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Cybersecurity and Cyber Forensics: Machine Learning Approach Systematic Review
Author(s) -
Ibrahim Goni,
Jerome M. Gumpy,
Timothy Umar Maigari,
Murtala Mohammad
Publication year - 2020
Publication title -
semiconductor science and information devices
Language(s) - English
Resource type - Journals
ISSN - 2661-3212
DOI - 10.30564/ssid.v2i2.2495
Subject(s) - computer security , computer science , data science
The proliferation of cloud computing and internet of things has led to the connectivity of states and nations (developed and developing countries) worldwide in which global network provide platform for the connection. Digital forensics is a field of computer security that uses software applications and standard guidelines which support the extraction of evidences from any computer appliances which are perfectly enough for the court of law to use and make a judgment based on the comprehensiveness, authenticity and objectivity of the information obtained. Cybersecurity is of major concerned to the internet users worldwide due to the recent form of attacks, threat, viruses, intrusion among others going on every day among internet of things. The aim of this work is make a systematic review on the application of machine learning algorithms to cybersecurity and cyber forensics, systematic survey method was used on recent application of machine learning algorithms on cyber forensics and cyber security based on this findings it is observed that cybersecurity is based on confidentiality, integrity and validity of data, it is also noted that there are ten steps to cybersecurity; network security, user education and awareness, malware prevention, removable media control, secure configuration, managing user privileges, incident management, monitoring and home and mobile working and pave away for further research directions on the application of deep learning, computational intelligence, soft computing to cybersecurity and cyber forensics.

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