K-University-AIED/online_fraud_dataset

Digital Forensic Investigation Scenario Dataset (Online Fraud)

This dataset is a structured collection of digital evidence for research in digital forensics and criminal investigation. It simulates a multi-stage Online Fraud (Voice Phishing) scenario. All metadata and evidence linkages are defined in the accompanying metadata.csv file.

Dataset Structure

The dataset features follow the exact structure of the provided metadata file, ensuring data integrity and consistency for research purposes.

Metadata Features

• sample_id: Unique identifier for each data record.
• file_name: Standardized dataset file name.
• category: Criminal category classification (online_fraud).
• label: Investigative relevance (positive / negative).
• description: Detailed role of the evidence in the investigation scenario.
• source: Data generation origin (synthetic).
• type: Data format or type (e.g., str, int, pdf).

Evidence Inventory

sample_id	file_name	category	label	description	source	type
1	fraud_account_transactions.xlsx	online_fraud	positive	Transaction records of accounts used for fraudulent activities	synthetic	str
2	tel_suspect_call_center_logs.xlsx	online_fraud	negative	Call log data of the suspect	synthetic	str
3	cims_ip_list_101_em515.xlsx	online_fraud	positive	Start and end times of investigation for suspicious PC IP addresses (Log 101)	synthetic	int
4	cims_ip_list_102_em515.xlsx	online_fraud	negative	Start and end times of investigation for suspicious PC IP addresses (Log 102)	synthetic	int
5	cims_ip_list_103_em515.xlsx	online_fraud	positive	Start and end times of investigation for suspicious PC IP addresses (Log 103)	synthetic	int
6	cims_ip_list_104_em515.xlsx	online_fraud	negative	Start and end times of investigation for suspicious PC IP addresses (Log 104)	synthetic	int
7	cims_ip_list_105_em515.xlsx	online_fraud	positive	Start and end times of investigation for suspicious PC IP addresses (Log 105)	synthetic	int
8	suspect_phone_call_and_data_usage.xlsx	online_fraud	positive	Communication logs for the suspicious number (010-8457-3455)	synthetic	str
9	secondary_account_atm_withdrawals.xlsx	online_fraud	positive	ATM location information for cash withdrawals from the crime-related account	synthetic	str
10	suspect_phone_call_locations.xlsx	online_fraud	positive	Outgoing call location information for the suspicious number (010-8457-3455)	synthetic	str
11	phone_atm_location_matching_results.xlsx	online_fraud	positive	Matching results between the suspicious number's location and ATM withdrawal location	synthetic	str
12	phone_atm_location_matching_map.html	online_fraud	positive	Map visualization of matching results between the suspicious number and ATM location	synthetic	str
13	realtime_sms_logs.txt	online_fraud	positive	Outgoing SMS location information of the suspect	synthetic	str
14	fault_tracker_user_manual.pdf	online_fraud	negative	User manual for the location tracking program (PoleTracker)	synthetic	pdf
15	google_cloud_access_logs.xlsx	online_fraud	positive	Google Cloud access logs categorized by phone number	synthetic	str
16	money_mule_telegram_analysis.xlsx	online_fraud	positive	Telegram chat logs of the cash-out agent containing criminal instructions	synthetic	str

Project Information

This dataset is a result of the Glocal University 30 Project, supported by the Ministry of Education and the National Research Foundation of Korea. It was developed at the Hallym Intelligent Social Safety Research Lab.

• Project ID: GLOCAL-202407990001
• Contact: shha@hallym.ac.kr

License

Distributed under the CC BY NC ND 4.0 license.

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디지털 포렌식 수사 시나리오 데이터셋 (Online Fraud)

소개

본 데이터셋은 가상의 온라인 사기 사건을 수사하는 과정을 재구성한 연구용 데이터입니다. 업로드된 metadata.csv의 규격에 따라 모든 데이터 파일이 정의되어 있으며, 수사적 유의미성(label)과 데이터 형식(type)을 실제 메타데이터와 1:1로 매칭하여 관리합니다.

데이터 명세

제공해주신 metadata.csv의 컬럼 구조를 그대로 반영하였습니다.

• sample_id: 데이터 고유 식별 번호
• file_name: 표준 영문 파일명
• category: 범죄 분류 (online_fraud)
• label: 수사 유의미성 (positive: 핵심 증거, negative: 참고용 데이터)
• description: 시나리오 내 해당 파일의 수사적 의미 및 역할 (영문 설명)
• source: 데이터 생성 출처 (synthetic)
• type: 데이터 기술 형식 (str, int, pdf 등)

라이선스

본 데이터셋은 CC BY NC ND 4.0 라이선스를 따릅니다. 출처 명시 시 비영리 목적의 교육 및 연구 용도로 사용 가능합니다.

소속: 한림대학교 지능형사회안전연구소 (Hallym Intelligent Social Safety Research Lab)