Great Deal! Get Instant $10 FREE in Account on First Order + 10% Cashback on Every Order Order Now

1.1P Basic Linux Security SIT719 Security and Privacy Issues in Analytics Pass Task 7.1: Taxonomy of Attacks, Defenses, and Consequences in Adversarial Machine Learning Overview The Information...

1 answer below »
1.1P Basic Linux Security


SIT719 Security and Privacy Issues in Analytics


Pass Task 7.1: Taxonomy of Attacks, Defenses, and
Consequences in Adversarial Machine Learning

Overview

The Information Technology Laboratory (ITL) at the National Institute of Standards and Technology
(NIST) promotes the U.S. economy and public welfare by providing technical leadership for the
Nation’s measurement and standards infrastructure. Recently NIST has published an internal
eport on “A Taxonomy and Terminology of Adversarial Machine Learning” (link below). This NIST
Interagency/Internal Report (NISTIR) is intended as a step toward securing applications of Artificial
Intelligence (AI), especially against adversarial manipulations of Machine Learning (ML), by
developing a taxonomy and terminology of Adversarial Machine Learning (AML).

Link: https:
nvlpubs.nist.gov/nistpubs/i
2019/NIST.IR.8269-draft.pdf

Please see the details of the task in the Task Description section.

This is a Pass task, so you MUST complete the task and submit the evidence of your work to
Ontrack.

Task Description

Suppose you are working in an organization who are developing a report on the vulnerabilities of
machine learning models due to adversarial attacks. Your manager has asked you to provide a
600 word report to submit within the next week. His expectation is that the 600 word report will
cover the attack taxonomies, defense mechanisms and consequences.

Instructions:

1. Read the NIST article from the below link:

https:
nvlpubs.nist.gov/nistpubs/i
2019/NIST.IR.8269-draft.pdf

2. Identify five important attack types. Summarize in approx. 300 words.
https:
nvlpubs.nist.gov/nistpubs/i
2019/NIST.IR.8269-draft.pdf
https:
nvlpubs.nist.gov/nistpubs/i
2019/NIST.IR.8269-draft.pdf



Hint: The above figure demonstrates the attack categories. It has been obtained from Figure
2 of the report.

2. Summarize the defense mechanisms for the attack types you identified in step 1. (Approx.
200 words)


Submit the report PDF to the OnTrack system.
    Overview
    Task Description
Answered Same Day May 27, 2021 SIT719 Deakin University

Solution

Neha answered on May 30 2021
136 Votes
Attacks
When an Oracle attack occurs, an advisory uses an interface for the application programming to present the model which includes the inputs and to observe the output of the model. When the adversary has no direct knowledge about the model then the input output pairing can be obtained from the Oracle attack. It can be used to train a similar model which operates like the targeted model using the transferable property exhibited by multiple model architectures.
The data extraction is mainly related with the input extraction and also known as the model in version for stock in this attack attacker find out the details about the data corpus on which a machine learning model was trained. The research performed in the deep learning mainly focuses on the model for the explosion of the data and the data is very crucial to train the behaviour of the system.
The model extraction is a type of extraction attack on the model itself install when an attacker targets machine learning system which is not complete white box attempt the opening of the box and copy the parameters or behaviour of system. The model extension can...
SOLUTION.PDF

Answer To This Question Is Available To Download

Related Questions & Answers

More Questions »

Submit New Assignment

Copy and Paste Your Assignment Here