When Star Trek gave us a glimpse of the future with the Universal Translator it seemed like a far-off science-fiction. However, newer features of mobile operating systems have made this more science-fact.
There’s a moment that shows up in almost every investigation; the quiet realization that you’re about to reach for one more tool. Not because you want to. Not because the tools you already have failed. But because the evidence in front of you doesn’t quite fit the workflows you’re holding. Maybe it’s a cloud artifact that didn’t exist the last time you worked a similar case. Maybe mobile data has crept into what used to be a clean-cut investigation. Maybe the logs exist, but only if you know exactly where and how to extract them.
Both iOS and Android are known to keep multiple copies of certain data, but the reason why isn’t always the same. Not all copies are created equal! In this episode of Mobile Unpacked, we will explore why data gets duplicated across both iOS and Android and how those duplicates can be ignored or crucial to your investigation.
Mobile devices are indispensable tools in the modern workplace. The vast amount of data stored on these devices makes them invaluable sources of evidence in digital forensics investigations.
Digital forensic investigators face extreme pressure to deliver accurate results. The stakes in the field are especially high; an error could mean overlooking potential suspects or missing exculpatory evidence . That’s why the use of artificial intelligence in the field isn’t without controversy. Broader societal concerns around the “hallucinations” and inconsistent results produced by generative AI have raised questions about the use of AI in digital forensic investigations.
The proliferation of digital data and connected devices has had a profound impact on forensic investigations, straining laboratory resources, pressuring budget-conscious jurisdictions to spend more on technology, and worsening evidence backlogs.
There appears to be a growing tension in digital forensics around artificial intelligence. On one side are people excited by what AI can already do—surface patterns at scale, accelerate triage, highlight anomalies no human would realistically find. On the other side are voices urging extreme caution or outright prohibition, often framed as a need to “protect the human element.”
AI adoption is accelerating. Cyber incidents continue to dominate workloads. Mobile evidence is harder to access than ever. And investigative toolkits are growing—often faster than teams can integrate them. The result? A DFIR landscape that’s more powerful, more complex, and under increasing pressure.
Based on findings from the 2026 State of Enterprise DFIR Report, this webinar breaks down the realities facing modern investigation teams and the strategic shifts underway across the private sector.
We’ll unpack the four defining trends shaping enterprise DFIR today:
The dual impact of AI as both a force multiplier and a threat vector,
Why real-time collaboration has become a critical driver of SaaS adoption,
The increasing complexity of mobile evidence, and
The operational pressure created by fragmented investigative tools.
Backed by survey data from private sector DFIR professionals, we’ll examine what’s changing, why it matters now, and how organizations can prepare their teams to investigate with confidence in 2026 and beyond.
Join us for this panel discussion with some of the expert contributors from the report.
Your organization is coming across more advanced digital investigations than ever, and the time has come to either launch your own digital forensics lab or level up your existing one.
모바일 기기 포렌식에서 사용되는 추출 방식은 Full File System과Logical두 가지로 나뉩니다. iOS 및 Android 기기의 활용이 법 집행기관 수사와 기업 조사 전반으로 확대되면서, 두 방식의 차이를 이해하는 것이 더욱 중요해지고 있습니다.
