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'<p data-vmark="93d6"></p><p data-vmark="8743">数字经济时代, 数据已经成为企业的重要资产, 企业对数据的保护意识日益增强, 甚至频频出现画地为牢的现象。然而, 数据作为第五大生产要素, 其价值需在流通、共享环节进行释放。为解决这种"数据孤岛"问题, 隐私计算应运而生, 并在近几年成为业界关注的热点领域。</p><p data-vmark="700a">在风险评估等业务中, 实现数据的"共用但不共享, 可用而不可见"是非常迫切的需求。通过隐私计算利用多家企业的多维数据训练人工智能模型, 既能保护各方原始数据不出私域、保护用户隐私信息不泄露, 又能帮助模型具有更高的准确率及更好的模型效果。</p><p data-vmark="e58f">洞见科技正是隐私计算领域的领军力量之一。洞见科技是由中国最大、世界第四大的信用管理集团"中诚信"投资孵化的领先的隐私计算技术服务商, 聚焦于为政务、金融等客户提供基于隐私计算生态底座建设及面向场景的数据智能服务, 已取得数十个典型示范案例。</p><p data-vmark="fdf1">洞见科技提供的联邦学习服务和多方安全计算服务, 是隐私计算的重要实现路径, 能满足企业参与数据共享协作时的安全计算需求。不过, 在落地过程中, 隐私计算服务商往往面临着需要自证可信、算力需求量大且波动、网络质量要求高等痛点。因此, 洞见科技与阿里云携手合作, 为客户提供了基于阿里云的隐私计算服务解决方案, 有效解决了上述问题。</p><p data-vmark="d019">首先是信任。联邦学习服务中的聚合计算环节需要向参与方企业提供更多的信任依据, 阿里云今年刚发布的第七代 ECS, 配备芯片级可信计算能力, 企业从实例启动直至模型部署, 均加入相关校验, 确保其中无人篡改模型或计算逻辑, 解决了基础的信任问题。</p><p data-vmark="a680">其次, 在计算量大且波动大这一点上, 隐私计算与常见的大数据、AI 等计算无异。TEE 可信执行环境是该领域主流技术之一。原有的第一代技术仅有 512M 大小, 计算能力太低, 几乎难以满足商用。同时, 客户基于线下计算资源承载计算任务时, 往往会遭遇算力不足的情况, 计算任务需排队执行, 影响了业务运转的效率。</p><p data-vmark="ee62">阿里云七代 ECS 实现了将第二代 TEE 技术部署在云上, 对外提供基于硬件的加密计算能力, 算力容量大大提升, 并提供了虚拟化层面的自研神龙 enclave 方案。利用供应充足并且弹性灵活的云上算力, 洞见科技可以根据任务情况按需创建和释放云服务器, 保证快速交付计算结果, 又能精细化控制计算资源, 降低了持有服务器的成本并实现成本优化。</p><p data-vmark="66c3">在第三点网络问题上, 可以想象, 在多方参与的计算过程中, 必然涉及到大量的数据传输, 网络将成为瓶颈之一, 当参与各方所在地分散时, 问题尤为明显。阿里云作为全球前三、国内第一的云厂商, 在世界各地均有海量的计算资源与高速可达的网络, 云的多可用区与多地域布局, 让数据得以就近上传, 洞见科技无需让客户进行代理机配置等繁琐操作。</p><p data-vmark="6c19"></p><p data-vmark="6413">最后, 云上灵活的调度能力和自动化运维能力, 让洞见科技得以帮助客户方便地进行资源扩充和迁移, 大大降低了运维成本。</p><p data-vmark="157c">洞见科技联合创始人兼 CTO 何浩表示:"依托阿里云第七代实例的可信和加密计算能力, 洞见科技可以为客户设计更多技术信任加持的隐私计算解决方案, 提供稳定可靠、灵活调度的算力来源, 更好地帮助政务、金融等客户打破数据孤岛, 赋能数据价值的安全释放和数据智能的合规应用。"</p><p data-vmark="e572">阿里云弹性计算产品总监王志坤表示:"我们看到, 客户对安全的追求是永无止境的, 从存储和传输期间的安全, 到今天计算过程中的数据安全需求兴起, 是技术也是市场共同发展的必然结果。隐私计算作为新兴的计算需求, 阿里云非常高兴能携手洞见科技一同开拓这个市场。"</p>' |
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