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The impact of AI on numerous sectors of our society and its successes over the years indicate that it can assist in resolving a variety of complex digital forensics investigative problems. Forensics analysis can make use of machine learning models’ pattern detection and recognition capabilities to uncover hidden evidence in digital artifacts that would have been missed if conducted manually. Numerous works have proposed ways for applying AI to digital forensics; nevertheless, scepticism regarding the opacity of AI has impeded the domain’s adequate formalization and standardization. We present three critical instruments necessary for the development of sound machine-driven digital forensics methodologies in this paper. We cover various methods for evaluating, standardizing, and optimizing techniques applicable to artificial intelligence models used in digital forensics. Additionally, we describe several applications of these instruments in digital forensics, emphasizing their strengths and weaknesses that may be critical to the methods’ admissibility in a judicial process.

The advancement of Information and Communication Technologies (ICT) opens new avenues and ways for cybercriminals to commit crime. The primary goal of this paper is to raise awareness regarding gaps that exist with regards to Nigeria’s capabilities to adequately legislate, investigate and prosecute cases of cybercrimes. The major source of cybercrime legislation in Nigeria is an act of the National Assembly which is majorly a symbolic legislation rather than a full and active legislation. In perusing these avenues of inquiry, the authors seek to identify systemic impediments which hinder law enforcement agencies, prosecutors, and investigators from properly carrying out their duties as expected.

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