Digital Forensics in Cybersecurity

References

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@article{1706783,
      author = {Shola Erinfolami , Ogechukwu Scholastica Onyenaucheya , Adekola Adams, Olayinka Esther Abudu},
      title = {Digital Forensics in Cybersecurity},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {6},
      pages = {756-761},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706783.pdf},
      abstract = {Background of the Study: The digital era has revolutionized information access, transmission, and storage, leading to a surge in cybercrimes. This necessitates robust mechanisms for investigating and mitigating such incidents, positioning digital forensics as a cornerstone of modern cybersecurity.
Purpose: This research aims to investigate how artificial intelligence (AI), and machine learning (ML) can be incorporated into digital forensic processes to improve the accuracy and efficiency of cybercrime inquiries. Design/Methodology/Approach: An extensive review of relevant literature was carried out to examine current trends and progress in digital forensics, artificial intelligence, and machine learning. The research also investigates collaboration between different disciplines and ongoing professional development in the field.
Findings: The incorporation of AI and ML in digital forensics enhances the effectiveness and precision of investigations through the automation of data analysis and detection of patterns associated with malicious behavior. Working together across different fields, such as cybersecurity, law enforcement, legal professionals, and behavioral scientists, improves how cyber threats are understood and reduced. Professionals must participate in continuous training programs to keep abreast of evolving technologies and emerging threats. Thorough legal systems guarantee that digital evidence can be used in court while protecting the privacy rights of individuals. Continual research and development are essential in the creation of new forensic tools to tackle issues brought about by advancing technologies such as cloud computing and the Internet of Things (IoT).
Research Limitations/ Implications: This study relies on current literature and may not cover recent technological developments. Future studies should prioritize conducting empirical research to confirm the efficiency of integrating AI and ML in digital forensics.
Practical and Social Implications: Utilizing AI and ML in digital forensics can result in stronger and more effective responses to cyber threats, ultimately improving organizational security and safeguarding societal interests.
Originality/Value: The research offers a broad perspective on the incorporation of AI and ML in digital forensics, emphasizing the significance of multidisciplinary teamwork, ongoing skills enhancement, and thorough legal structures.},
      keywords = {AI, Collaborative Interdisciplinary Work, Cybersecurity, Digital Forensics, Legal Regulations, ML, Ongoing Professional Growth.},
      month = {December},
  }