Robust Dynamic Searchable Symmetric Encryption with CollusionResistance for Internet of Vehicles
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摘要: 随着车辆规模的持续扩大，车联网的应用日益广泛。车联网用户普遍将加密数据外包至云服务器，同时动态可搜索对称加密(DSSE)为解决加密数据动态更新与搜索提供了一种有效的手段。然而，传统的DSSE方案在实际应用中仍面临若干问题。一方面，DSSE无法同时支持多用户场景与搜索结果可验证。另一方面，DSSE还应实现前向与后向隐私从而保护敏感数据。此外，在设计方案时也需要考虑恶意用户与云服务器的合谋攻击风险与方案鲁棒性。因此，该文提出适用于车联网的抗合谋攻击的鲁棒动态可搜索对称加密方案(RDSSE-CR)。该方案通过双位图索引与布尔电路，构建了同时满足前后向隐私与鲁棒性的DSSE框架。同时，该文采用基于身份的密钥封装机制以适用于可能存在恶意用户与不可信云服务器合谋的多用户场景，该机制显著降低数据拥有者端的存储开销。此外，云服务器返回搜索结果的同时须根据验证标签提供工作量证明，以实现搜索结果完整性和正确性的有效验证。安全性分析证明RDSSE-CR方案实现了自适应安全性。性能分析表明，与现有同类方案相比，该方案在存储开销方面具有显著优势，在实现更多功能的同时仍保持了较高的运行效率，因而更加适用于车联网应用场景。Abstract:
Objective With the continuous expansion of the Internet of Vehicles (IoV), its applications have become increasingly widespread. Users commonly outsource encrypted data to cloud servers, and Dynamic Searchable Symmetric Encryption (DSSE) provides an effective approach for dynamically updating and searching encrypted data. However, existing DSSE schemes still face several challenges in practical applications. On the one hand, DSSE cannot simultaneously support multi-user scenarios and verifiable search results. Multi-user functionality improves collaborative efficiency among groups, whereas search result verification ensures the correctness and reliability of query results. On the other hand, DSSE needs to achieve forward and backward privacy to protect sensitive data. Forward privacy ensures that newly inserted vehicle data cannot be associated with historical search tokens. Backward privacy ensures that deleted vehicle data are not exposed in subsequent queries and that cloud servers cannot recover deleted data using current or future query information. Furthermore, the risks of collusion attacks between malicious users and cloud servers, as well as the robustness of the scheme, should be considered during design. Methods A state chain mechanism based on random numbers is designed to achieve forward privacy by ensuring that newly added data cannot be associated with historical search tokens. Meanwhile, a bitmap index-based construction method is adopted to achieve backward privacy and prevent information leakage from deleted data during subsequent queries. Furthermore, a dual bitmap index structure consisting of a keyword bitmap index and an operation bitmap index is constructed and combined with Boolean circuit technology to design a DSSE framework that simultaneously satisfies forward privacy, backward privacy, and robustness. The framework maintains stable system operation when facing abnormal or unreasonable update requests. In addition, an IDentity-based Key Encapsulation Mechanism (ID-KEM) is adopted to support multi-user scenarios where corrupted users and untrusted cloud servers may collude. This mechanism enables data owners to avoid storing additional information for authorized users, thereby reducing the storage overhead at the data owner’s side. Moreover, the cloud server is required to provide a proof of work based on verification labels when returning search results, enabling users to verify the integrity and correctness of the results. Results and Discussions The security of the RDSSE-CR scheme is demonstrated through a series of games between the real game $ \text{REAL}_{\mathcal{A}}^{\varPi }({1}^{\lambda }) $ and ideal game $ \mathrm{IDEAL}_{\mathcal{A}}^{\varPi }({1}^{\lambda }) $. First, by constructing games $ {G}_{0} $ to $ {G}_{7} $, the distinguishing capability of the adversary is gradually reduced. Under the assumptions of pseudorandom function security, hash function collision resistance, and symmetric encryption security, the distinguishing advantage of the adversary is proved to be negligible, demonstrating that the scheme achieves $ \mathcal{L} $ - adaptive security. Second, because search tokens are generated by a pseudorandom function bound to user identities, tokens generated by different users for the same keyword are independent and uncorrelated. Therefore, even under collusion attacks, adversaries cannot obtain the search tokens or private information of other authorized users. The experimental evaluation consists of performance analysis and Internet of Vehicles scenario simulation to assess the efficiency and practical applicability of the proposed scheme. In the performance test based on the Intel Core i7 environment, the RDSSE-CR scheme achieves the lowest storage overhead at both the data owner’s and data user’s sides among the compared schemes because both entities only need to maintain their own private keys ( Fig. 4 ). Regarding algorithm performance (Fig. 5 ), the RDSSE-CR scheme achieves high verification efficiency through efficient XOR operations while maintaining a constant search token size. Although the introduction of security mechanisms slightly increases the update and search costs, the scheme provides improved functionality and security. In the Internet of Vehicles simulation based on Simulation of Urban MObility (SUMO) and OMNeT++, the proposed scheme effectively resists attack interference and enables vehicle queues to maintain stable spacing and consistent speed under attacks (Fig. 6 ). This prevents vehicle lag and queue collapse observed without the proposed scheme, demonstrating its practical value in improving the safety and stability of the Internet of Vehicles in complex communication environments.Conclusions A verifiable multi-user dynamic searchable symmetric encryption scheme supporting forward and backward privacy is designed to meet the practical requirements of the Internet of Vehicles. To address security threats in multi-user environments where untrusted cloud servers and corrupted users may collude, the proposed scheme implements multi-user authorization based on ID-KEM and effectively resists collusion attacks. The RDSSE-CR scheme ensures system robustness against unreasonable operation requests by constructing a dual bitmap index structure combined with Boolean circuit design. During the search process, the cloud server generates a proof of work based on verification labels, allowing users to verify the correctness and integrity of search results. Future research will focus on efficient user revocation mechanisms to further improve the practicality and security of the scheme. -
表 1 具有鲁棒性的真值表
$ {\mathrm{bs}}_w[i] $ $ ({\rm{bs}}_a[i],{\mathrm{bs}}_b[i]) $ (0,0) (0,1) (1,1) (1,0) 0 0 0 1 0 1 1 1 1 0 
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1 ID-KEM
$ \text{Setup}({1}^{\lambda }) $ 1: $ m\leftarrow Z_{p}^{\ast } $ 2: $ \mathrm{\mathrm{mpk}}\leftarrow g^m $ 3: $ {\text{par}}\leftarrow \{e,g,p,G,{G}_{1},N,h,H\} $ $ \text{KeyGen(}u,\mathrm{\mathrm{msk}}) $ 1: $ \mathrm{\mathrm{msk}}\leftarrow m $ 2: $ {\mathrm{sk}}_{u_j}\leftarrow h(u_j)^m $ $ \text{Encap(}u,\mathrm{\mathrm{mpk}}) $ 1: $ n\leftarrow Z_{p}^{\ast } $ 2: $ {\mu }^{\prime}\leftarrow {g}^{n} $ 3: $ {\mu }_{j}\leftarrow ({\mu }^{\prime},j) $ 4: $ {r}_{j}\leftarrow H(e(h({u}_{j}),{({{g}^{m}})}^{n}),j) $ $ \text{Decap}({\mathrm{sk}}_u,\mu) $ 1: $ {r}_{j}\leftarrow H(e(h{({{u}_{j}})}^{m},{g}^{n}),j) $
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表 2 符号说明
符号 含义 par 系统公共参数 mpk 主公钥 msk 主私钥 $ {\mathrm{sk}}_{u_j} $ 授权用户$ {u}_{j} $的密钥 $ {\mu }_{j} $ 封装密文 $ {r}_{j} $ 封装密钥 $ {K}_{w} $ 关键字状态密钥 $ {K}^{\prime}_{w} $ 计数器密钥 $ \mathrm{\mathrm{\mathrm{ST}}}_c $ 关键字状态 $ \mathrm{\mathrm{\mathrm{UT}}}_c $ 加密索引 $ ({{\mathrm{bs}}}_a,{{\mathrm{bs}}}_b) $ 双位图索引 $ ({e}_{a},{e}_{b}) $ 加密双位图索引 $ C_{\rm{\mathrm{ST}}_c} $ 加密状态 $ {m}_{j} $ 封装的内容 vt 工作量证明 token 搜索令牌 $ \varGamma $ 3.3节中的密钥封装方案 $ {\mathrm{bs}}_w $ 聚合位图索引 $ {e}_{w} $ 加密聚合
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2 Setup
输入: $ \lambda ,{u}_{j} $ 输出: $ k,O,S,\mathrm{EDB},{\mathrm{par}},\mathrm{mpk},{\mathrm{msk}},{\mathrm{sk}}_{u_j} $ DO: 1: $ k\leftarrow {\{0,1\}}^{\lambda } $ 2: $ {O,S,{\mathrm{EDB}}}\leftarrow \mathrm{empty}\;\mathrm{map} $ 3: $ {{\mathrm{Send}} (S,{\mathrm{EDB}})\;{\mathrm{to}}\; {\mathrm{CS}}} $ 4: $ \text{Store (}k,{O) {\mathrm{in}}\; {\mathrm{DO}}} $ PKG: 5: $ \mathrm{userList}\leftarrow \{{u}_{1},{u}_{2},\cdots,{u}_{m}\} $ 6: $ ({\text{par}},{\mathrm{msk}},{\text{mpk}})\leftarrow \varGamma .{\text{Setup(1}}^{\lambda }) $ 7: $ \text{for all}\;{u}_{j}\;\text{in}\;\mathrm{user}\;{\mathrm{List}}\;\text{do} $ 8: ${\text{sk}}_{{{u}_{j}}}\leftarrow \varGamma .\mathrm{KeyGen}({u}_{j},{\text{msk}}) $ 9: end for 10: $ \text{Send}\; {\mathrm{sk}}_{u_j}{\text{to DU}}u_j $
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3 Update
输入: $ k,{\mathrm{mpk}},\text{userList},{\mathrm{op}},(w,{\mathrm{ind}}),{O} $ 输出: $ {m}_{j},{\mu }_{j},({K}_{w},{K}^{\prime}_{w}),c,{{\mathrm{ST}}}_{c},{{\mathrm{UT}}}_{c},{C}_{{{{\mathrm{ST}}}_{c}}},{\mathrm{vt}},({e}_{a},{e}_{b}) $ DO: 1: $ \mathrm{userList}\leftarrow \{{u}_{1},{u}_{2},\cdots,{u}_{m}\} $ 2: $ \text{AccessList,CList}\leftarrow \mathrm{empty}\mathrm{map} $ 3: $ ({\mu }_{j},{r}_{j})\leftarrow \varGamma .\mathrm{Encap}({u}_{j},{\mathrm{mpk}}) $ 4: $ \text{for all}\;w\;\text{in}W({u}_{j}\text{) do} $ 5: $ {K}_{w}||{K}^{\prime}_{w}\leftarrow F(k,w||{u}_{j}) $ 6: $ ({{\mathrm{ST}}}_{c},c)\leftarrow {O}[w] $ 7: $ {{\mathrm{if }}\;O}[w]=\bot \text{then} $ 8: $c\leftarrow -1,{{\mathrm{ST}}}_{c}\leftarrow {\{0,1\}}^{\lambda } $ 9: $ \text{end if} $ 10: $ {\rm{ST}}_{c}\leftarrow {\{0,1\}}^{\lambda },\text{where}c=c+1 $ 11: $ {O}[w]\leftarrow ({{\mathrm{ST}}}_{c},c) $ 12: $ {\mathrm{UT}}_{c}\leftarrow {H}_{1}({K}_{w},{\mathrm{ST}}_{c}) $ 13: $ {{C}}_{{{{\mathrm{ST}}}_{c}}}\leftarrow {H}_{2}({K}_{w},{{\mathrm{ST}}}_{c})\oplus {{\mathrm{ST}}}_{c-1} $ 14: $ { {\mathrm{Generate}}\; {\mathrm{the}}\; {\mathrm{bi-bitmap}} (}{\rm{bs}}_{a},\mathrm{b}{s}_{b}) $ based on 2.1
technology15: $ {e}_{a}\leftarrow {H}_{3}({K}^{\prime}_{w},c)\oplus {\rm{bs}}_{a} $ 16: $ {e}_{b}\leftarrow {H}_{4}({K}^{\prime}_{w},c)\oplus {\rm{bs}}_{b} $ 17: $ {\mathrm{vt}}\leftarrow {F}_{1}(w,c-1)\oplus {F}_{1}(w,c)\oplus {F}_{1}(w,{\mathrm{ind}})$ 18: $ \text{ AccessList}[{u}_{j}]\leftarrow (w,{K}_{w},{K}^{\prime}_{w},{\rm{ST}}_{c},c)$ 19: end for 20: $ {m}_{j}\leftarrow \text{SE.Enc}({r}_{j},\text{AccessList}[{u}_{j}])$ 21: $ \text{CList}[{u}_{j}]\leftarrow ({\mu }_{j},{m}_{j}) $ 22: $\mathrm{Send}({{\mathrm{UT}}}_{c},({e}_{a},{e}_{b},{{C}}_{{{{\mathrm{ST}}}_{c}}},{\mathrm{vt}}))\text{and CList}[{u}_{j}]\mathrm{to}\text{CS} $ CS: 23: $ \text{EDB[}{{\mathrm{UT}}}_{c}]\leftarrow ({e}_{a},{e}_{b},{{C}}_{{{{\mathrm{ST}}}_{c}}},{\mathrm{vt}}) $
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4 Search
输入: $ {\rm{sk}}_{{{u}_{j}}},\text{CList}[{u}_{j}],{{\mathrm{EDB}},S,{\mathrm{AccessList}}}[{u}_{j}] $ 输出： $ {E},{e}_{w},{{\mathrm{EDB}},S,}{\mathrm{proof}},{\mathrm{ind}}\text{s} $ DU: 1: $ \text{Receive}({\mu }_{j},{m}_{j})\text{from CS} $ 2: $ {r}_{j}\leftarrow \varGamma .\text{Decap}({\rm{sk}}_{{{u}_{j}}},{\mu }_{j}) $ 3: $ \text{AccessList}[{u}_{j}]\leftarrow \text{SE.Dec}({r}_{j},{m}_{j}) $ 4: $ (w,{K}_{w},{K}^{\prime}_{w},{\rm{ST}}_{c},c)\leftarrow \text{AccessList}[{u}_{j}] $ 5: $ \mathrm{if}({\rm{ST}}_{c},c)=\bot \text{then} $ 6: $ \text{return}\varnothing $ 7: end if 8: $ \mathrm{\mathrm{token}}\leftarrow(K_w,{\mathrm{ST}}_c,c) $ 9: $ \mathrm{Send}\;{\mathrm{token}}\;\mathrm{to}\;\text{CS} $ CS: 10: $ \text{1if}\;S[{K}_{w}] =\mathrm{Null}\text{then} $ 11: $ {e}_{w}\leftarrow {0}^{n} $ 12: else 13: ${e}_{w}\leftarrow {S}[{K}_{w}] $ 14: end if 15: $ {E}\leftarrow \text{empty map} $ 16: $ \text{for}\;i=c\;\text{to}\;0\;\text{do}$ 17: $ {\rm{UT}}_{i}\leftarrow {H}_{1}({K}_{w},{\rm{ST}}_{i})$ 18: $ ({e}_{a},{e}_{b},{{C}}_{{{{\mathrm{ST}}}_{i-1}}},{\mathrm{vt}})\leftarrow \text{EDB[}{\rm{UT}}_{i}] $ 19: $ {E}[i-{c}_{0}]\leftarrow ({e}_{a},{e}_{b}) $ 20: $ \mathrm{\mathrm{proof}}\leftarrow\mathrm{\mathrm{proof}}\oplus\mathrm{vt} $ 21: $ \text{ Remove EDB[}{\mathrm{UT}}_i] $ 22: $ \mathrm{if}\;{{C}}_{{{{\mathrm{ST}}}_{i-1}}}=\bot \text{then} $ 23: Break 24: end if 25: $ {\rm{ST}}_{i-1}\leftarrow {H}_{2}({K}_{w},{\rm{ST}}_{i})\oplus {\mathrm{C}}_{{{{\mathrm{ST}}}_{i-1}}}$ 26: end for 27: $ \text{EDB[}{\rm{UT}}_{c}]\leftarrow ({e}_{a},{e}_{b},{{C}}_{{{{\mathrm{ST}}}_{c-1}}},{\mathrm{vt}}) $ 28: $ \mathrm{Send}({e}_{w},\text{E,}{\mathrm{proof}})\mathrm{to}\text{DU}$ DU: 29: $ {\rm{bs}}_{w}\leftarrow {0}^{n}\$ 30: $ \text{if}\;{e}_{w}\neq {0}^{n}\text{then} $ 31: $ {\rm{bs}}_{w}\leftarrow {H}_{5}({{{K}^{\prime}}}_{w},c)\oplus {e}_{w} $ 32: end if 33: $ \text{for}\;i =0\;\text{to}\;c\;\text{do} $ 34: $ ({e}_{a},{e}_{b})\leftarrow {E}[i]$ 35: $ {\rm{bs}}_{a}\leftarrow {e}_{a}\oplus {H}_{3}({K}^{\prime}_{w},i) $ 36: $ {\rm{bs}}_{b}\leftarrow {e}_{b}\oplus {H}_{4}({K}^{\prime}_{w},i)$ 37: $ {\rm{bs}}_{w}\leftarrow (\overline{{\rm{bs}}_{a}}\wedge {\rm{bs}}_{w})\oplus ({\rm{bs}}_{a}\wedge {\rm{bs}}_{b}) $ 38: end for 39: $ {e}_{w}\leftarrow {\rm{bs}}_{w}\oplus {H}_{5}({K}^{\prime}_{w},c+1) $ 40: $ \text{Send}\;{e}_{w}\text{to CS} $ 41: $ \mathrm{Parse}\;{\rm{bs}}_{w}\;\text{into file identifiers}\;{\mathrm{ind}}\text{s} $ 42: $ \mathrm{Return}\;{\mathrm{ind}}\text{s} $ CS: 43: $ {S}[{K}_{w}]\leftarrow {e}_{w} $
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5 Verify
输入： $ w,\mathrm{\mathrm{ind}\text{s}},\text{AccessList}[u_j],\mathrm{\mathrm{proof}} $ 输出: $ \mathrm{\mathrm{accept}/}\mathrm{\mathrm{reject}} $ DU: 1: $ (w,{K}_{w},{{{K}^{\prime}}}_{w},{\rm{ST}}_{c},c)\leftarrow \text{AccessList}[{u}_{j}] $ 2: $ {\mathrm{proof}}'\leftarrow {F}_{1}(w,0)\oplus {F}_{1}(w,c) $ 3: $ \text{for each}\;{\mathrm{ind}}\;\text{in}\;{\mathrm{inds}}\text{do} $ 4: $ {\mathrm{proof}}'\leftarrow {\mathrm{proof}}'\oplus {F}_{1}(w,{\mathrm{ind}}) $ 5: end for 6: $ \text{if}\;{\mathrm{proof}} ={\mathrm{proof}}'\text{then} $ 7: $ \mathrm{\text{return}\; \mathrm{accept}} $ 8: else 9: $ \mathrm{\text{return}\; \mathrm{reject}} $ 10: end if
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6 Simulator
Setup DO: 1: $ {O,S,{\mathrm{EDB}}}\leftarrow \mathrm{empty}\mathrm{map} $ 2: $ {{\mathrm{Send}} (S,{\mathrm{EDB}}) \;{\mathrm{to}} \;{\mathrm{CS}} \;{\mathrm{and}}\; {\mathrm{keep}}\; {\mathrm{others}} \;{\mathrm{locally}}} $ 3: $ \mathrm{userList}\leftarrow \{{u}_{1},{u}_{2},\cdots,{u}_{m}\} $ 4: $ ({\mathrm{par}},{\mathrm{msk}},{\mathrm{mpk}})\leftarrow \varGamma .{\text{Setup(1}}^{\lambda }) $ 5: $ \text{for all}{u}_{j}\text{in}\mathrm{userList}\text{do} $ 6:$ {\rm{sk}}_{{{u}_{j}}}\leftarrow \varGamma .\mathrm{KeyGen}({u}_{j},{\mathrm{msk}}) $ 7:$ \text{end for} $ 8:$ \text{Send}\;{\rm{sk}}_{{{u}_{j}}}\text{to DU}{u}_{j} $ Update DO: 1: $ {\mathrm{ts}}\leftarrow {\mathrm{ts}}+1 $ 2: $ {\rm{ST}}_{c}\leftarrow {\{0,1\}}^{\lambda } $ 3: $ {{T}}_{1}[{\mathrm{ts}}]\leftarrow {\{0,1\}}^{\lambda } $ 4: $ {{T}}_{2}[{\mathrm{ts}}]\leftarrow {\{0,1\}}^{\lambda } $ 5: $ \text{Generate the bi-bitmap (}{\rm{bs}}_{a},{\rm{bs}}_{b}) $ 6: $ {{T}}_{3}[{\mathrm{ts}}]\leftarrow {\{0,1\}}^{\lambda } $ Search DU: 1: $ {\mathrm{ts}}\leftarrow {\mathrm{ts}}+1 $ 2: $ \tilde{w}\leftarrow \min \text{sp(}w) $ 3: $ \text{Parse Ti(}w\text{) as}({\rm{ts}}_{0},\cdots,{\rm{ts}}_{c}) $ 4: $ {K}_{\tilde{w}}||{{{K}^{\prime}}}_{\tilde{w}}\leftarrow {{T}}_{F}(\tilde{w}) $ 5: $ \text{for}\;i=c\;\text{to 0 do}$ 6: $ {\rm{ST}}_{i-1}\leftarrow \{0,1\}^{\lambda }$ 7: $\text{ Program}\;{H}_{1}({K}_{\tilde{w}},{\rm{ST}}_{i})\leftarrow {{T}}_{1}[{\rm{ts}}_{i}]$ 8: $ \text{Program}\;{H}_{2}({K}_{\tilde{w}},{\rm{ST}}_{i})\leftarrow {{T}}_{2}[{\mathrm{ts}}]\oplus {\rm{ST}}_{i-1} $ 9: $ \text{Program}\;{H}_{3}({K}^{\prime}_{\tilde{w}},i)\leftarrow {{T}}_{3}[{\mathrm{ts}}] $ 10: $ \text{Program}\;{H}_{4}({K}^{\prime}_{\tilde{w}},i)\leftarrow {{T}}_{4}[{\mathrm{ts}}] $ 11: $ {\mathrm{proof}} \leftarrow {\mathrm{proof}} \oplus {\text{VT}}[{\mathrm{ts}}] $ 12: end for 13: $ \text{Program}\;{H}_{5}({{{K}^{\prime}}}_{\tilde{w}},i+1)\leftarrow {{T}}_{5}[{\mathrm{ts}}] $ 14: $ \mathrm{Send}({K}_{\tilde{w}},{\rm{ST}}_{c},c)\mathrm{to}\;\text{CS} $ 15: $ \text{Return rp(}w) $ Verify DU: 1: $ {\mathrm{proo}}{f}^{\prime}\leftarrow {{T}}_{{{F}_{1}}}[0]\oplus {{T}}_{{{F}_{1}}}[c] $ 2: $ \text{for each}\;{\mathrm{ind}}\;\text{in rp}[w]\text{do} $ 3: $ {{\mathrm{proof}}}^{\prime}\leftarrow {{\mathrm{proof}}}^{\prime}\oplus {{T}}_{{{F}_{1}}}[{\mathrm{ind}}]$ 4: end for 5: $ \mathrm{if}\;{\mathrm{proof}}={{\mathrm{proof}}}^{\prime}\;\text{then} $ 6: $ \text{return}\;{\mathrm{accept}} $ 7: else 8: $ \text{return}\;{\mathrm{reject}} $ 9: end if
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表 3 功能性与复杂度对比
方案 多用户 结果可验证 前向隐私 后向隐私 抗合谋 鲁棒性 更新复杂度 搜索复杂度 验证复杂度 $ \text{Q-}\mu \text{SE} $(2020)[31] √ × √ Type-II √ × $ O(|\text{DB}|)\cdot F $ $ O({R}_{w})\cdot F $ - NIMS(2023)[10] √ × √ Type-III × × $ O(|\mathrm{DB}|+|W|)\cdot F $ $ O({a}_{w}+|W|) $ - FBVDSSE(2025)[21] × √ √ Type-II × × $ O(|\mathrm{DB}|)\cdot (F+{\mathrm{Exp}}) $ $ O({R}_{w})\cdot (F+{\mathrm{Exp}}) $ $ O(R_w)\cdot\mathrm{\mathrm{Exp}} $ RDSSE-CR √ √ √ Type-I– √ √ $ O(|\mathrm{DB}|)\cdot (F+{\mathrm{Hash}}) $ $ O({R}_{w})\cdot (F+{\mathrm{Hash}}) $ $ O({R}_{w})\cdot F $ 注：$ F $和$ {\mathrm{Hash}} $分别表示伪随机函数和哈希函数。$ {R}_{w} $表示对应关键字w的搜索结果的大小，$ {a}_{w} $和$ {R}_{w} $分别表示关键字w的更新总数和对应关键字w的搜索结果的大小。|W|和|DB|分别表示关键字的总数和关键字/文档对的数量。$ {\mathrm{Exp}} $表示幂运算。
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表 4 参数配置
参数 值 队列规模 6 速度 24 m/s 默认间距 20 m 车道数量 4 高速公路长度 18 km 模拟时间 100 s 网络协议 LTE-V2X 消息大小 256 Byte
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