Poly (EA-MAn-APTES)/silica hybrid materials were successfully prepared fromEthyl acrylate (EA), maleic anhydride (MAn) and tetraethoxysilane (TEOS) in the presence of acoupling agent 3-aminopropyltriethoxysilane (APTE...Poly (EA-MAn-APTES)/silica hybrid materials were successfully prepared fromEthyl acrylate (EA), maleic anhydride (MAn) and tetraethoxysilane (TEOS) in the presence of acoupling agent 3-aminopropyltriethoxysilane (APTES),by free-radical solution polymerization and insitu sol-gel process. The mass fraction of TEOS varied from 0 to 25%. The hybrid materials werecharacterized by the methods of FT-IR spectra, solvent extraction, scanning electron microscope (SEM), transmission electron microscope (TEM), differential scanning calorimetry (DSC) andthermogravimetric analysis (TGA) measuring apparatus to get their structures, gel contents,morphologies, particle sizes and thermal performances. The results show that the covalent bonds arebetween organic and inorganic phases, gel contents in the hybrid materials are much higher, theSiO_2 phase is well dispersed in the polymer matrix, silicon dioxide exist at nanoscale in thecomposites and have excellent thermal stability.展开更多
新一代信息技术与工业系统深度融合,提升了工业控制系统和工业设备网络的连接性,使得工业互联网成为APT攻击的重点目标.针对现有偏向于静态认证的方法难以识别APT攻击者控制内部失陷终端获取的“傀儡身份”,进而造成敏感数据泄露的问题...新一代信息技术与工业系统深度融合,提升了工业控制系统和工业设备网络的连接性,使得工业互联网成为APT攻击的重点目标.针对现有偏向于静态认证的方法难以识别APT攻击者控制内部失陷终端获取的“傀儡身份”,进而造成敏感数据泄露的问题,提出一种面向工业互联网的零信任动态认证方案.融合CNN-BiLSTM构建混合神经网络,利用其时序特性设计行为因子预测模型.通过多个残差块组成的深度卷积网络提取特征,双向长短时记忆网络(bidirectional long short-term memory,BiLSTM)进行时间序列分析,生成对主体的行为因子预测,作为零信任动态认证重要凭据.为快速识别“傀儡身份”,融入行为因子设计IPK-SPA动态认证机制.利用轻量级标识公钥技术适应工业互联网海量末梢,借助零信任单包授权技术隐藏工控网络边界.安全性分析和实验结果表明,提出的动态认证方案具有较好的“傀儡身份”识别能力,有助于抗击工业互联网环境下因APT攻击者窃取身份导致的数据窃密威胁.展开更多
文摘Poly (EA-MAn-APTES)/silica hybrid materials were successfully prepared fromEthyl acrylate (EA), maleic anhydride (MAn) and tetraethoxysilane (TEOS) in the presence of acoupling agent 3-aminopropyltriethoxysilane (APTES),by free-radical solution polymerization and insitu sol-gel process. The mass fraction of TEOS varied from 0 to 25%. The hybrid materials werecharacterized by the methods of FT-IR spectra, solvent extraction, scanning electron microscope (SEM), transmission electron microscope (TEM), differential scanning calorimetry (DSC) andthermogravimetric analysis (TGA) measuring apparatus to get their structures, gel contents,morphologies, particle sizes and thermal performances. The results show that the covalent bonds arebetween organic and inorganic phases, gel contents in the hybrid materials are much higher, theSiO_2 phase is well dispersed in the polymer matrix, silicon dioxide exist at nanoscale in thecomposites and have excellent thermal stability.
文摘新一代信息技术与工业系统深度融合,提升了工业控制系统和工业设备网络的连接性,使得工业互联网成为APT攻击的重点目标.针对现有偏向于静态认证的方法难以识别APT攻击者控制内部失陷终端获取的“傀儡身份”,进而造成敏感数据泄露的问题,提出一种面向工业互联网的零信任动态认证方案.融合CNN-BiLSTM构建混合神经网络,利用其时序特性设计行为因子预测模型.通过多个残差块组成的深度卷积网络提取特征,双向长短时记忆网络(bidirectional long short-term memory,BiLSTM)进行时间序列分析,生成对主体的行为因子预测,作为零信任动态认证重要凭据.为快速识别“傀儡身份”,融入行为因子设计IPK-SPA动态认证机制.利用轻量级标识公钥技术适应工业互联网海量末梢,借助零信任单包授权技术隐藏工控网络边界.安全性分析和实验结果表明,提出的动态认证方案具有较好的“傀儡身份”识别能力,有助于抗击工业互联网环境下因APT攻击者窃取身份导致的数据窃密威胁.
