区块链赋能：物联网安全的协同机制

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"证据与信任：物联网协同安全机制" 在物联网(IoT)环境中，设备间的交互日益频繁，安全问题变得至关重要。"证据与信任：物联网协同安全机制"这篇研究论文探讨了如何利用证据的属性以及区块链技术来增强物联网的安全性和信任度。证据的三个关键属性——相关性、真实性和合法性，是确保物联网数据安全的基础。相关性确保了证据与事件的关联性，真实性则保证了数据未经篡改，而合法性使证据在法律框架下具有效力。区块链技术作为一种分布式、防篡改的数据库，为物联网安全提供了理想的基础。它将数据分块存储，并通过复杂的密码学算法确保每个区块的完整性和前后顺序的一致性。这种特性使得物联网设备能够创建和验证不可伪造的数据记录，从而增强对关键信息的信任。本文提出了一种利用区块链的关键技术实现物联网设备协同安全的方法。通过分布式众包的方式，可以有效地检测和防止对关键数据证据的篡改，提高系统的安全性。这种方法利用网络中多个节点的共识，使得篡改数据的行为变得极其困难，同时也增强了数据的自我修复能力。论文结合了理论研究和实践经验，旨在为物联网的协同安全提供一种操作性强、成本效益高的解决方案。作者Bin Wen、Ziqiang Luo和Yazhi Wen分别来自海南师范大学信息科学技术学院和华中科技大学计算机科学与技术学院，他们通过实验验证了该方案的可行性和有效性，为物联网安全领域提供了一种创新的思路。总体来说，"证据与信任：物联网协同安全机制"这篇论文深入探讨了物联网环境下的证据机制和区块链应用，旨在提升物联网系统的数据安全性和互信水平，为未来物联网安全架构的设计提供了新的视角和理论支持。

Evidence and Trust: IoT Collaborative Security

Mechanism

Bin Wen and Ziqiang Luo

School of Information Science and Technology,

Hainan Normal University,

Haikou, China

Email: binwenwebb@gmail.com

Yazhi Wen

School of Computer Science and Technology,

Huazhong University of Science and Technology,

Wuhan, China

Email: wyzhust@163.com

Abstract—The evidence has three properties including rele-

vance, authenticity and legitimacy. For evidence, once implement-

ed, it must not be tampered with and can always be traced back.

For trust, the content can be forensics, so the relationship between

each other is trustworthy and exchangeable value. Blockchain is

a tamper-proof and unforgeable decentralized shared ledger that

chunks data blocks chronologically into speciﬁc data structures

and is cryptographically guaranteed. In this paper, we use the key

technologies of blockchain to investigate and achieve collaborative

security for IoT devices. This approach uses distributed crowd-

sourcing to make tampering of critical data evidence (security) .

Combination of theoretical research and empirical validation, the

paper tries to provide a technical operational and cost-effective

solution for collaborative security with blockchain services and

promoting the key data stability and self-healing ability.

Keywords—Internet of Things; evidence; blockchain services;

collaborative security

I. INTRODUCTION

Internet is moving from content delivery to the era of

trust value. On the basis of mutual trust, both parties can

exchange value[1], [2]. Bitcoin birth in 2009 is a landmark

event[3], [1]. As a technology that builds trust and exchange

of value, blockchain came into being. Blockchain allows every

movement of the digital currency to be clearly identiﬁed and

linked, while also protecting the privacy of the participants.

The core advantage of the commercial blockchain is that

the distributed ledger constructed by the blockchain using

cryptography has formed a complete and uninterrupted trust

bond between the parties in the collaboration, greatly reducing

business friction and improving business process efﬁciency.

The distributed system can learn from the decentralized ledger

database technology in the blockchain to improve the core data

resource security [2], [4].

Therefore, starting from the discussion of the logic for

evidence and trust, we are committed to the integrity and

illegal tampering of the key data (evidence) of distributed

systems in order to achieve system security.

This paper aims at study the collaborative security for

distributed IoT with blockchain style. We will mainly focus on

collaborative data protection and self-healing mechanism. The

rest of the article is organized as follows. Section II includes

the related technologies for Internet trust infrastructure. Sec-

tion III introduces the application scenario - distributed IoT

system. Section IV presents collaborative security mechanism

to deal with data protection and self-healing. Conclusions with

main contributions of proposed approach are also touched

upon in section V.

II. B

UILD AN INTERNET TRUST INFRASTRUCTURE

A. Evidence and Trust

Evidence refers to the basis for ascertaining the facts of

a case in accordance with the rules of procedure. Foren-

sics means obtaining evidence. According to Wikipedia’s

deﬁnition, Forensic science is the application of science to

criminal and civil laws, mainly-on the criminal side-during

criminal investigation, as governed by the legal standards of

admissible evidence and criminal procedure

. There is a job

called Computer Intrusion Forensics Expert.

In social science, trust is considered a dependency. In

psychology, trust is a stable belief that maintains the social

shared value and stability. It is the overall expectation that the

individual can trust others’ words, promises and declarations.

Formally, Authenticity = Completeness = ”Untampered” is

the formal requirement of a data message as evidence. The

evidence has three properties including relevance, authenticity

and legitimacy. Electronic data (data messages) is not just

textual information.

How to employ sophisticated algorithm design and cryptog-

raphy to build trust?

• Evidence:

Once implemented, it must not be tampered with and can

always be traced back. Once the data is generated, it must

not be tampered with and can always be traced back.

• Trust:

Because the content can be forensics, the relationship

between each other is trustworthy and exchangeable

value.

We can precisely control the transparency and privacy

through algorithms. Artiﬁcial Intelligence now has three main

representative genres.

1) The ﬁrst direction of artiﬁcial intelligence is to use a

logical approach, usually we call it a school of logic, or

symbolism school.

https://en.wikipedia.org/wiki/Forensic science

8th International Conference on Information Science and Technology

June 30-Jul

6, 2018; Granada, Cordoba, and Seville, Spain

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