diff --git a/AI4Forensics/CKIM2024/CIKM2024_PPTs.pdf b/AI4Forensics/CKIM2024/CIKM2024_PPTs.pdf new file mode 100644 index 0000000..55bfe60 Binary files /dev/null and b/AI4Forensics/CKIM2024/CIKM2024_PPTs.pdf differ diff --git a/AI4Forensics/CKIM2024/readme.md b/AI4Forensics/CKIM2024/readme.md index b2625b3..b445a25 100644 --- a/AI4Forensics/CKIM2024/readme.md +++ b/AI4Forensics/CKIM2024/readme.md @@ -27,7 +27,7 @@ By fostering a collaborative learning environment, this tutorial aims to empower --- -## Table of Contents +## Table of Contents [PPT](CIKM2024_PPTs.pdf) - Introduction - [Forensic evidence entity recognition (hands-on lab)](#forensic-evidence-analysis) @@ -46,9 +46,9 @@ By fostering a collaborative learning environment, this tutorial aims to empower ### Forensic Evidence Analysis -The cyber incident report documents a conversation between an IT Security Specialist and an Employee about an email phishing attack. We use LLMs to identify evidence entities and relationships and to construct digital forensic knowledge graphs. +The [Cyber incident report](PhishingAttack/PhishingAttackScenarioDemo/conversation.txt) documents a conversation between an IT Security Specialist and an Employee about an email phishing attack. We use LLMs to identify evidence entities and relationships and to construct digital forensic knowledge graphs. -Here is an example of a reconstructed digital forensics knowledge graph: +Here is an example of a reconstructed digital forensics knowledge graph using an LLM only: