CITS 3001代写、代写Python/Java编程设计

日期：2022-09-22 06:35

CITS 3001 - 2022

Project: A game on operations in the information environment

Due Date: 13th October

Implementation: Java or Python

Game Scenario

There are four teams involved: Red, Blue, Green and Grey.

The scenario has been deliberately designed to represent the uneven playing field of the

contested environment between the various teams. The scenario highlights the

vulnerabilities of blue team in the contested information environment. The concept of blue

and red teams is prevalent in cybersecurity related serious games or wargames. If you wish

to get some background knowledge about the functioning of teams, you can read this article:

https://csrc.nist.gov/glossary/term/red_team_blue_team_approach. However, this game is

not related to cyber security, rather we are modelling the information environment in a

country.

Red and Blue teams are the major geopolitical players in this fictitious country.

Red team is seeking geopolitical influence over Blue team. Of particular interest to Red team

is influence over Green population and the Government. Blue is seeking to resist the Red

teams growing influence in the country, and promote democratic government in the Green

country.

A key challenge faced by the Blue team, that will become apparent in the exercise, is that

their democratic values are leveraged against them. They are vulnerable to some forms of

manipulation, yet their rules-of-engagement do not allow them to respond in equal measure:

there are key limitations in the ways in which they respond and engage in this unique

battlespace. The Blue team is bound by legal and ethical restraints such as free media,

freedom of expression, freedom of speech.

The Green team lacks a diverse media sector, it is confused and there is a wide range of

foreign news broadcasting agencies Green’s population has subscribed to. The Green

population suffers from poor internet literacy, and the internet literacy can be modelled via

pareto distribution. The government lacks resources to launch a decisive response to foreign

influence operations and a lack of capability to discover, track and disrupt foreign influence

activity.

The Red team, an authoritarian state actor, has a range of instruments, tactics and

techniques in its arsenal to run influence operations. The Green government can block

websites and social media platforms and censor news coverage to its domestic population

whilst maintaining the capability to run sophisticated foreign influence operations through

social media.

The Grey team constitutes foreign actors and their loyalties are not known.

Election day is approaching and the Red team wants to keep people from voting.

Population Model:

An underlying network model that define the probability of nodes interacting with each other.

Majority of the nodes, over 90%, will belong to green team and they depict the population of

the country. A small percentage of nodes will be red, blue and grey. At the beginning grey

nodes are not part of the network.

Each green node/agent has an opinion and an uncertainty associated. In every simulation

round nodes will interact with each other and affect each others’ opinions. The more

uncertain an agent is, the more likely their opinion would change. The probability of

interaction is not uniform across all nodes. Some nodes (for instance those in a household),

may have a higher probability to interact.

How teams are going to take turns:

Teams are going to take turns one by one.

1. Red Team: You need to create function where red team (only 1 agent) is able to

interact with all members of the green team. The agent affects the opinions and

uncertainty of the green team during the interaction. The catch is that you need to

select from 5 levels of potent messaging. If the red team decides to disseminate a

potent message, during the interaction round, the uncertainty variable of the red team

will assume a high value. A highly potent message may result in losing followers i.e.,

as compared to the last round fewer green team members will be able to interact with

the red team agent. However, a potent message may decrease the uncertainity of

opinion among people who are already under the influence of the red team (meaning

they are skeptical about casting a vote). You need to come up with intelligent

equations so that red team improves the certainity of opinion in green agents, but at

the same time does not lose too many green agents. Think of it as a media channel

trying to sell their narrative to people. However, if they may big, claim, lie too much,

they might lose some neutral followers which they could indoctrinate with time.

2. Blue Team: Similarly, blue team can push a counter-narrative and interact with green

team members. However, if they invest too much by interacting with a high certainty,

they lose their “energy level”. If they expend all their energy, the game will end. You

need to model this in way that the game keeps going on while the blue team is

changing the opinion of the green team members. Blue team also has an option to let

a grey agent in the green network. That agent can be thought of as a life line, where

blue team gets another chance of interaction without losing “energy”. However, the

grey agent can be a spy from the red team and in that case, there will be a round of

an inorganic misinformation campaign. In simple words, grey spy can push a potent

message, without making the red team lose followers.