MLDED: Multi-layer Data Exfiltration Detection System
| Title | MLDED: Multi-layer Data Exfiltration Detection System |
| Publication Type | Conference Paper |
| Year of Publication | 2015 |
| Authors | Allawi, M. A. A., Hadi, A., Awajan, A. |
| Conference Name | 2015 Fourth International Conference on Cyber Security, Cyber Warfare, and Digital Forensic (CyberSec) |
| Date Published | oct |
| Keywords | Algorithm design and analysis, Communication networks, Complexity theory, Computer crime, computer network security, crime ware services, cryptography, Data Breach, Data Exfiltration, data hiding, data leakage, data leakage threats, data loss, data theft, digital forensics, forensic readiness data exfiltration system, information protection strategy, keyword extraction, keyword labeling, MLDED system, multilayer data exfiltration detection system, organization information system, Organizations, PDF files, plain ASCII text, pubcrawl170109, security, sensitive data exfiltration detection, Standards, Tuning |
| Abstract | Due to the growing advancement of crime ware services, the computer and network security becomes a crucial issue. Detecting sensitive data exfiltration is a principal component of each information protection strategy. In this research, a Multi-Level Data Exfiltration Detection (MLDED) system that can handle different types of insider data leakage threats with staircase difficulty levels and their implications for the organization environment has been proposed, implemented and tested. The proposed system detects exfiltration of data outside an organization information system, where the main goal is to use the detection results of a MLDED system for digital forensic purposes. MLDED system consists of three major levels Hashing, Keywords Extraction and Labeling. However, it is considered only for certain type of documents such as plain ASCII text and PDF files. In response to the challenging issue of identifying insider threats, a forensic readiness data exfiltration system is designed that is capable of detecting and identifying sensitive information leaks. The results show that the proposed system has an overall detection accuracy of 98.93%. |
| DOI | 10.1109/CyberSec.2015.29 |
| Citation Key | allawi_mlded:_2015 |
- forensic readiness data exfiltration system
- tuning
- standards
- sensitive data exfiltration detection
- security
- pubcrawl170109
- plain ASCII text
- PDF files
- Organizations
- organization information system
- multilayer data exfiltration detection system
- MLDED system
- keyword labeling
- keyword extraction
- information protection strategy
- Algorithm design and analysis
- Digital Forensics
- data theft
- data loss
- data leakage threats
- data leakage
- data hiding
- Data Exfiltration
- Data Breach
- Cryptography
- crime ware services
- computer network security
- Computer crime
- Complexity theory
- Communication networks