Methodology for Detecting Advanced Persistent Threats in Oracle Databases

Towards an Operational Semantic Theory of Cyber Defense Against Advanced Persistent Threats

This paper presents current work on developing an operational semantic theory of cyber defense against advanced persistent threats (APTs), which is grounded in cyber threat analytics, science of evidence, knowledge engineering, and machine learning. After introducing advanced persistent threats, it overviews a systematic APT detection framework and the corresponding APT detection models, the fo...

Anomaly Detection in Log Data using Graph Databases and Machine Learning to Defend Advanced Persistent Threats

Advanced Persistent Threats (APTs) are a main impendence in cyber security of computer networks. In 2015, a successful breach remains undetected 146 days on average, reported by [Fi16]. With our work we demonstrate a feasible and fast way to analyse real world log data to detect breaches or breach attempts. By adapting well-known kill chain mechanisms and a combine of a time series database and...

Accessing multidimensional Data Types in Oracle 9i Release 2

In former Releases of the Oracle Database, multidimensional data types did not exist. In typical Warehouse situations, especially if more advanced analytics was needed, an additional database had to be chosen to store and analyze the data. These databases offered a lot functionality for advanced analytics like what-if analysis, statistical queries and so on and an excellent query performance du...

Defending Against Advanced Persistent Threats

Enhancing Network Intrusion Detection through Host Clustering

The state-of-the-art in intrusion detection mainly relies on signature-based techniques. Although signature-based detection is an efficient way of protecting against known threats, it will not protect against new, advanced intrusions such as Advanced Persistent Threats (APTs). Moreover, many intrusion detection systems only monitor the network traffic crossing the external border of a network, ...