#
Reduction Theorem for Secrecy over Linear Network Code for Active Attacks^{ †}

^{1}

^{2}

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^{7}

^{*}

^{†}

^{‡}

## Abstract

**:**

## 1. Introduction

## 2. Single Transmission Setting

#### 2.1. Generic Model

**Definition**

**1.**

**(A1)**- The relation ${H}_{E;j,i}=0$ holds for $j\in {w}_{i}$.
**(A2)**- The relation ${w}_{1}\subseteq {w}_{2}\subseteq \dots \subseteq {w}_{{m}_{5}}$ holds.

**Definition**

**2.**

**Lemma**

**1.**

**Proof.**

**Theorem**

**1**

**.**When the strategy α satisfies the uniqueness condition, Eve’s information ${\mathbf{Y}}_{E}(\alpha )$ with strategy α can be calculated from Eve’s information ${\mathbf{Y}}_{E}(0)$ with strategy 0 (the passive attack), and ${\mathbf{Y}}_{E}(0)$ is also calculated from ${\mathbf{Y}}_{E}(\alpha )$. Hence, we have the equation

**Proof.**

#### 2.2. Recovery and Information Leakage with Linear Code

**Proposition**

**1.**

**Proof.**

**Proposition**

**2.**

**Proof.**

**Corollary**

**1.**

#### 2.3. Construction of ${K}_{B},{K}_{E}$ from Concrete Network Model

#### 2.4. Construction of ${H}_{B},{H}_{E}$ from a Concrete Network Model

#### 2.5. Strategy and Order of Communication

#### 2.6. Secrecy in Concrete Network Model

**(B1)**- Eve eavesdrops one of three edges $e(7),e(9),$ and $e(11)$ connected to the sink node, and eavesdrops and contaminates one of the remaining eight edges $e(1),e(2),e(3),e(4),e(5),e(6),e(8),$ and $e(10)$ that are not connected to the sink node.

#### 2.7. A Problem in Error Detection in a Concrete Network Model

**(B2)**- Our node operations are fixed to the way as Figure 2.
**(B3)**- The message set $\mathcal{M}$ and all information on all edges are ${\mathbb{F}}_{2}$.
**(B4)**- The variables ${X}_{1},{X}_{2},{X}_{3},$ and ${X}_{4}$ are given as the output of the encoder. The encoder on the source node can be chosen, but is restricted to linear. It is allowed to use a scramble random number, which is an element of $\mathcal{L}:={\mathbb{F}}_{2}^{k}$ with a certain integer k. Formally, the encoder is given as a linear function from $\mathcal{M}\times \mathcal{L}$ to ${\mathbb{F}}_{2}^{4}$.
**(B5)**- The decoder on the sink node can be chosen dependently of the encoder and independently of Eve’s attack.

#### 2.8. Wiretap and Replacement Model

## 3. Multiple Transmission Setting

#### 3.1. General Model

**Definition**

**3.**

#### 3.2. The Multiple Transmission Setting with Sequential Transmission

**Definition**

**4.**

**(A1’)**- The relation ${H}_{E;j,i}=0$ holds for $(j,l)\notin {w}_{i,l}$.
**(A2’)**- The relation ${w}_{i,l}\subseteq {w}_{{i}^{\prime},{l}^{\prime}}$ holds when ${\tau}_{E}(\eta (i),l)\le {\tau}_{E}(\eta ({i}^{\prime}),{l}^{\prime})$.

**Lemma**

**2.**

**Proof.**

#### 3.3. Multiple Transmission Setting with Simultaneous Transmission

**Lemma**

**3.**

#### 3.4. Non-Local Code and Reduction Theorem

**Definition**

**5.**

**Remark**

**1.**

**Theorem**

**2**

**.**When the triplet $(\mathit{K},\mathit{H},{\alpha}^{n})$ satisfies the uniqueness condition, Eve’s information ${Y}_{E}^{n}({\alpha}^{n})$ with strategy ${\alpha}^{n}$ can be calculated from Eve’s information ${Y}_{E}^{n}(0)$ with strategy 0 (the passive attack), and ${Y}_{E}^{n}(0)$ is also calculated from ${Y}_{E}^{n}({\alpha}^{n})$. Hence, we have the equation

**Proof.**

**Remark**

**2.**

**Remark**

**3.**

#### 3.5. Application to Network Model in Section 2.6

**(B1’)**- Eve can choose any one of nodes $v(1),\dots ,v(4)$. When $v(2)$ is chosen, she eavesdrops all edges connected to $v(2)$ and contaminates all edges incoming to $v(2)$. When $v(i)$ is chosen for $i=1,3,4$, she eavesdrops and contaminates all edges connected to $v(i)$.

#### 3.6. Error Detection

**(B3’)**- The message set $\mathcal{M}$ is ${\mathbb{F}}_{q}^{2}$, and all information on all edges per single use are ${\mathbb{F}}_{q}$.
**(B4’)**- The encoder on the source node can be chosen, but is restricted to linear. It is allowed to use a scramble random number, which is an element of $\mathcal{L}:={\mathbb{F}}_{q}^{k}$ with a certain integer k. Formally, the encoder is given as as a linear function from $\mathcal{M}\times \mathcal{L}$ to ${\mathbb{F}}_{q}^{8}$.

#### 3.7. Solution of Problem Given in Section 2.7

## 4. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Network of Section 2.6 with name of edges.

**Figure 2.**Network of Section 2.6 with network flow.

**Figure 3.**Network of Section 2.6 with the wiretap and replacement model. Eve injects the replaced information on the edges ${e}^{\prime}(2)$ and ${e}^{\prime}(5)$.

${m}_{1}$ | Number of edges |

${m}_{2}$ | Number of vertecies |

${m}_{3}$ | Dimension of Alice’s input information $\mathbf{X}$ |

${m}_{4}$ | Dimension of Bob’s observed information ${\mathbf{Y}}_{B}$ |

${m}_{5}$ | Dimension of Eve’s injected information $\mathbf{Z}$ |

${m}_{6}$ | Dimension of Eve’s wiretapped information ${\mathbf{Y}}_{E}$ |

${m}_{7}$ | ${m}_{1}-{m}_{3}$ |

Node | Eavesdropping | Vector | $\mathit{\eta}$ | Detection | Recovery |
---|---|---|---|---|---|

$v(1)$ | $e(1)$ | $(0,1,0)$ | $\eta (1)=1$ | $-{Z}_{1}\kappa $ | ${Y}_{B,2}-{Y}_{B,3}$ |

$e(5)$ | $(0,1,0)$ | $\eta (2)=5$ | |||

$e(10)$ | $(0,1,0)$ | $\eta (3)=10$ | |||

$v(2)$ | $e(2)$ | $(\kappa ,\kappa ,1+\kappa )$ | ${Z}_{2}-{Z}_{1}\kappa $ | ${Y}_{B,2}-{Y}_{B,3}$ | |

$e(5)$ | $(0,1,0)$ | $\eta (1)=5$ | |||

$e(6)$ | $(0,1,0)$ | ||||

$e(7)$ | $(\kappa ,1+\kappa ,1+\kappa )$ | $\eta (2)=2$ | |||

$e(8)$ | $(0,1,0)$ | ||||

$v(3)$ | $e(3)$ | $(1,0,1)$ | $\eta (1)=3$ | $-({Z}_{1}+{Z}_{2}+{Z}_{3})\kappa $ | $({Y}_{B,1}-{Y}_{B,3}(1+\kappa )){\kappa}^{-1}$ |

$e(6)$ | $(0,1,0)$ | $\eta (2)=6$ | |||

$e(9)$ | $(1,1,1)$ | $\eta (3)=9$ | |||

$v(4)$ | $e(4)$ | $(0,0,1)$ | $\eta (1)=4$ | $-{Z}_{1}-{Z}_{2}-{Z}_{4}$ | ${Y}_{B,2}(1+\kappa )-{Y}_{B,1}$ |

$e(8)$ | $(0,1,0)$ | $\eta (2)=8$ | |||

$e(10)$ | $(0,1,0)$ | $\eta (3)=10$ | |||

$e(11)$ | $(0,1,1)$ | $\eta (4)=11$ |

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**MDPI and ACS Style**

Hayashi, M.; Owari, M.; Kato, G.; Cai, N.
Reduction Theorem for Secrecy over Linear Network Code for Active Attacks. *Entropy* **2020**, *22*, 1053.
https://doi.org/10.3390/e22091053

**AMA Style**

Hayashi M, Owari M, Kato G, Cai N.
Reduction Theorem for Secrecy over Linear Network Code for Active Attacks. *Entropy*. 2020; 22(9):1053.
https://doi.org/10.3390/e22091053

**Chicago/Turabian Style**

Hayashi, Masahito, Masaki Owari, Go Kato, and Ning Cai.
2020. "Reduction Theorem for Secrecy over Linear Network Code for Active Attacks" *Entropy* 22, no. 9: 1053.
https://doi.org/10.3390/e22091053