We then explain how graph databases can be used to analyze network log files in near-real time within a network security-monitoring environment. To facilitate the evaluation of our proposed approach, we use the Zeek network security monitor system to produce log files from monitored network traffic in real-time. Specifically, we posit the importance of constantly monitoring log files for new entries for immediate processed and analysis, and their results imported into the graph database. Hence, in this paper, we propose a new approach to analyze network log files, by using the graph database. importing a fixed amount of log data for subsequent analysis). In recent years, there has been a trend of using graph databases to manage data for semantic queries (e.g. We can use relational databases to establish these relationships, for example using complex database queries involving multiple join operations to link the tables. While using a log management system allows for searching across different log files, the relationship(s) between different network activities may not be easy to establish from the analysis of these different log files. For example, using command line tools, any log file can be reviewed only in isolation. Network log files from different sources often need to be analyzed in order to facilitate a more accurate assessment of the cyber threat severity. Moreover, two threshold value used and data preprocessing in that experiment affected amount and quality of the generated rules. Our experiment showed that Coro was able to cluster around 5000 request in a short time and our graph clustering was a big help to that. Coro focuses on HTTP, as it will be used to harden our e-voting system, but it is possible to be extended to other protocols. Coro uses graph clustering that make it be able to cluster data without the need to recompute the centroid. We proposed Coro, an IDS signature generator that create an IDS rules based on honeypot log data. Secondly, zero-day attack, attack that has never been happened before, is the main weakness of this IDS due to absence of its signature. Yet there are two problems with this kind of IDS, first, not all people are able to create a signature or rule, therefore they need to wait for updates if they want to renew their database. You can color-code each parent node for better clarity to easily trace how ideas are related to each other.Attacks on computer network are increasing everyday and most institution use Intrusion Detection System (IDS) to cope with that and most used IDS is the signature-based IDS, which need a database of rules when looking for an malicious packet.Link the concepts together with arrows - make sure to add linking words or phrases to explain how concepts are related.Begin to draw the map keeping the focus question at the center and the related topics branching out from it.Create a ‘parking lot’ of ideas- which is a list of related topics that are ranked from the most specific to the most general concepts. Now identify all the key concepts that are related to this focus question.Begin by identifying the focus question- which is the problem your concept map is trying to solve.Creately’s concept map maker provides a collaborative workspace that is perfect for creating concept maps in any collective group session. First, select the right platform to create a concept map, you need a space where you can easily move ideas around and reorganize concepts.Concepts or ideas are represented by nodes- usually in circles or boxes and relationships are represented by arrows that connect the ideas together. A concept map is a visual tool that represents how ideas and concepts are related to each other.
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