Edge-Cloud Collaborative Searchable Attribute-Based Signcryption Approach for Internet of Vehicles
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摘要: 动态开放的网络环境使车联网难免遭受窃听、数据篡改和伪造，传统云计算因高延迟难以满足海量数据的实时性需求，安全性和性能之间固有冲突制约着车联网发展。为了解决上述问题，该文专为车联网设计出边云协同可搜索属性签密方法，可允许授权用户无需解密密文，就能通过云端快速匹配机制高效检索所需信息。利用边缘计算下沉计算能力到网络边缘，协同云服务器、边缘服务器和车载终端设备共同工作。通过属性签密和线性秘密共享机制的融合，实现车联网数据的细粒度访问控制，更好保障数据的安全性。针对车载设备资源受限问题，解签密过程中的复杂运算外包给高性能边缘节点处理，减轻了车载终端的运算负担且提升了响应速度，能够很好适应车联网这种动态的资源受限复杂环境。Abstract:
Objective Dynamic and open environment of IoV brings the challenges for data security and real-time performance. Massive data interactions are vulnerable to malicious eavesdropping, tampering, forgery and replay attacks. Traditional cloud computing has inherent high latency and fails to meet millisecond-level real-time IoV demands, this leads to inefficient data transmission and potential traffic accident. Balancing of data security and real-time performance is critical bottleneck for large-scale deployment of IoV. Methods Edge-cloud collaborative searchable attribute-based signcryption method is proposed for IoV, it establishes multi-layer architecture including the cloud servers, edge servers and in-vehicle terminal devices. Access control is enforced by hybrid key and ciphertext policy from attribute-based signcryption and LSSS. To mitigate local decryption burden, bilinear operations are outsourced to edge nodes. SM9 is employed for trapdoor generation and signature authentication. Proposed method has the confidentiality, signature unforgeability and trapdoor unforgeability. Results and Discussions Our method has the superiority in IoV edge-cloud collaborative architecture for searchable attribute-based signcryption ( Tables 1 and4 ). Functional characteristics are inTable 1 .Figure 2 shows the change trend of total time as the number of attributes increases; total time of our method increases slightly but the growth rate is very slow; for effective outsourcing of intensive computing tasks to edge nodes, our method reduces local computing burden on user terminals. This calculation optimization is quantified by OE exceeding 96% (Table 4 ,Fig.5 ). Our method achieves an instantaneous retrieval capability by optimizing the search complexity to O(1) (Fig.4 ) using hash index. E2E search latency is controlled to acceptable level in IoV applications (Table 6 ), verifying its applicability for real-time data access. Known fromFigure 3 , with the increase of the number of attributes, the variation range of ciphertext size of our method is the smallest.Conclusions Our method achieves fine-grained access control, data confidentiality, integrity, and unforgeability, and it exhibits the advantages in computation and communication efficiency. By computation offloading mechanism, our method effectively addresses the resource constraints of on-board devices for dynamic, resource-sensitive and real-time IoV environments. -
表 2 运算符号说明(ms)
符号及含义 执行一次双线性对操作: $ 1{T}_{\mathrm{p}} $ 执行一次指数操作:$ {1T}_{\mathrm{e}} $ 执行一次乘法操作:$ 1{T}_{\mathrm{m}} $ 执行一次哈希函数操作:$ 1{T}_{\mathrm{h}} $ 耗时 4.843 7.941 0.043 0.003 
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表 3 计算开销分析
对比方法 总体时间开销 密文大小 文献[9] $ (4+4n){T}_{\mathrm{e}}+3{T}_{\mathrm{m}}+{T}_{\mathrm{h}}+{T}_{\mathrm{p}} $ $ \left(\begin{matrix}2n+7\\ \end{matrix}\right)\left| {G}_{1}\right| $ 文献[10] $ {(6n+10)T}_{\mathrm{e}}+{T}_{\mathrm{m}}+2{T}_{\mathrm{p}}+(3n+2){T}_{\mathrm{h}} $ $ 4\left| {Z}_{p}\right| +6\left| {G}_{1}\right| +\left(n+1\right)\left| {G}_{\mathrm{T}}\right| $ 文献[11] $ {\left(3n+7\right){{T}_{\mathrm{e}}}+3T}_{\mathrm{h}}+(n+5){T}_{\mathrm{m}}+4{T}_{\mathrm{p}} $ $ 2\left| {Z}_{p}\right| +(2n+3)\left| {G}_{1}\right| $ ECCSABSCM $ 2{T}_{\mathrm{e}}+\left(4n+9\right){T}_{\mathrm{m}}+(n+4{)T}_{\mathrm{p}}+(2n+5){T}_{\mathrm{h}} $ $ \left| {Z}_{p}\right| +\left(n+2\right)\left| {G}_{1}\right| +2\left| {G}_{2}\right| $
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表 4 解签密计算任务外包效率分析
属性数量 $ 10 $ $ 30 $ $ 50 $ 70 90 $ {T}_{\mathrm{t}}(\text{ms}) $ 108.71 306.66 504.64 702.63 900.60 $ {T}_{\mathrm{r}}(\text{ms}) $ 16.66 20.92 25.18 29.44 33.70 $ \text{OE}(\% ) $ 84.67 93.18 95.01 95.81 96.26
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表 5 端到端搜索延迟构成(ms)
属性数量 $ 10 $ $ 30 $ $ 50 $ 70 90 $ {T}_{\text{Calc}} $ 137.31 337.86 538.43 738.99 939.55 $ {T}_{\text{Comm}} $ 80.00 80.00 80.00 80.00 80.00 $ {T}_{\mathrm{E}2\mathrm{E}} $ 217.31 417.86 618.43 818.99 1019.55
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