How Putin Ends: A United Front

火炎焱燚Bridge, Ferry, Jets, Oil: it all Burns.

May 31, 2024

Contents: United Front, Word of the Day, News, Analysis (Cryptography), Videos, Learn Chinese, Free eBooks!. Trump is a criminal.

A United Front Against Putin

The geopolitical landscape of the 21st century presents numerous challenges and opportunities for major world powers. Among these, the ability to intercept and decrypt foreign communications is crucial for national security. The United States and China, despite their differences, have a unique opportunity to join forces against a common threat: Russian cipher traffic. There are also compelling reasons to do so. By working together, the USA and China can address shared security concerns, foster a more stable global order, and reap significant benefits.

Common Enemies, Common Goals

Both the United States and China face significant threats from a resurgent Russia, whose strategic ambitions, military activities and aggressive expansionism have destabilized various regions, especially Eastern Europe and parts of Asia. The interception and decryption of Russian communications can provide vital intelligence on Moscow’s intentions, capabilities, and potential threats. By pooling resources and expertise, the U.S. and China can gain vital insights into Moscow's intentions, capabilities, and threats to preempt potential conflicts that would spill over into their respective spheres of influence.

Tech Titans Unite!

The US and China possess complementary technological strengths that can be leveraged to enhance their signals intelligence (SIGINT) capabilities. The US has a long history of excellence in cryptographic analysis and cyber operations, while China has made rapid strides in artificial intelligence. By combining their strengths, they can accelerate the decryption process and overcome technical challenges that might be insurmountable alone.

Economic Interests Align

Economic stability is a top priority for both nations, and Russian cyberattacks on financial institutions and infrastructure pose a direct threat to global economic stability. By intercepting and decrypting Russian communications, the US and China can preempt and mitigate these threats. Furthermore, cooperation in SIGINT can reduce the economic burden on each nation by sharing the costs associated with advanced cryptographic research and operational deployment.

Diplomatic Dividends

Joint efforts in SIGINT can serve as a powerful diplomatic tool, fostering a more constructive bilateral relationship between the US and China. This cooperation can lay the groundwork for broader diplomatic engagements, reducing tensions in areas like trade, territorial disputes, and human rights issues. Moreover, possessing detailed intelligence on Russian activities enhances both nations' leverage in negotiations with Moscow, allowing them to better manage and counter Russian influence globally.

A United Front for a Safer World

In conclusion, the strategic imperatives for the US and China to cooperate in intercepting and decrypting Russian cipher traffic are clear and compelling. By working together, they can enhance their own national security, contribute to a more stable and secure global environment, and reap significant economic and diplomatic benefits. This cooperative endeavor, grounded in mutual respect and common goals, represents a pragmatic approach to addressing one of the most pressing security challenges of our time.

Word of the Day: 东方 (dong fang), east (lit. eastern quarter), l'est (Fr.), Osten (Ger.), Vostok (n.) Vostochniy (adj.) (Ru., Slav)

News:

I omitted “war crimes tribunal” because I expect he will not survive the forces he himself unleashed. Lies and murder lead where exactly? Oh. See supra.

Ukraines-atacms-rockets-are-severing-russian-supply-lines-into-crimea-but-the-last-line-is-the-toughest

https://fakty.com.ua/ru/svit/20240531-vybuhy-v-portu-kavkaz-ta-pozhezha-na-naftobazi-31-travnya-2024-detali/ It. All. Burns. This is what happens to would-be imperialists.

https://www.wsj.com/world/europe/frances-macron-readies-plan-to-send-military-instructors-to-ukraine-e1d5742a

https://www.newsweek.com/putin-facing-another-coup-what-we-know-1906387

fanyi.baidu.com translate.google.com

The left part dong东 is a shorthand that depicts the sun 日 rising behind a tree 木. The second character 方fang may indicate a man in cangue (Chinese stocks) or perhaps a flag bearer. n any case it is a picture of a man standing (dot on top is his head), representing the idea of square, squared away, for the stocks are square as is a flag.

Introduction

In earlier posts I talked about the Maoist concept of Unity in Conflict. That idea still shapes and influence the contemporary Chinese Communist Party, and explains why China simultaneously acts assertively in some fields, confrontationally, yet in other areas is cooperative.

Here, I want to examine a practical real-world problem in cryptography that illustrates the idea of unity-in-conflict. This is particularly interesting because it is an example of a Cooperative Multi-Player Zero Sum Game with Imperfect Information and No Random Elements.

The following cryptography problem is also an example of the concept of unity-in-conflict. Namely, it is a cooperative-competitive game with dynamic matrices. I limit the game theory model to its cryptography aspects. I may discuss cooperative-competitive dynamic sum game theory in greater detail in a later post, with frther real world examples. That would almost certainly look at multiplayer game with imperfect information but no random elements.

GIVEN:

Let us suppose the following cryptography problem, and then analyze it politically, with game theory, and mathematics.

You and I both want to decipher Russia's encrypted messages. In other words, we both want to read all of Russia's mail. You are China. I am america. You and I also want to read each others.. Neither of us want the other to read our own mail. Neither of us want Russia to read our mail.

How can You and I cooperate to solve our Russia problem?

Pragmatic Analysis:

First, lets state the problem a bit more exactly to get a better overview of the problem and implications. Sometimes using formal language allows us to get a clearer head, thinking more logically and less emotionally,. The scenario described involves three entities: the United States (USA), China, and Russia (A, B, and C). The primary goal of each entity is to access the communications (referred to as "mail") of the other entities while maintaining the confidentiality of its own communications. The objectives and constraints are as follows:

Objectives:

1. The USA and China both aim to intercept and read Russia's communications.

2. The USA and China also seek to intercept and read each other's communications.

Constraints:

1. The USA does not want its communications to be intercepted by either China or Russia.

2. China does not want its communications to be intercepted by either the USA or Russia.

3. Russia does not want its communications to be intercepted by either the USA or China.

Practical Analysis:

1. Intercepting Russia's Communications:

- Both the USA and China will deploy intelligence assets and techniques (such as cyber-espionage, signal interception, and human intelligence) to monitor Russia's communications.

- There may be competition or cooperation between the USA and China in this effort, depending on their strategic interests.

2. Intercepting Each Other's Communications:

- The USA and China will also focus on intercepting each other's communications, employing similar intelligence methods.

- Both nations will invest in advanced cryptographic measures and secure communication channels to protect their own information from being intercepted.

3. Preventing Interception:

- Each entity will enhance its cybersecurity infrastructure, use encryption, and adopt secure communication protocols to prevent unauthorized access to its communications.

- Diplomatic and military strategies may be employed to deter adversaries from engaging in espionage activities.

Strategic Considerations:

1. Technological Capabilities:

- Each nation's technological prowess in cyber capabilities will significantly impact its ability to intercept communications and protect its own.

- Continuous advancements in encryption and cyber defense mechanisms are critical.

2. International Relations:

- The geopolitical dynamics between the USA, China, and Russia influence the intensity and nature of their espionage activities.

- Alliances and rivalries play a crucial role in determining the extent of cooperation or conflict in intelligence operations.

3. Risk Management:

- Each entity must balance the benefits of obtaining intelligence against the risks of exposure and retaliation.

- Operational security and plausible deniability are essential to mitigate the consequences of being discovered.

What end state would this sitaution yield? That depends on the starting positions of each of them and their differing goal. But, if the USA and China each want to be able to read all of Russian cipher traffic then they are both in a better position if they cooperate in that endeavour. Furthermore, under given constraints this problem yields with all Russian cipher traffic being broken and readable by at least one of them and, with perfect play, both of them.

Cooperation

We can understand how A and B might cooperate by looking at the problem using cooperative game theory, which focuses on the joint actions of players to achieve a common goal.

A and B must form a coalition to achieve their cooperative goal, which involves negotiating the terms of their partnership. A and B must identify a core solution, which represents the set of feasible outcomes that satisfy both parties' interests. To facilitate cooperation, A and B must design mechanisms that align their incentives and promote mutual trust. Thus, A and B must also design mechanisms that are incentive-compatible, meaning that each party's self-interest is aligned with the cooperative goal and that encourage eaches of them to reveal the truth to the other regarding their true intentions, capabilities, and intelligence. A and B must also establish punishment mechanisms to deter defection and ensure cooperation, in other words to prevent either of them from “cheating”.

A and B have a recent history of distrust, making it challenging for them to collaborate. However, they share a common goal: to decipher C's transmissions. C, being their common adversary, has created an opportunity for A and B to put aside their differences and work together.

Establishing a Framework for Cooperative Deciphering

To initiate cooperation, A and B must establish a framework that addresses their mutual distrust. A and B must define clear goals and objectives for their cooperation, focusing on deciphering C's transmissions and sharing the resulting intelligence. A and B then engage in cooperative deciphering efforts, leveraging their individual expertise and resources to crack C's codes. Despite their mutual distrust, A and B can cooperate to decipher C's transmissions by establishing a framework for cooperation, engaging in cooperative deciphering, and implementing mutual verification and validation mechanisms. By incentivizing cooperation and sharing the benefits of their joint effort, A and B can overcome their differences and achieve common goals, ultimately strengthening their position against.

Game Theory

The A B C scenario can be analyzed using concepts from game theory, particularly focusing on strategies and payoffs in a multi-player, non-cooperative game. Multi-player Cooperative-Competitive game theory is one of the less researched but more important aspects of game theory because it better reflects most real world interactions, especially international interactions. Many international relations problems can be effectively cast as competitive-cooperative and also are multiplayer. Here’s a detailed breakdown of the game:

Players:

1. United States (USA)

2. China

3. Russia

Objectives:

- USA wants to read China's and Russia's mail.

- China wants to read USA's and Russia's mail.

- Neither wants their own mail to be read by the other or by Russia.

- Russia wants to read USA's and China's mail but is not the primary focus in this analysis.

For Russia, this is a Zero-Sum Game: one nation's gain (successful interception) is another nation's loss (compromised communication).

Lets assign decrypts and known plain texts to each of the players. Denote the number of DKRP tokens owned by player X (where X is A, B, or C) as DKRP(X), and similarly, the number of KPTXT tokens owned by player X as KPTXT(X).

The end state of the game is when all of C's DKRP and KPTXT tokens are owned by A, B, or both A and B.

Initially, the tokens are distributed as follows:

- A: DKRP(A) = 7, KPTXT(A) = 3, DKRP(B) = 2, KPTXT(B) = 1

- B: DKRP(B) = 3, KPTXT(B) = 8, DKRP(A) = 1, KPTXT(A) = 10

- C: DKRP(C) = 20, KPTXT(C) = 20

Players can negotiate and exchange tokens among themselves. They may also lie during negotiations, which adds a layer of complexity to the game.

Players would need to consider various factors, such as their initial token holdings, their objectives, their perceptions of other players' objectives, and the information available to them (including potential lies). Strategies could involve cooperative agreements, bluffing, coercion, or other negotiation tactics, with the ultimate goal for A and B being to acquire and share all of C's tokens, while C seeks to maximize its own token holdings within the constraints of the game.

Here is a decision tree based on the game parameters provided. The decision tree will illustrate the sequence of decisions made by players A, B, and C, leading to the end state where all of C's tokens are owned by A, B, or both.

We'll start with Player A's decision:

1. Player A's Decision:

- A can either:

- Offer a token exchange to B

- Keep tokens and pass the turn to B

If A chooses to offer a token exchange, possible sub-decisions depend on B's response.

2. Player B's Decision:

- B, upon receiving an offer from A, can:

- Accept the offer

- Reject the offer

- Make a counteroffer

If B accepts, the game proceeds accordingly. If not, B's turn is over, and C gets to make a decision.

3. Player C's Decision:

- C can:

- Offer tokens to A or B in exchange for their tokens

- Pass the turn to A

The process continues until all of C's tokens are owned by A, B, or both. Here's how the decision tree might look in a simplified form:

                      A
                  /       \
               Offer     Pass
              /  |  \       
             /   |   \
            /    |    \
     B Accept Reject Counteroffer
         /        |       \
        /         |        \
       /          |         \
      /           |          \
Loop to A      C Pass        Offer
                 /  \        /   \
                /    \      /     \
A            Offer  Pass  Offer   Pass

(A moves first to reflect predominance of resources)

In this tree A's decision is shown at the root. Each branch represents a decision or a possible response. Subsequent branches represent the decisions made by B and C in response to the previous player's move. The game continues until all of C's tokens are acquired by A, B, or both.

This decision tree outlines the sequence of decisions made by each player and how they lead to the end state of the game. C will lose all their tokens, though whether C loses all tokens to both A and B or only to one of them is not pre-determined and depends on the course of play. The duration of the game is also somewhat open. C might lose comparatively quickly or might take a while to lose, but given the asymmetries in the game, which are much greater in reality, C loses. The real world asymmetries include: productive power, industrial capacity or lack thereof, population base or lack thereof, and military training and equipment available. C might prolong the agony, but if A and B are rational actors then they simply reduce C, including seizing as many secrets C holds that they can.

Given the asymmetries in the initial token distribution and assuming perfect cooperation between A and B, the game will eventually reach the end state where C loses all tokens to A and B, possibly to both A and B jointly. This is without considering Russian domestic governance, which only exacerbates the problem for Russia. It is entirely likely that saboteurs within Russia will help with decryption and also that certain Russians can be bribed or otherwise coerced to betray Russian comsec, one way or other.

Returning to theory: In this scenario, A and B would strategize to maximize their combined token holdings at the expense of C. Since A and B have complementary token types initially, they can potentially exchange tokens between themselves to optimize their positions before focusing on acquiring C's tokens.

The key aspect here is the extent of cooperation between A and B. If they collaborate efficiently, they can coordinate their actions to ensure that C loses all tokens quickly without sacrificing any of their own. This might involve making strategic offers to C, leveraging their initial token advantages, and possibly misleading or coercing C in negotiations. Even imperfect cooperation would, after sufficient iterations, lead to C losing all tokens, though whether C loses them to A or B or both is an open question.

Achieving perfect cooperation between A and B in practice might be challenging, especially considering the potential for lies and deception allowed in the game as in the real world. Nonetheless, assuming effective cooperation between A and B, it's feasible for them to work together to reach the end state where C loses all tokens to A and B, or possibly both A and B jointly.

Mathematical Representation

1. Graph Representation: - Nodes: Represent A, B, and C as nodes in a graph. - Edges: Represent the distrust relationships as edges.

We denote the graph G=( V,E ) , where V={A,B,C} is the set of vertices (nodes) and E ⊆ V × V is the set of edges representing distrust relationships.

Given the situation: - A distrusts B. - B distrusts A. - A distrusts C. - B distrusts C.

The graph G can be represented as follows: - V={A,B,C} - E={( A,B ) ,( B,A ) ,( A,C ) ,( B,C ) }

Implications for Triadic Closure

Triadic Closure is a concept in social network theory which states that if two people have a friend in common, there is an increased likelihood that they will become friends themselves, forming a closed triangle.

In the context of our graph: - The edges (A, B), (A, C), and (B, C) form a triadic structure but not a closed triad because there is no direct edge between A and C that represents a positive relationship or cooperation.

Implications:

1. Lack of Cooperation: - In this graph, there is no positive relationship (friendship) between A and B. The triad remains open, indicating that A and B do not cooperate directly despite both distrusting C.

2. Strategic Alliances: - Despite A and B being rivals, their common distrust of C can lead to a temporary or strategic alliance to achieve a common goal (in this case, A's desire to destroy C). This is often seen in international relations where states form alliances against a common adversary.

3. Structural Balance Theory: - According to structural balance theory, for the network to be balanced, all three relations need to be positive, or two should be negative and one positive. The current network is unbalanced as it does not meet either condition. - This imbalance suggests potential instability. A potential resolution might involve A and B eventually cooperating against C or C finding a way to create discord between A and B to prevent their cooperation.

Conclusion: The situation of A and B distrusting each other but both distrusting C, with A wishing to destroy C, creates an open triadic structure in graph theory. This configuration is unstable and suggests potential strategic moves where temporary alliances could form despite the underlying distrust, highlighting the complex nature of strategic interactions and alliances in social and international relations. The end state is, roughly speaking, inevitable. Though, how it unfolds and how long it takes to reach the end state – or whether the end state already obtains depend on how well China and the USA cooperate. Cooperation in turn depends on trust. Trust in turn grows out of common interests, goals, and common culture.

Mathematical proof

To provide a mathematical proof that this game reaches the end state where player C loses all tokens to players A and B (or both A and B jointly), we can analyze the optimal strategy for A and B, assuming perfect cooperation. We'll consider the initial token distributions and the potential token exchanges between the players.

Let's denote the number of DKRP tokens owned by player X as DKRP(X), and the number of KPTXT tokens owned by player X as KPTXT(X).

Given the initial token distributions:

- A: DKRP(A) = 7, KPTXT(A) = 3, DKRP(B) = 2, KPTXT(B) = 1

- B: DKRP(B) = 3, KPTXT(B) = 8, DKRP(A) = 1, KPTXT(A) = 10

- C: DKRP(C) = 20, KPTXT(C) = 20

To reach the end state where C loses all tokens, A and B would collaborate to acquire C's tokens. Here's a potential strategy:

1. A and B begin by exchanging tokens between themselves to optimize their positions. Since A has more DKRP tokens and B has more KPTXT tokens initially, they can exchange DKRP tokens for KPTXT tokens to balance their holdings.

2. Once A and B have balanced their token holdings, they would jointly approach C for token exchanges. They can offer favorable deals to C, leveraging their combined token holdings and potentially misleading C about the true value of the tokens being exchanged.

3. Since A and B have more negotiating power and token leverage, they can strategically pressure C into accepting deals that are advantageous to A and B. This can involve offering attractive token exchanges or using deception to manipulate C's decisions.

4. Through a series of negotiations and token exchanges, A and B can gradually acquire all of C's tokens without sacrificing any of their own. They can continue to collaborate to ensure that C loses all tokens to them.

5. Once all of C's tokens are acquired by A and B (or both), the game reaches the end state where C has lost all tokens.

Mathematically, we can model this process by considering the token exchanges and negotiations as a series of strategic decisions made by A, B, and C. By analyzing the optimal strategies for A and B, accounting for their initial token advantages and potential collaboration, we can demonstrate that the game can indeed reach the end state where C loses all tokens to A and B, or possibly both A and B jointly.

Token Representation

We can represent the tokens using a matrix, where each row corresponds to a player (A, B, or C) and each column corresponds to a token type (DKRP or KPTXT). The entries in the matrix represent the number of tokens of each type held by each player.

Let's denote the matrix as T, where T[i, j, k] represents the number of tokens of type j held by player i, where i ∈ {A, B, C}, j ∈ {DKRP, KPTXT}, and k is the index of the token (e.g., k = 1 for the first token of type j held by player i).

Initially, the matrix T looks like this:

T = [

[7, 3, 1, 2], // A's tokens

[3, 8, 1, 10], // B's tokens

[20, 20, 0, 0] // C's tokens

]

The game can be modeled as a series of negotiations between players, where each player tries to acquire tokens from others while minimizing their own losses. We can represent the negotiations using a sequence of matrices, where each matrix represents the state of the tokens after a negotiation round.

Let's denote the negotiation round as t, and the matrix at round t as T_t. The initial matrix T_0 is the one shown above.

At each round t, players can engage in one of the following actions:

Trade: Player i offers to trade x tokens of type j to player k in exchange for y tokens of type l. If player k accepts, the tokens are exchanged, and the matrices are updated accordingly.

Lie: Player i makes a false claim about their token holdings to deceive other players. This can affect the negotiations, but the actual token holdings remain unchanged.

Refuse: Player i refuses to trade or negotiate with other players.

The game ends when all tokens of type DKRP(C) and KPTXT(C) are owned by A or B or both A and B.

We can evaluate the game using dynamic programming, where the goal is to maximize the number of tokens acquired by A and B while minimizing their losses.

Let's define the following variables:

V_i(t) : the value of player i's tokens at round t

U_i(t) : the utility function of player i at round t, which represents their satisfaction with the current token holdings

P_i(t) : the probability of player i acquiring a token of type j at round t

L_i(t) : the probability of player i losing a token of type j at round t

The dynamic programming equation can be written as:

V_i(t+1) = max(U_i(t), V_i(t) + ∑[j,k] P_i(t) \* T_t[i, j, k] - L_i(t) \* T_t[i, j, k])

The goal is to maximize V_A(T) and V_B(T) while minimizing V_C(T).

Computational Representation

We can also cast this game as a dynamic programming problem, where the goal is to maximize the number of tokens acquired by A and B while minimizing their losses. The game can be modeled as a series of negotiations between players. using a sequence of matrices.

Let's denote the negotiation round as t, and the matrix at round t as T_t. The initial matrix T_0 is the one shown above.

At each round t, players can engage in one of the following actions:

Trade Tokens: Player i offers to trade x tokens of type j to player k in exchange for y tokens of type l. If player k accepts, the tokens are exchanged, and the matrices are updated accordingly.

Lie about number and/or content of tokens: Player i makes a false claim about their token holdings to deceive other players. This can affect the negotiations, but the actual token holdings remain unchanged.

Refuse: Player i can refuse to trade or negotiate with other players.

The game ends when all tokens of type DKRP(C) and KPTXT(C) are owned by A or B or both A and B.

Let's define the following variables:

V_i(t) : the value of player i's tokens at round t

U_i(t) : the utility function of player i at round t, which represents their satisfaction with the current token holdings

P_i(t) : the probability of player i acquiring a token of type j at round t

L_i(t) : the probability of player i losing a token of type j at round t

The dynamic programming equation can be written as:

V_i(t+1) = max(U_i(t), V_i(t) + ∑[j,k] P_i(t) \* T_t[i, j, k] - L_i(t) \* T_t[i, j, k])

The goal is to maximize V_A(T) and V_B(T) while minimizing V_C(T).

Solving the Game

Solving this game requires a combination of game theory, dynamic programming, and optimization techniques. One possible approach is to use a Markov decision process (MDP) to model the game and then apply reinforcement learning algorithms to find the optimal strategies for A and B.

The MDP can be defined as follows:

States: S = {T_t | t = 0, 1, 2,...}

Actions: A = {Trade, Lie, Refuse}

Transition model: P(s' | s, a) = Pr(T_t+1 | T_t, a)

Reward function: R(s, a) = U_i(t) - L_i(t)

The reinforcement learning algorithm can be used to learn the optimal policies for A and B, which maximize their expected utilities while minimizing their losses.

This is a high-level mathematical formulation of the game. The actual solution will depend on the specific details of the game and the optimization algorithms used.

“I would like to solve the puzzle.”