Chhattisgarh, 492001, IndiaView full profile → , Omprakash Chandrakardromprakashc@matsuniversity.ac.inDepartment of Information TechnologyMATS UniversityRaipur, Chhattisgarh, 492001, IndiaView full profile → , Rajeshree Khanderajeshreekhande@gmail.comDepartment of Technology and ManagementShri Balaji Institute of Technology & ManagementSri Balaji University, PunePune, Maharashtra, 411033, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Nov 2025
- Published Online:
- 31 Aug 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2209
- Pages:
- 2877–2889
Abstract
In this era of Artificial Intelligence and huge online activities, safeguarding sensitive data and protecting personal information is essential in this era. Cyber-attacks can cause the monetary loss as well as reputational loss of the victim organizations. Malware is one type of cyber-attacks; it refers to malicious software that intentionally designed to damage or exploit or harm the data and networks. Detection of malware attacks using traditional based systems will fail to detect new types of variants. This Papers aims to provide ways for malware detection using the machine learning algorithms. Malware Dataset is processed using preprocessing techniques and then machine learning algorithms like Logistic Regression, Ransom Forest, Ada boost will be used to analyse the data and provide high accuracy in classification and detection of malwares. Data Preprocessing techniques and ML algorithms will give significant results as compared to traditional ways.
Keywords
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References
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