Machine Learning Approach to Mobile Forensics Framework for Cyber Crime Detection in Nigeria

Author:

Goni Ibrahim,Mohammad Murtala

Abstract

The mobile Cyber Crime detection is challenged by number of mobile devices (internet of things), large and complex data, the size, the velocity, the nature and the complexity of the data and devices has become so high that data mining techniques are no more efficient since they cannot handle Big Data and internet of things. The aim of this research work was to develop a mobile forensics framework for cybercrime detection using machine learning approach. It started when call was detected and this detection is made by machine learning algorithm furthermore intelligent mass media towers and satellite that was proposed in this work has the ability to classified calls whether is a threat or not and send signal directly to Nigerian communication commission (NCC) forensic lab for necessary action. 

Publisher

Bilingual Publishing Co.

Subject

General Medicine

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exploring Deep Learning Architectures for Enhanced Cyber Threat Detection: A Survey;2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG);2024-04-02

2. Exploring the impact of how criminals interact with cyber-networks—a mathematical modeling approach;Research in Mathematics;2024-01-11

3. Research on Feature Extraction Strategies for Cybercrime Crimes Combined with Deep Learning and Their Probabilistic Models;Applied Mathematics and Nonlinear Sciences;2024-01-01

4. EHML: An Efficient Hybrid Machine Learning Model for Cyber Threat Forecasting in CPS;2023 International Conference on Artificial Intelligence and Smart Communication (AISC);2023-01-27

5. A Strategy for Identification and Prevention of Crime using various Classifiers;2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT);2022-10-03

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