物联网传感层节点实时远程认证与信任追踪机制

99 浏览量更新于2024-07-15 收藏 913KB PDF 举报

"物联网传感层节点的远程认证机制是一种针对物联网中传感层节点的安全策略，旨在解决现有远程认证机制在实时信任度确认和节点跟踪上的不足。本文提出的机制结合了形式化描述、实时信任度度量和节点属性封装，以确保数据传输的信任度并能够跟踪不受信任的节点。其安全性和动态适应性得到了证明，能有效抵御感知节点的攻击，提高数据传输的可靠性。" 物联网（Internet of Things, IoT）是一个由各种智能设备和传感器组成的网络，其中传感层节点是收集和传输数据的关键组件。在物联网环境中，数据的可信传输至关重要，因为任何安全漏洞都可能导致敏感信息泄露或系统被恶意操控。传统的远程认证机制在面对物联网传感层的特定需求时显得力不从心，无法实时评估节点的信任度，也无法有效地跟踪可能的恶意节点。本文提出了一种创新的远程认证机制，主要包含以下几个方面： 1. **形式化描述**：首先，对物联网传感层节点进行形式化的描述，这是构建安全机制的基础。形式化描述有助于精确理解节点的功能和行为，从而更好地设计和分析认证过程。 2. **实时信任度度量**：基于形式化描述，文章提出了一个实时信任测量模型。这个模型能够动态评估每个传感节点的信任程度，确保在数据传输过程中节点的可信度始终保持最新状态。这种实时性对于及时识别潜在威胁至关重要。 3. **节点属性和信任值封装**：通过封装感知节点的属性和信任度，机制在数据传输过程中实现了节点信任度的实时跟踪。这使得系统能够在传输过程中随时了解节点的状态，及时发现并隔离不信任的节点。 4. **安全性证明**：在标准模型下，该机制的安全性得到了证明，表明它能够在保护节点隐私的同时，有效执行认证过程，防止节点隐私在认证过程中被暴露。 5. **动态适应性**：此机制表现出良好的动态适应性，能够适应不断变化的网络环境，即使在面临攻击或网络条件波动的情况下，也能保持数据传输的信任度。 6. **易实现性与有效性**：提出的机制不仅简单有效，而且设计灵活，便于实际部署和实施。仿真实验的结果证实了该机制在抵抗感知节点攻击方面的有效性，显著提高了数据传输的信任度。这项研究为物联网的传感层提供了一种安全可靠的远程认证方案，它弥补了现有技术的不足，增强了物联网环境的数据安全性和整体性能。

870 B. Gong et al. / Future Generation Computer Systems 78 (2018) 867–886

2.1.5. Other authentication mechanism of IoT

To authenticate the identity of the terminal in the Internet

of Things, domestic and foreign scholars have carried out a lot

of research on authentication in the Internet of Things. Litera-

ture [28] introduced several the biometric-based user authenti-

cation schemes for heterogeneous wireless sensor networks and

analyzed the defects of biometric-based authentication schemes,

such as the failure to resist replay attack, user impersonation

attack, the failure to accomplish mutual authentication and the

failure to provide data privacy. Literature [29] presented a remote

authentication via Biometrics, this authentication is an effective

wavelet-based stenographic method which is proposed for hid-

ing encrypted biometric signals into semantically meaningful VOs

such as the head-and-shoulders VO, but this authentication is

mainly used in Video and image transmission field, it cannot be

applied to other applications in IoT. Literature [30] presented an

efficient generic framework for three-factor authentication, and

this scheme enhances the security of existing two-factor authenti-

cation schemes by upgrading them to three factor authentication

schemes, without exposing user privacy. But three-factor authenti-

cation But this authentication mechanism is a static authentication

mechanism that cannot continuously monitor the authentication

object, it also cannot meet the changing needs of the computing

environment in the Internet of Things. Literature [31] presented a

remote authentication for Smartphones, this authentication com-

bines cloud computing to complete terminal authentication, which

can reduce the energy consumption, and this authentication is suit-

able for low-latency continuous authentication. But this authenti-

cation needs to work with cloud computing, it is not suitable for

the sensing network deployed in wild environment. Literature [32]

presented a two Factor remote authentication, and secret PIN ver-

ification is combined with keystroke analysis to enhance accuracy

level of authentication. The authors have proved their algorithms

are flexible, easy for implementation and more practical for users

than the other known methods in healthcare field. But this scheme

is only considered in the medical field of application, and the

versatility is poor.

2.1.6. Summary

In conclusion, the above-mentioned remote attestation models

have a variety of defects, when they are applied to the sensing

nodes of Internet of thing. To solve the defects, the unified descrip-

tion of the sensing nodes is described in this paper, and remote

attestation mechanism is realized on the basis of the dynamic

trusted measure of the sensing nodes. Compared with the above

remote attestation models, remote attestation model proposed in

this paper has good environmental adaptability, it can real-time

monitor the trust of the proof node and proves its safety under the

standard model.

2.2. Related work of trust measurement for sensing node

2.2.1. The need for trusted measurement of sensing layer nodes

Internet of Things is widely used in various fields, such as the

wisdom of the city, environmental protection, industrial control,

military cooperation and logistics positioning. And it promotes

the economic and social development, but there will be serious

security problems, resulting in huge economic losses and even

endangering people’s lives. The Internet of Things is composed

of the sensing layer, the network layer and the application layer.

The sensing layer node is the peripheral nerve of the Internet

of things. And it realizes the intelligent sensing recognition, the

information collection processing and the automatic control of the

physical world (object), and connect the physical entity to network

communication domain through the communication gateway, and

connect with application domain. Sensing nodes are essential for

the smooth operation of the Internet of Things, so the sensing

operation of the node is the basis of the security of things. The

current lack of research on the security mechanism of node-aware

nodes makes most of the sensing nodes in the actual operation

of the ‘‘streaking’’ state, which is vulnerable to attack. Once the

sensing node is attacked, it will directly affect the Internet of things

on the data acquisition, transmission and processing, and thus

affect the normal application of Internet of things.

Limited by the effective computing resources of the sensing

layer nodes, traditional virus defense mechanism, firewall mech-

anism and intrusion detection mechanism are difficult to apply

to the sensing nodes. These traditional security mechanisms are

passive defense mechanism, and they cannot deal with unknown

security threats. For example, location information services are a

typical application of the Internet of Things, and it is often used

for the positioning of children and the elderly. In this application

scenario, it is important to ensure that hosts networking terminals

of children or the elderly are trustworthy, otherwise they will

not be able to effectively identify the location of children and the

elderly. And in order to avoid malicious attackers’ access to the

location information of children and the elderly, location query

must also be trusted, which requires real-time trusted confirma-

tion of the Internet of things terminals. In order to protect the

trusted operation of sensing layer nodes, it is necessary to monitor

whether the node is trusted in real time. In other words, it is

necessary to ensure that the sensing nodes are trusted to operate

from the perspective of active metrics.

Trusted measurement of sensing nodes can not only improve

the security of Internet of Things, but also reduce the extra over-

head incurred in preventing and monitoring due to untrustwor-

thiness. However, the research on the trusted measurement of the

existing nodes in the Internet has not been satisfactory. First of all,

the current research on trustworthy measurement depends on the

specific application scenarios and the universality is poor. Besides,

it lacks trustworthy measurement model for the internet of Things

sensing nodes. The network of trusted nodes depends on the state

of the sensing nodes, the real-time monitoring and measurement

of the behavior, so the research is suitable for the static and dy-

namic measurement mechanism of the sensing nodes, which is the

key to ensure the trusted operation of the sensing nodes. In the

sensing layer, the current trusted measurement mechanism has

the following challenges: (1) node resources are limited, (2) nodes

are heterogeneous, (3) lack of facility support, (4) wireless channel

fragility. And the trust mechanism of the object-sensing layer node

through the trusted measure is faced with some of the following

challenges: (1) Heterogeneous environment cannot use a unified

trusted measurement mechanism, (2) sensing node deployment

and application mode makes the traditional security policy failure,

(3) different application scenarios make the interaction between

nodes exist unknown mode.

Therefore, in view of the above, the traditional security mech-

anism does not apply to the sensing nodes because of the special

characteristics of the sensing nodes. Secondly, because the sensing

nodes are the basis of the Internet of Things, the trusted operation

is the basis of the trusted operation of the Internet of Things.

Finally, the main task of the sensing node is to collect and transmit

data. To ensure the trust of the data, it is necessary to monitor and

confirm the trusted state of the sensing node in real time.

2.2.2. Related research on trusted metrics of sensing Layer nodes

The current trustworthiness measurement for sensing nodes

of the Internet of Things is to establish a trusted measurement

model of the sensor nodes based on the state of the nodes and

the evidence of the behavior. In literature [33], a trusted metric

model based on the state of data transmission is discussed. The

model focuses on the reliability of data transmission, but lacks

剩余19页未读，继续阅读

weixin_38712279

粉丝: 6
资源: 949

物联网传感层节点实时远程认证与信任追踪机制

ESP8266+MQTT：低成本物联网温湿度传感节点设计

物联网设备节点管理系统服务器端实现

物联网实验教学：ZigBee传感层与实验室建设

基于ESP8266WiFi模块和MQTT协议的物联网传感节点设计1

1物联网传感技术PPT教案.pptx

物联网传感技术PPT学习教案.pptx

1物联网传感技术(PPT52页).ppt

物联网与数控机床远程智能监控系统.pdf

基于物联网对智能家居远程控制系统设计.pdf

基于物联网的智能家居远程无线监控系统设计.pdf

最新资源