INNOVATIONS IN CYBERSECURITY FOR CRIME INVESTIGATIONS: ADVANCED DATA ENGINEERING AND AI-DRIVEN THREAT DETECTION
Keywords:
Cybersecurity, Cybercrime, Data Engineering, Machine Learning, Artificial IntelligenceAbstract
Data engineering and machine learning may improve cybersecurity in criminal investigations. Cybercrime development requires a criminal investigative paradigm change. The amount and complexity of digital data overwhelm traditional approaches, leaving evidence in the digital shadows. This article examines cutting-edge criminal investigation cybersecurity. It uses modern data engineering, machine learning, and AI to identify cyber dangers in criminal data. Combining these tools will protect criminal investigations from growing cyber dangers. To reveal criminal data insights, we use data wrangling, feature engineering, and distributed computing. Meanwhile, we examine how machine learning and AI algorithms might help cybercrime investigators discover and mitigate threats early. Analysing case studies and demonstrating the usefulness of various tools, we show how this integrated strategy helps investigators to traverse the digital terrain with better accuracy and efficiency, improving criminal investigations.
References
International Association of Chiefs of Police, “Cybercrime Investigations - Law Enforcement Cyber Center,” Law Enforcement Cyber Center, 2015. [Online]. Available: https://www.iacpcybercenter.org/officers/cyber-crime-investigations/
www.linkedin.com. “Steps for Conducting Cyber Crime - Computer Forensics Investigations,” [Online]. Available: https://www.linkedin.com/pulse/steps-conducting-cyber-crime-computer-forensics-aaftab-mohammed
“Cybercrime Module 4 Key Issues: Standards and best practices for digital forensics,”. [Online]. Available: https://sherloc.unodc.org/cld/en/education/tertiary/cybercrime/module-4/key-issues/standards-and-best-practices-for-digital-forensics.html
“Cybercrime Investigation,” DIGITPOL. [Online]. Available: https://digitpol.com/cybercrime-investigation/
www.linkedin.com. “The Intersection of Cybersecurity and Data Engineering: Protecting Sensitive Information in the Digital Age,” [Online]. Available: https://www.linkedin.com/pulse/intersection-cybersecurity-data-engineering- sensitive-van-der-merwe
IABAC®, “Data Engineering for Cybersecurity: Analyzing and Protecting Data from Threats,” IABAC®, Aug. 07, 2023. [Online]. Available: https://iabac.org/blog/data-engineering-for-cybersecurity-analyzing-and-protecting-data-from-threats
insights.sei.cmu.edu. “CERT Applied Data Science for Cybersecurity Professional Certificate,” [Online]. Available: https://insights.sei.cmu.edu/credentials/cert-applied-data-science-for-cybersecurity-professional-certificate/
www.darktrace.com. “World-Leading AI for Cyber Security,” [Online]. Available: https://www.darktrace.com/en/
crowdstrike.com. CrowdStrike, “CrowdStrike: We stop breaches,” [Online]. Available: https://www.crowdstrike.com/
M. K, “Artificial Intelligence & Machine Learning in Cyber Security,” Alpha, Nov. 09, 2023. [Online]. Available: https://www.aalpha.net/articles/artificial-intelligence-and-machine-learning-in-cyber-security/
datasciencedojo.com. “AI in Cybersecurity: Revolutionizing threat detection and defense | Data Science Dojo,” [Online]. Available: https://datasciencedojo.com/blog/ai-in-cybersecurity/
www.linkedin.com. “Leverage AI and machine learning in threat detection,” [Online]. Available: https://www.linkedin.com/pulse/leverage-ai-machine-learning-threat-detection-getoppos
www.linkedin.com. “How can Machine Learning (ML) and Artificial Intelligence (AI) be used to prevent cyber-attacks?” [Online]. Available: https://www.linkedin.com/pulse/how-can-machine-learning-ml-artificial-intelligence-ai-jet-l%C3%BC
crowdstrike.com. L. Stanham, “Machine Learning in Cybersecurity: Benefits and Use Cases | CrowdStrike,”, Nov. 03, 2023. [Online]. Available: https://www.crowdstrike.com/cybersecurity-101/machine-learning-cybersecurity/
www.linkedin.com. “Empowering the Future: The Synergy of Data Engineering and AI Engineering,” [Online]. Available: https://www.linkedin.com/pulse/empowering-future-synergy-data-engineering-ai-ravi-mannepalli-jffxc
“Revolutionizing law enforcement data analytics with advanced AI,” Police1. [Online]. Available: https://www.police1.com/police-products/investigation/investigative-software/articles/revolutionizing-law-enforcement-data-analytics-with-advanced-ai-rRpAEaXQe7Cp7iS3/
insights.sei.cmu.edu. “Synergy Among Engineering Disciplines: Software, Cybersecurity, and AI,” Sep. 11, 2023. [Online]. Available: https://insights.sei.cmu.edu/blog/synergy-among-engineering-disciplines-software-cybersecurity-and-ai/
Y. Bao, W. Gong, and K. Yang, “A Literature Review of Human–AI Synergy in Decision Making: From the Perspective of Affordance Actualization Theory,” Systems, vol. 11, no. 9, pp. 442–442, Aug. 2023, [Online]. Available: https://doi.org/10.3390/systems11090442.
P. Bisconti et al., “Maximizing team synergy in AI-related interdisciplinary groups: an interdisciplinary-by-design iterative methodology,” AI & society, Jun. 2022, [Online]. Available: https://doi.org/10.1007/s00146-022-01518-8.
Cyber Talents, “Cybercrime Investigation Tools and Techniques You Must Know!” Cyber Talents Blog, 2023. [Online]. Available: https://cybertalents.com/blog/cyber-crime-investigation
www.secretservice.gov. United States Secret Service, “Cyber Investigations | United States Secret Service,” [Online]. Available: https://www.secretservice.gov/investigation/cyber
FBI, “Cyber Crime | Federal Bureau of Investigation,” Federal Bureau of Investigation, 2023. [Online]. Available: https://www.fbi.gov/investigate/cyber
www.sans.org. “Cybersecurity Investigation | Nice Framework | SANS Institute,” [Online]. Available: https://www.sans.org/nice-framework/investigate/
B. Schneier, J. Kelsey, D. Whiting, D. Wagner, C. Hall, and N. Ferguson, The Two fish Encryption Algorithm. John Wiley & Sons, 1999.
E. Barker and W. C. Barker, “Title: Recommendation for Key Management-Part 2: Best Practices for Key Management Organizations,” 2018. [Online]. Available: https://csrc.nist.gov/CSRC/media/Publications/sp/800-57-part-2/rev-1/draft/documents/sp800-57pt2-r1-draft.pdf
E. Rescorla and T. Dierks, “The Transport Layer Security (TLS) Protocol Version 1.2,” IETF, Aug. 01, 2008. [Online]. Available: https://datatracker.ietf.org/doc/html/rfc5246
A. Menezes, Paul Van Oorschot, and S. Vanstone, Handbook of Applied Cryptography. CRC Press, 1996.
D. R. Stinson, Cryptography: theory and practice. Boca Raton: Chapman & Hall/CRC, 2006.
A. Ometov, S. Bezzateev, N. Mäkitalo, S. Andreev, T. Mikkonen, and Y. Koucheryavy, “Multi-Factor Authentication: A Survey,” Cryptography, vol. 2, no. 1, p. 1, Jan. 2018, [Online]. Available: https://doi.org/10.3390/cryptography2010001.
R. S. Sandhu, “Role-based Access Control,” Advances in Computers, pp. 237–286, 1998, [Online]. Available: https://doi.org/10.1016/s0065-2458(08)60206-5
“Cybersecurity Research – Gartner,” Gartner, 2019. [Online]. Available: https://www.gartner.com/en/information-technology/insights/cybersecurity
Google.com, 2024. “Redirect Notice,” [Online]. Available: https://www.google.com/url?sa=i&url=https%3A%2F%2Fwww.collidu.com%2Fpresentation-cybersecurity-engineer&psig=AOvVaw1i1HpJ6ZIv7pvri6yWv1Y-&ust=1704628458268000&source=images&cd=vfe&opi=89978449&ved=0CBUQjhxqFwoTCIjQtIDayIMDFQAAAAAdAAAAABAD
www.xenonstack.com. “Artificial Intelligence in Cyber Security | The Advanced Guide,” [Online]. Available: https://www.xenonstack.com/blog/artificial-intelligence-cyber-security
