Analysis Techniques - Static and Dynamic Analysis - Cyber Security and Analytics - Engineering Assignment Help

Assignment Task :

Section 1  

Q1. : To understand the working and the characteristics of malware and to assess its impact on the system, you will often use different analysis techniques. The following is the classification of these analysis techniques: Static analysis, Dynamic analysis (Behavioral Analysis), Code analysis and Memory analysis (Memory forensics). Static analysis defined: This is the process of analyzing a binary without executing it. It is the easiest kind of analysis to perform and allows you to extract the metadata associated with the suspect binary. Static analysis might not reveal all the required information, but it can sometimes provide interesting information that helps in determining where to focus your subsequent analysis efforts. Now, you have to define and evaluate Dynamic analysis (Behavioral Analysis), Code analysis and Memory analysis (Memory forensics) in regards to Advanced Malware Analysis. 

Q2. Demonstrate the use of CRUNCH tool to create a Wordlist file to generate a minimum and maximum word length (2-9) based on your MIT ID and the first seven numbers and two unique special characters, and store the result in file pass.txt. Give an exampleof two generated passwords with length of three characters, one number and one special character. After that, use the HYDRA attacking tool to attack ftp://192.168.1.3 server which has the username ‘tom’ and password length between 2 and 9, generated by CRUNCH in the previous step.

Q3. Consider the following Play Tennis dataset Table 1 (adapted from: Quinlan, “Induction of Decision Trees”, Machine Learning, 1986). From this given 14 instances in Table 1, showing the mapping between X and Y (which machine learning always does). 

The decision tree takes the training set and splits it into the smaller subsets based on features. 

We repeat this procedure at every node of a tree with different subsets and attributes till there is no uncertainty that Min will play or not. 

i) Which of the major machine learning categories (supervised, unsupervised, or reinforcement) does this problem fall under? Justify your answer. [3 Marks] 

ii) Draw the relevant decision trees using divide and conquer method to predict whether the Min will play tennis or not based on new feature vector (X).

iii) Build the Naive Bayes model from the dataset given in Table 1. Remember that 1 is added to all the counts to avoid the problem of having a probability that is equal to 0. 

Q4. Justify the statement “Spam detection is perhaps the classic example of pattern recognition”.  

Q5. The implication of current arrangements is that end-users carry a significant portion of the risk, and Government has a limited role in protecting a large number of systems critical to our way of life. Whether these outcomes are correct is one of the most fundamental questions we need to explore. Who is responsible for managing cyber risks in the economy? 

Q6. Compare and contrast cyber security policy of Victorian and NSW governments? Propose your cyber security policy for the Victorian Government that they may follow? 

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