Big Data Analytics Report Writing & Australian Centre for Cyber Security IT Assignment Help

Assignment Task

Providing big data queries using HIVE.
Analytics using Using Built-in (Date, Math, Conditional, and String) HIVE Functions in HIVE.
(10) Visualizing the results of queries into the graphical representations and be able to interpret them.
(15) Analyzing the dataset through statistical analysis methods. Big Data 50 (35) Designing single- and multi-class classifiers and evaluate Analytics using and visualize the accuracy/performance.
Spark Individual 10 (10) (1) Find alternative solutions for high level languages and assessment analytics approaches (use references), and Express findings from big data analytics with the relevant theories.

(1) Understanding Dataset:
dataset was created by the IXIA PerfectStorm tool in the Cyber Range Lab of the Australian Centre for Cyber Security (ACCS) for generating a hybrid of real modern normal activities and synthetic contemporary attack behaviours. Tcpdump tool used to capture 100 GB of the raw traffic (e.g., Pcap files). This data set has nine types of attacks, namely, Fuzzers, Analysis, Backdoors, DoS, Exploits, Generic, Reconnaissance, Shellcode and Worms.

The Argus and Bro-IDS tools are used and twelve algorithms are developed to generate totally 49 features with the class label.
a) The features are described here.
b) The number of attacks and their sub-categories is described here.
c) In this coursework, we use the total number of 10-million records that was stored in the CSV file (download). The total size is about 600MB, which is big enough to employ big data methodologies for analytics. As a big data specialist, firstly, we would like to read and understand its features, then apply modeling techniques. If you want to see a few records of this dataset, you can import it into Hadoop HDFS, then make a Hive query for printing the first 5-10 records for your understanding.
 

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