计算机科学
加密
身份(音乐)
欺骗攻击
认证(法律)
公钥密码术
模糊逻辑
密文
钥匙(锁)
模糊集
计算机安全
算法
计算机网络
理论计算机科学
人工智能
物理
声学
作者
Ye Chen,Yubo Song,Yihan Cai,Qiuhong Shan,Bo Zhang,Tao Zhang
标识
DOI:10.1109/hpcc-dss-smartcity-dependsys60770.2023.00084
摘要
Identity-Based Encryption algorithm generates public-private key with identity, reduces the key management complexity of IoT devices. However, traditional IBE algorithm is vulnerable to spoofing attacks. This paper proposes a novel Fuzzy Identity-Based Encryption algorithm, defines the fuzzy identity as an attribute set composed of multidimensional physical features of IoT devices. The algorithm extracts device fuzzy identity from their unique physical characteristics, establish a linkage between device physical attributes and logical identity. Moreover, this paper introduces the concept of fuzziness to overcome the impact of physical noise. We calculate the fuzziness of individual attributes within the attribute set, as well as the overall fuzziness among the sets to match fuzzy identity. To achieve low-cost device identity authentication for multiple wireless IoT devices in a contactless scenario, this paper proposes a Physical Unclonable Function to extract device-related physical attributes based on Channel State Information. The stimuli response of the PUF constitute the fuzzy identity of IoT devices. Formal security analysis indicates that the security of our method can be reduced to the hardness of the Decisional Modified Bilinear Diffie-Hellman (MBDH) assumption and provides Chosen Ciphertext Attack security. Our approach achieves a 96.9% success rate in extracting public-private keys despite physical noise, even in scenarios with concurrent access by multiple wireless IoT devices.
科研通智能强力驱动
Strongly Powered by AbleSci AI