With the rapid development of the Artificial Intelligence of Things(AIoT),convolutional neural networks(CNNs)have demonstrated potential and remarkable performance in AIoT applications due to their excellent performan...With the rapid development of the Artificial Intelligence of Things(AIoT),convolutional neural networks(CNNs)have demonstrated potential and remarkable performance in AIoT applications due to their excellent performance in various inference tasks.However,the users have concerns about privacy leakage for the use of AI and the performance and efficiency of computing on resource-constrained IoT edge devices.Therefore,this paper proposes an efficient privacy-preserving CNN framework(i.e.,EPPA)based on the Fully Homomorphic Encryption(FHE)scheme for AIoT application scenarios.In the plaintext domain,we verify schemes with different activation structures to determine the actual activation functions applicable to the corresponding ciphertext domain.Within the encryption domain,we integrate batch normalization(BN)into the convolutional layers to simplify the computation process.For nonlinear activation functions,we use composite polynomials for approximate calculation.Regarding the noise accumulation caused by homomorphic multiplication operations,we realize the refreshment of ciphertext noise through minimal“decryption-encryption”interactions,instead of adopting bootstrapping operations.Additionally,in practical implementation,we convert three-dimensional convolution into two-dimensional convolution to reduce the amount of computation in the encryption domain.Finally,we conduct extensive experiments on four IoT datasets,different CNN architectures,and two platforms with different resource configurations to evaluate the performance of EPPA in detail.展开更多
研究聚焦于盐城市人工智能物联网(Artificial Intelligence Internet of Things,AIoT)驱动的智慧温室系统开发,旨在通过数字化手段提升草莓种植效能与品质。针对传统种植模式中资源浪费和管理粗放等问题,系统构建了“环境感知-智能调控...研究聚焦于盐城市人工智能物联网(Artificial Intelligence Internet of Things,AIoT)驱动的智慧温室系统开发,旨在通过数字化手段提升草莓种植效能与品质。针对传统种植模式中资源浪费和管理粗放等问题,系统构建了“环境感知-智能调控-管理优化”三位一体解决方案。通过多模态传感器实时监测环境参数,结合OpenHarmony系统的边缘-云端协同处理及规则引擎与机器学习算法,动态调控作物最佳生长环境。实验表明,智慧温室通过高效数据处理与精准恒温调控,提升了草莓产量与品质。展开更多
在数字化转型背景下,传统财务审计模式受限于数据孤岛与流程滞后,难以应对复杂经济场景的需求。研究整合区块链与人工智能物联网(Artificial Intelligence&Internet of Things,AIoT)技术,构建分布式财务审计系统框架。实证分析显示...在数字化转型背景下,传统财务审计模式受限于数据孤岛与流程滞后,难以应对复杂经济场景的需求。研究整合区块链与人工智能物联网(Artificial Intelligence&Internet of Things,AIoT)技术,构建分布式财务审计系统框架。实证分析显示,该系统显著提升审计效率,并借助链上数据不可篡改特性将人为舞弊风险降低至5%以下,尤其在供应链金融与跨国税务稽查场景中展现出强适应性。展开更多
基金supported by the Natural Science Foundation of China No.62362008the Major Scientific and Technological Special Project of Guizhou Province([2024]014).
文摘With the rapid development of the Artificial Intelligence of Things(AIoT),convolutional neural networks(CNNs)have demonstrated potential and remarkable performance in AIoT applications due to their excellent performance in various inference tasks.However,the users have concerns about privacy leakage for the use of AI and the performance and efficiency of computing on resource-constrained IoT edge devices.Therefore,this paper proposes an efficient privacy-preserving CNN framework(i.e.,EPPA)based on the Fully Homomorphic Encryption(FHE)scheme for AIoT application scenarios.In the plaintext domain,we verify schemes with different activation structures to determine the actual activation functions applicable to the corresponding ciphertext domain.Within the encryption domain,we integrate batch normalization(BN)into the convolutional layers to simplify the computation process.For nonlinear activation functions,we use composite polynomials for approximate calculation.Regarding the noise accumulation caused by homomorphic multiplication operations,we realize the refreshment of ciphertext noise through minimal“decryption-encryption”interactions,instead of adopting bootstrapping operations.Additionally,in practical implementation,we convert three-dimensional convolution into two-dimensional convolution to reduce the amount of computation in the encryption domain.Finally,we conduct extensive experiments on four IoT datasets,different CNN architectures,and two platforms with different resource configurations to evaluate the performance of EPPA in detail.
文摘研究聚焦于盐城市人工智能物联网(Artificial Intelligence Internet of Things,AIoT)驱动的智慧温室系统开发,旨在通过数字化手段提升草莓种植效能与品质。针对传统种植模式中资源浪费和管理粗放等问题,系统构建了“环境感知-智能调控-管理优化”三位一体解决方案。通过多模态传感器实时监测环境参数,结合OpenHarmony系统的边缘-云端协同处理及规则引擎与机器学习算法,动态调控作物最佳生长环境。实验表明,智慧温室通过高效数据处理与精准恒温调控,提升了草莓产量与品质。
文摘在数字化转型背景下,传统财务审计模式受限于数据孤岛与流程滞后,难以应对复杂经济场景的需求。研究整合区块链与人工智能物联网(Artificial Intelligence&Internet of Things,AIoT)技术,构建分布式财务审计系统框架。实证分析显示,该系统显著提升审计效率,并借助链上数据不可篡改特性将人为舞弊风险降低至5%以下,尤其在供应链金融与跨国税务稽查场景中展现出强适应性。
