通信网络安全：生物加密与模糊保险库算法

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"《2018_Book_SecurityAndPrivacyInCommunication.pdf》是一本关于网络安全的专业书籍，由Raheem Beyah、Bing Chang、Yingjiu Li和Sencun Zhu等人编辑，收录了第14届国际通信网络安全会议（SecureComm2018）的论文，该会议于2018年8月8日至10日在新加坡举行。本书是计算机科学、社会信息学和电信工程研究所讲座笔记系列的一部分。" 本书探讨的主题集中在通信网络的安全与隐私，涵盖了多个关键领域。生物加密系统是其中的一个重要议题，这涉及到利用生物特征（如指纹、虹膜或DNA）进行身份验证和加密，因为这些特征的独特性使得它们在安全性上具有显著优势。生物加密技术可以增强身份验证过程，防止冒充和数据泄露，为网络安全提供更高级别的保护。 Fuzzy Vault共享密钥算法也是本书讨论的焦点。Fuzzy Vault是一种基于误差纠正码的密码学方法，它允许在不安全的环境中安全地存储和共享密钥。通过引入一定程度的“模糊”或容忍错误，Fuzzy Vault能够确保即使在数据受损或部分丢失的情况下，仍能正确解密。这种技术对于无线通信、物联网设备以及需要密钥管理的任何环境都有重要的应用价值。此外，书中还可能涵盖了其他网络安全技术，如入侵检测系统、密码学协议、隐私保护机制、网络防御策略以及最新的威胁和攻击模式。这些内容将深入分析通信网络中的潜在风险，并提出应对策略。同时，可能还会讨论政策、法规以及道德问题，这些都是确保网络安全和用户隐私不可或缺的部分。对于IT专业人士、研究人员以及对网络安全感兴趣的读者来说，这本书提供了宝贵的理论知识和实践经验，有助于提升对网络安全挑战的理解，并推动该领域的技术创新和发展。通过阅读本书，读者可以学习如何设计和实施更有效的安全措施，以应对不断演变的网络威胁。

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Contents – Part II XVII

A Secure Remote Monitoring Framework

Supporting Eﬃcient Fine-Grained Access

Control and Data Processing in IoT

Yaxing Chen

1,2(

)

, Wenhai Sun

,NingZhang

, Qinghua Zheng

Wenjing Lou

, and Y. Thomas Hou

School of Electronic and Information Engineering, Xi’an Jiaotong University,

Xi’an 710049, Shaanxi, China

cyx.xjtu@gmail.com, qhzheng@mail.xjtu.edu.cn

Department of Computer Science,

Virginia Polytechnic Institute and State University, Blacksburg, VA 24060, USA

{whsun,ningzh,wjlou,thou}@vt.edu

Abstract. As an important application of the Internet-of-Things, many

remote monitoring systems adopt a device-to-cloud network paradigm. In

a remote patient monitoring (RPM) case, various resource-constrained

devices are used to measure the health conditions of a target patient

in a distant non-clinical environment and the collected data are sent

to the cloud backend of an authorized health care provider (HCP) for

processing and decision making. As the measurements involve private

patient information, access control, conﬁdentiality, and trustworthy pro-

cessing of the data become very important. Software-based solutions that

adopt advanced cryptographic tools, such as attribute-based encryption

and fully homomorphic encryption, can address the problem, but they

also impose substantial computation overhead on both patient and HCP

sides. In this work, we deviate from the conventional software-based solu-

tions and propose a secure and eﬃcient remote monitoring framework

using latest hardware-based trustworthy computing technology, such as

Intel SGX. In addition, we present a robust and lightweight “heartbeat”

protocol to handle notoriously diﬃculty user revocation problem. We

implement a prototype of the framework for PRM and show that the

proposed framework can protect user data privacy against unauthorized

parties, with minimum performance cost compared to existing software-

based solutions with such strong privacy protection.

Keywords: Remote patient monitoring

· Internet-of-Things (IoT)

Fine-grained access control

· Secure hardware · Trusted computing

1 Introduction

Remote patient monitoring is one of the silver applications of the Internet of

Things (IoT) system. It allows health care providers to monitor the health con-

ditions of a patient outside the conventional clinical environment, e.g. at the

 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

R. Beyah et al. (Eds.): SecureComm 2018, LNICST 254, pp. 3–21, 2018.

https://doi.org/10.1007/978-3-030-01701-9

4Y.Chenetal.

patient’s home. The measurements are collected in real time from various IoT

devices, for example, user activities from audio and video streaming, biometrics

such as weight, blood pressure, heart rate via wearable devices on patients’ bodies

or sensors installed in the room and then sent to the HCP for further functional

processing. Instead of maintaining their proprietary infrastructures, nowadays

HCPs adopt the public cloud to provide such remote health care services [1].

Due to the private and sensitive nature of the measured information, there is

a crucial need for eﬀective and ﬂexible access control and secure data processing

to protect user data against unauthorized access while keeping the usability and

functionalities of the PRM system. The patient can permit an authorized HCP

to access data types based on the oﬀered service. For instance, a cardiovascular

HCP may need to access the information of electrocardiogram and heart rate.

At the same time, the data processing should be secure against unauthorized

parties and adhere to the intended service functions.

Much work has been done in the literature to address this problem. For exam-

ple, attribute-based encryption (ABE) [2–5] is a well-known technique used in

a variety of applications to achieve scalable, secure, ﬁne-grained access control.

On the other hand, privacy-preserving date processing can be realized by secure

multi-party computation [6], fully homomorphic encryption (FHE) [7]. How-

ever, such pure crypto-based solutions typically involve complex crypto oper-

ations. RPM at the client side consists of a number of battery-powered and

extremely resource-constrained devices, which are likely unable to aﬀord com-

plex computationally-intensive cryptographic operations. Another challenge is

the realization of on-demand user revocation and privacy-preserving data pro-

tection. The former typically requires a cumbersome large-scale key update as

well as storage re-encryption; the latter is usually considered to be prohibitively

expensive if we target generic computations, rather than a special class of com-

putation.

In this work, we take the RPM as a case study and propose a secure and

eﬃcient remote monitoring framework. In contrast to the software-based solu-

tions that exploit cryptographic primitives as building blocks, we present a novel

framework by leveraging the hardware-based trusted computing technology, such

as Intel SGX to protect user data privacy and enable secure computations over

sensitive data. Speciﬁcally, assuming a current smart home IoT platform, e.g.

Samsung SmartHome [8], we set up a trusted broker in the home gateway to

provide data encryption, remote attestation and key management on behalf of

the user (i.e., patient). On the cloud server, access control enforcement and data

processing are performed in a trusted execution environment (TEE) protected

by secure hardware. Our proposed approach represents a major departure from

existing software-based solutions. Due to the use of secure hardware, our scheme

is very eﬃcient as we only adopt symmetric encryption, such as AES and carry

out the monitoring service (i.e., HCP) functions which could be arbitrary con-

stitution over plaintext data, rather than encrypted ciphertext data.

On the other hand, there is a signiﬁcant challenge that we need to address

before delivering the claimed secure and eﬃcient framework. By our design, the

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通信网络安全：生物加密与模糊保险库算法

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DriverManager.getConnection("jdbc:sqlite:E:\\read_book\\read.db");写错了吗？

from flask import Flask app = Flask(__name__) @app.route('/book/list') def book_list(): page = request.args.get('page',default=1,type=int) return f"您获取的是第{page}的图书列表" if __name__ == '__main__': app.run(debug=True) 为什么浏览器报错

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#include <iostream> #include <vector> #include <algorithm> using namespace std; int main(); struct Entry; vector<Entry>phone_book(1000); void print_entry(int i) { cout<<phone_book[i].name<<' '<<phone_book[i].number<<'\n'; } void add_entries(int i) { phone_book.resize(phone_book.size()+n); }

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