How AI Quakes the Digital Forensics Landscape

Introduction

Artificial Intelligence (AI) is one of, if not, the fastest growing advancements in technology today. Aligning with this is the ubiquity of AI integrated into our everyday lives. Whether for good or bad, AI is constantly pushing the envelope in cyberspace. Cybercriminals weaponize AI by automating and simplifying hacking processes, making it welcoming for novices and newcomers, increasing the rate of cyberattacks. On the other hand, cybersecurity professionals can leverage AI to bolster security efforts by enhancing threat detection. This article will dive into today’s dangers and benefits of AI, focusing on the cyber forensic environment.

AI enhanced Cybercrime

Cybercrime is a rapidly growing threat, with damages expecting to reach $10.5 million annually by 2025 [1]. This is due in large part to the accessibility of cybercrime services and the sheer speed of AI computerization.  With the help of AI, traditional cyber attacks can now be augmented and amplified to avoid detection, ensure attack completion, increase attack speed, and scale [3]. An example of this is enhanced malware creation, where AI can add edits to existing malware code, increasing its complexity and likelihood to go undetected through security measures. Any existing cybercrime can be upgraded through AI, these include cybercrime(s)-as-a-service, brute force, generated password word lists and with new attacks including deep fakes, which uses generative AI to mimic the likeliness of a human through digital media(s) [7].

Embracing AI in Forensics

The most obvious advantage AI offers to digital forensic investigators is their ability to process information immensely faster than humans. Unlike humans, AI can operate 24/7 without breaks, fatigue, or sleep, enabling processing and analyzing data at speeds no human can match. Leveraging this, the tedious forensics process can drastically be cut short, saving costs and time in an investigation. Whether it be raw data, source code, images, video, or audio, AI can apply their superior data processing and analysis to conduct advanced pattern recognition [2]. This is AI’s ability to detect patterns and anomalies that may have been missed by human analysts, a skill that is crucial for digital forensic experts when investigating cybercrimes. Furthermore, by adopting AI into data analysis efforts, reducing the human element will also reduce human error [1]. A similar implication that AI promotes is cyber threat detection, where AI is implemented into monitoring and logging systems to detect anomalies. Ultimately completing predictive analysis to detect criminal activity within networks or infrastructure [4]. Applying this, investigators and cybersecurity professionals can gain valuable cyber threat intelligence such as, potential cyber threats, adversarial TTP (tactics, techniques, and practices) trends, and other indicators of compromise (IoCs).

An automated effort enabled by AI in the forensic atmosphere is swift and efficient data acquisition. With the boom of Internet of Things (IoT), a diverse range of data devices and types like phones, tablets, cameras, household appliances, and more IoT, could all contain digital evidence [2]. Traditionally, extracting data from all relevant devices can prove to be a cumbersome process, resulting in a high volume of data to be sifted through. By implementing AI into digital forensics, relevant information of a crime can be swiftly extracted from large volumes of data faster than humans. AI is then able to categorize and prioritize the data, encouraging a smooth cyber investigation process.

Challenges and Limitations

Though the time and cost savings are vast, there are several concerns posed by AI that need to be addressed. First, bias should be in question. AI algorithms are based on human-created patterns. Therefore, the data that AI is trained on inherently holds a bias, just as human nature does [4]. As a result, it is imperative that investigators are aware of this and take this into account while adopting specific AI techniques. Second, there are privacy and security concerns through AI data management [1]. Cyber investigations must be conducted securely to avoid any data leakage while adhering to legal and ethical regulations, it is imperative forensic experts are aware of this and comply. Third, digital forensic professionals must avoid relying too much on AI, yielding the idea of “push button forensics” [6]. To combat this, forensic investigators must understand what their data means and where it is coming from because doing so can validate their findings and debunk or eliminate false positives.

Government Application

It is well known that the government can be unhurried when adopting new technologies such as AI compared to the private sector. And for warranted reasons, the challenges posed are budget constraints, skill gaps, legacy systems, and the data handling concerns [8]. Despite this, the federal government has recently integrated AI into cybersecurity efforts. This is evident with DC3 (Department of Defense Cyber Crime Center), establishing a new program that incorporates artificial intelligence and machine learning to aid their analysts in parsing through enormous amounts of sensor data, which sharpen cyber threat and forensic analysis [5].

Conclusion

The ubiquity in AI leaves no surprises that the adoption is happening with both the attackers and the defenders within cyberspace. AI could redefine the digital forensics industry, transforming how digital evidence is being handled and analyzed. The more efficient data processing of AI ultimately enhances the cyber detection and investigation process in an effort to keep up with high volumes of data to investigate and remediate. But, forensic experts must be wary of  the challenges that come with AI application. With now the government starting to assimilate AI, there is no sign of AI dying and the digital forensics field must be equipped and ready for what new implications that AI has to offer.

References

[1] Behl, H. (2024, August 21). From Sci-Fi to Crime-Solving: How AI is Transforming Digital Forensics for Law Enforcement. Exterro. https://www.exterro.com/resources/blog/from-sci-fi-to-crime-solving-how-ai-is-transforming-digital-forensics-for-law-enforcement

[2] EclipseForensics. (2024, September 18). The Role of Artificial Intelligence in Data Forensics. Eclipse Forensics. https://eclipseforensics.com/the-role-of-artificial-intelligence-in-data-forensics/

[3] FBI San Francisco. (2024, May 8). FBI Warns of Increasing Threat of Cyber Criminals Utilizing Artificial Intelligence. FBI. https://www.fbi.gov/contact-us/field-offices/sanfrancisco/news/fbi-warns-of-increasing-threat-of-cyber-criminals-utilizing-artificial-intelligence

[4] Gaona, J. (2024, September 10). The Role of AI in Forensics. Marymount University. https://marymount.edu/blog/the-role-of-ai-in-forensics/

[5] Kluber, A. (2024, October 23). AI Boosts DOD Cyber Crime Center Digital Forensics . GovCIO Media & Research. https://govciomedia.com/ai-boosts-dod-cyber-crime-center-digital-forensics/

[6] Roush, Z. (2024, April 11). Digital Forensics: The Good, the Bad, and the AI-Generated. ACEDS. https://aceds.org/digital-forensics-the-good-the-bad-and-the-ai-generated-aceds-blog/

[7] Sangfor Technologies. (2024, August 13). Defining AI Hacking: The Rise of AI Cyber Attacks. https://www.sangfor.com/blog/cybersecurity/defining-ai-hacking-rise-ai-cyber-attacks

[8] Wheeler, K. (2024, October 1). Why Have Governments Been Slow to Adopt AI?. Technology Magazine. https://technologymagazine.com/ai-and-machine-learning/why-have-governments-been-slow-to-adopt-ai