物联网中的RFID协议设计与安全优化

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"IET.RFID.Protocol.Design.Optimization.and.Security.for.the.Internet.of.Things" 本书《IET RFID：协议设计、优化与物联网安全》是IET（英国工程技术学会）传感器系列的一部分，专注于RFID（无线射频识别）技术在物联网（IoT）中的应用。随着RFID技术在各个行业的广泛应用，它已成为从通信到监控、远程操作、过程控制、精准与安全以及机器人和自动化等多个领域的基础。然而，这种快速发展也带来了新的挑战。书中的核心内容可能包括以下几个方面： 1. **RFID协议设计**：讨论RFID系统的通信协议，如EPC Gen2、ISO/IEC 18000等，涵盖标签、阅读器之间的数据交换机制，以及如何设计高效、低功耗的协议以适应物联网的广泛需求。 2. **协议优化**：探讨如何提高RFID系统性能，例如通过信号处理技术改善读取范围、减少干扰、提升数据传输速率，以及在网络层面上的优化策略，以确保大规模部署的可扩展性和稳定性。 3. **安全性**：在物联网环境中，RFID的安全性成为一个关键问题。书中可能涵盖防止未授权访问、数据保护、隐私保护、反克隆技术以及防止中间人攻击的措施。 4. **能量管理**：由于RFID设备通常电池供电或无源，因此，能源效率是设计的关键。书中可能会讨论如何通过优化协议和硬件设计来降低能耗，延长设备的使用寿命。 5. **物联网集成**：如何将RFID系统无缝集成到物联网架构中，实现与其他传感器和智能设备的协同工作，提升整个系统的智能性和互操作性。 6. **案例研究与应用**：书中可能包含实际应用案例，展示RFID在物流、供应链管理、智能制造、医疗保健、交通控制等领域中的成功实践，以及遇到的问题和解决方案。 7. **未来趋势与挑战**：对RFID技术的未来发展进行展望，讨论新技术和趋势，如物联网安全的新方法、RFID在5G网络中的角色、以及如何应对日益复杂的网络安全威胁。 8. **编辑委员会**：由来自全球知名学府的专家组成，确保了书中的内容具有权威性和专业性，包括德国Ilmenau技术大学的Hartmut Brauer博士，美国阿克伦大学的Nathan Ida教授，以及阿拉巴马大学的Edward Sazonov教授等。《IET RFID：协议设计、优化与物联网安全》为读者提供了一个全面了解RFID技术在物联网中所面临的挑战、解决方案及未来趋势的平台，对于科研人员、工程师以及相关行业的从业者来说，是一份极具价值的参考资料。

List of figures xv

|B −G|:|B ∩ G|:|G −B|=1:1:1. (b) Varying p from 0.01 to 0.25,

where |B −G|=|B ∩G|=|G − B|=2,000 103

4.4 Comparing the estimator variance observed from simulations with

the theoretical value calculated by (4.11). (a) Varying u =|U |

from 3,000 to 6,000, where |B −G|:|B ∩G|:|G − B|=1:1:1.

(b) Varying p from 0.01 to 0.25, where |B −G|=|B ∩G|=

|G −B|=2,000 104

4.5 Trade-off between time cost and energy cost: b =10,000,



=5,000, g =10,000, f =512, α, β=0.02,98% 111

4.6 Verifying the convergence of f and p. α =2%, β =98%.

(a) Small-scale RFID system: |B −G|=100, |B ∩G|=100,

|G −B|=100; (b) large-scale RFID system: |B −G|=2,000,

|B ∩G|=2,000, |G − B|=2,000 114

4.7 Evaluating the reliability of REB. α =5%, β =95%. (a) Tag ratio

|B −G|:|B ∩ G|:|G −B| is fixed to 1:1:1, and u varies from 3,000

to 21,000. (b) u is fixed to 9,000, and tag ratio varies 114

4.8 Evaluating the time efficiency of protocols with varying u. The

tag ratio of |B −

G|:|B ∩G|:|G −B| is fixed to 1:1:1. α =5%,

β =95% 116

4.9 Evaluating the time efficiency of protocols with varying tag ratio.

u is fixed to 30,000, and α =5%, β =95%. (a) Ratio of tags in

B −G varies, (b) ratio of tags in B ∩G varies, and (c) ratio of tags

in G −B varies 116

4.10 Evaluating the time efficiency of RFID estimation protocols

without blocker tag. The number of tags is fixed to 10,000.

(α, β) =(5%,95%) 117

4.11 Evaluating the accuracy of RFID estimation protocols with

varying number of blocking tag IDs. |G|=10,000, |B| varies

from 0 to 20,000. (α, β) =(5%,95%) 117

4.12 Evaluating the energy efficiency of protocols with varying u.

The tag ratio of |B −G|:|B ∩G|:|G − B| is fixed to 1:1:1. α =5%,

β =95% 118

4.13 Evaluating the energy efficiency of protocols with varying tag

ratio. u is fixed to 30,000, and α

=5%, β =95%. (a) Ratio of tags

in B − G varies, (b) ratio of tags in B ∩G varies, and (c) ratio of

tags in G − B varies 119

4.14 Time cost of REB vs. given energy threshold. u =30,000,

|B −G|:|B ∩ G|:|G −B|=1:1:3. α =2%, β =98% 120

4.15 Energy cost of REB vs. given time threshold. u =30,000,

|B −G|:|B ∩ G|:|G −B|=1:1:3. α =2%, β =98% 120

5.1 False-positive probability (P

) comparison 136

5.2 Number of slots (S

) vs. number of frames (n) 138

5.3 Frame size (f ) vs. persistence probability (p) 138

5.4 Number of frames (n) vs. persistence probability (p) 139

5.5 Comparison of analytical and empirical E[D] 141

xvi RFID protocol design, optimization, and security

5.6 Convergence of value of v with frames 146

5.7 Actual reliability vs. # missing tags 148

5.8 Detection time vs. # missing tags 148

5.9 Actual reliability vs. # unexpected tags 149

5.10 Detection time vs. # unexpected tags 150

5.11 Percentage of identified missing tags vs. total number of

missing tags 150

5.12 Percentage of identified missing tags vs. total number of

unexpected tags 151

5.13 Effect of difference between m and T 151

5.14 cv in estimates of missing tags 152

5.15 α vs. T when time of TH and RUN equal 153

6.1 Standard bloom filter vs. sampling bloom filter. (a) Standard

bloom filter: each element is pseudorandomly compressed into

the filer using k different hashing functions; (b) sampling bloom

filter: each element is also pseudorandomly mapped to the filter

with k hashing functions; however, each mapping is implemented

with a sampling probability p, and the sampling process is also

pseudorandom 161

6.2 Investigating the impact of p and k on the time cost of SBF-UDP,

where N =10,000, λ =100, β =95%, p varies from 3% to 100%,

and k changes from 1 to 15 164

6.3 Investigating the impact of p and k on the energy cost of

SBF-UDP, where N =10,000, λ =100, β =95%, p varies from

3% to 100%, and k changes from 1 to 15 167

6.4 Impact of p on SBF-UTD. N =3,000, λ =20, β =95%. k is the

number of hashing functions. (a) Time cost vs. p and (b) energy

cost vs. p 170

6.5 Evaluating the actual detection reliability of the proposed

SBF-UDP, where N varies from 1,000 to 10,000; λ =10; β

=95%.

(a) λ =10 unknown tag is simulated; (b) λ +1 =11 unknown

tags are simulated; (c) λ +2 =12 unknown tags are simulated;

(d) λ+3 =13 unknown tags are simulated 172

6.6 Evaluating the impact of channel error on the accuracy of

SBF-UTD, where N varies from 1,000 to 10,000. λ =10,

β =95%. 10 unknown tags are simulated. (a) Investigating the

impact of different P

BER

. (b) Investigating the effectiveness of

multicopy countermeasure 172

7.1 E[N

] vs. |C| 184

7.2 Theoretical vs. experimental P

186

7.3 Total number of slots S vs. frame size f 188

7.4 Effect of |A|, |B|, |C|, and β on execution time of RTSP:

(a) execution time vs. |A|, (b) execution time vs. |B|,

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