Main Reference PaperAndroid Malware Detection using Complex-Flows, IEEE Transactions on Mobile Computing, 2018 [Java]
  • To detect the android malware, this work analyzes the information flow that assists in recognizing the existing behavior patterns. By examining the complex-flows in terms of patterns, structure, and relations, it captures the behavior of the malware and benign applications. Moreover, it employs the N-gram method to determine both the unique and common patterns occurred in the Complex-flows.

+ Description
  • To detect the android malware, this work analyzes the information flow that assists in recognizing the existing behavior patterns. By examining the complex-flows in terms of patterns, structure, and relations, it captures the behavior of the malware and benign applications. Moreover, it employs the N-gram method to determine both the unique and common patterns occurred in the Complex-flows.

  • To detect android malware.

  • To analyze the information flow for malware detection.

+ Aim & Objectives
  • To detect android malware.

  • To analyze the information flow for malware detection.

  • This work focuses on employing the feature selection method to extract the N-gram features during the information flow analysis effectively.

+ Contribution
  • This work focuses on employing the feature selection method to extract the N-gram features during the information flow analysis effectively.

  • Operating system: Ubuntu / Windows

  • Language: Java

+ Software Tools & Technologies
  • Operating system: Ubuntu / Windows

  • Language: Java

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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