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< h1 id = "Carving-Database-Storage-to-Detect-and-Trace-Security-Breaches" > < a href = "#Carving-Database-Storage-to-Detect-and-Trace-Security-Breaches" class = "headerlink" title = "Carving Database Storage to Detect and Trace Security Breaches" > < / a > Carving Database Storage to Detect and Trace Security Breaches< / h1 > < blockquote >
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< p > 复原数据库存储以检测和跟踪安全漏洞< br > < a href = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555312497/paper/2016-paper_carving_database_storage_to_detect_and.pdf" target = "_blank" rel = "noopener" > 原文下载< / a > < / p >
< / blockquote >
< h2 id = "Motivation" > < a href = "#Motivation" class = "headerlink" title = "Motivation" > < / a > Motivation< / h2 > < h3 id = "DBMS-数据库管理系统" > < a href = "#DBMS-数据库管理系统" class = "headerlink" title = "DBMS(数据库管理系统)" > < / a > DBMS(数据库管理系统)< / h3 > < ul >
< li > 通常用于存储和处理敏感数据， ， < / li >
< li > 一旦用户在DBMS中获得提升权限（ ） ， ， < br > 1） ， < br > 2） < / li >
< li > 部署预防措施< br > 1） < br > 2） ， < / li >
< / ul >
< h3 id = "例子" > < a href = "#例子" class = "headerlink" title = "例子" > < / a > 例子< / h3 > < p > Malice是政府机构的数据库管理员， ， ， ‘ ’ < br > 但是， ， ， ， ， < br > 但是，磁盘上的数据库存储仍将包含已删除行的证据。< br > 作者的方法检测已删除的痕迹和过期的记录版本，并将它们与审核日志进行匹配，以检测此类攻击，并提供数据库操作方式的证据。< br > 作者将检测已删除的行，因为它与审计日志中的任何操作都不对应，我们会将其标记为篡改的潜在证据。< br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555310640/paper/%E5%9B%BE%E7%89%871.png" alt > < / p >
< h3 id = "思路一览" > < a href = "#思路一览" class = "headerlink" title = "思路一览" > < / a > 思路一览< / h3 > < p > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555310736/paper/%E6%8D%95%E8%8E%B7.png" alt > < / p >
< h3 id = "提出方法" > < a href = "#提出方法" class = "headerlink" title = "提出方法" > < / a > 提出方法< / h3 > < p > 使用称为DICE的现有取证工具（ ， ） < br > 通过匹配提取的存储条目，报告任何无法通过操作记录解释的工件来自动检测潜在的攻击< / p >
< ol >
< li > DBDetective检查数据库存储和RAM快照， < / li >
< li > 然后，在不影响数据库操作的情况下，对核心数据进行分析。< br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555310863/paper/%E5%9B%BE%E7%89%872.png" alt > < / li >
< / ol >
< p > 确定数据库篡改的可能性，并指出数据库存储中发现的具体不一致性。< br > 由于数据库存储的易变性，无法保证将发现所有攻击。< br > 在对于我们评估的每个主要DBMS， < br > 我们进一步假设一名攻击者通过以下方式阻止记录已执行的恶意命令：< / p >
< ul >
< li > 停用审计策略并暂时挂起日志记录< / li >
< li > 更改现有审计日志（两者都在数据库日志可靠性部分中讨论）。< br > 通过将取证分析技术应用于数据库存储或缓冲区缓存，并将发现的证据与审计日志相匹配，可以：< / li >
< li > 检测DBMS审核日志中未显示的多种类型的数据库访问和操作。< / li >
< li > 将未归因的记录修改分类为模糊的INSERT， < / li >
< li > 检测无法从审核日志中的活动派生的（ ） < / li >
< / ul >
< h2 id = "Reliability-of-database-logs" > < a href = "#Reliability-of-database-logs" class = "headerlink" title = "Reliability of database logs" > < / a > Reliability of database logs< / h2 > < p > 攻击者可以更改两种类型的日志： write-ahead logs (WAL) and audit logs (event history records)< / p >
< ul >
< li > WALs以低级别记录数据库修改以支持ACID保证， < br > 通常无法禁用或轻松修改WAL， （ ， ） < br > 某些DBMS允许为特定操作禁用WAL， ， < / li >
< li > audit logs记录配置的用户数据库操作。包括SQL操作和其他用户活动。审计日志根据数据库管理员配置的日志记录策略存储已执行的SQL命令。 因此，管理员可以根据需要禁用日志记录或修改单个日志记录。< br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555311090/paper/%E5%9B%BE%E7%89%873.png" alt > < / li >
< / ul >
< h2 id = "Detecting-hidden-record-modifications" > < a href = "#Detecting-hidden-record-modifications" class = "headerlink" title = "Detecting hidden record modifications" > < / a > Detecting hidden record modifications< / h2 > < p > 插入或修改表记录时，数据库中会发生一连串的存储更改。 除了受影响记录的数据本身之外，页面元数据会更新（例如，设置删除标记），并且存储记录的索引的页面会改变（例如，以反映记录的删除）。 如果尚未缓存， < br > 此外， （ ） （ ） < br > 在本节中，我们将描述如何检测已修改记录与已记录命令之间的不一致。< / p >
< h3 id = "Deleted-records" > < a href = "#Deleted-records" class = "headerlink" title = "Deleted records" > < / a > Deleted records< / h3 > < ol >
< li > 算法< br > 删除的记录不会被物理删除，而是在页面中标记为“已删除”; 已删除行占用的存储空间将成为未分配的空间，最终将被新行覆盖。这些对数据库存储的更改不能被绕过或控制。< br > 识别存储中与日志中的任何删除操作都不匹配的已删除行。< br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555311166/paper/%E5%9B%BE%E7%89%874.png" alt > < / li >
< li > 实例< / li >
< / ol >
< ul >
< li > DICE从Customer表重建了三个删除的行< br > （ ， ， ） < br > （ ， ， ） < br > （ ， ， ） < / li >
< li > 日志文件包含两个操作< br > 在算法1中， < br > 算法1返回（ ， ， ） ， < br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555311315/paper/%E5%9B%BE%E7%89%875.png" alt > < / li >
< / ul >
< h3 id = "Inserted-records" > < a href = "#Inserted-records" class = "headerlink" title = "Inserted records" > < / a > Inserted records< / h3 > < ol >
< li > 算法< br > 新插入的行将附加到表的最后一页的末尾（如果最后一页已满，则为新页）或覆盖由先前删除的行创建的可用空间。< br > 如果“活跃”新表行与审核日志中的任何插入操作都不匹配，则此行是可疑活动的标志。< br > 算法2中使用这些“活跃”记录来确定重构行是否可归因于审计日志中的插入。< br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555311991/paper/%E5%9B%BE%E7%89%876.png" alt > < / li >
< li > 实例< / li >
< / ol >
< ul >
< li > 该日志包含六个操作。< br > 当行从T1插入到T4时， < br > 在T5， （ ， ） < br > 然后在T6插入（ ， ） < br > 由于row（ ， ） （ ， ） ， < / li >
< li > DICE重建了五个活动记录< br > 包括（ ， ） （ ， ） < br > 行被初始化为算法2的五个重建活动行< br > 算法2因此返回（ ， ） （ ， ） < br > 因为这些记录无法与记录的插入匹配。< br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555312072/paper/%E5%9B%BE%E7%89%877.png" alt > < / li >
< / ul >
< h3 id = "Updated-records" > < a href = "#Updated-records" class = "headerlink" title = "Updated records" > < / a > Updated records< / h3 > < ol >
< li > 算法< br > UPDATE操作本质上是一个DELETE操作， < br > 为了考虑更新的行， ， ， ， ， < br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555312183/paper/%E5%9B%BE%E7%89%878.png" alt > < / li >
< li > 实例< br > 算法1返回行（ ， ） < br > 算法2返回行（ ， ） （ ， ） < br > 使用这些记录集， （ ， ） ， （ ， ） （ ， ） < br > 此外， （ ， ） （ ， ） ， ： < br > （ ， ） （ ， ） < br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555312234/paper/%E5%9B%BE%E7%89%879.png" alt > < / li >
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< h2 id = "Detecting-inconsistencies-for-read-only-queries" > < a href = "#Detecting-inconsistencies-for-read-only-queries" class = "headerlink" title = "Detecting inconsistencies for read-only queries" > < / a > Detecting inconsistencies for read-only queries< / h2 > < p > DBMS使用称为缓冲区管理器的组件将页面从磁盘缓存到内存中。数据以页为单位读入缓冲池， < br > 在本节中，将描述如何将缓冲池中的工件与审计日志中的只读查询进行匹配。< br > 数据库查询可以使用两种可能的访问表的方式之一：< br > 全表扫描（ ） （ ） < br > FTS读取所有表页， < / p >
< h3 id = "Full-table-scan" > < a href = "#Full-table-scan" class = "headerlink" title = "Full table scan" > < / a > Full table scan< / h3 > < p > 当查询使用FTS时， < br > 我们可以通过SID=131识别属于Employee的页面， （ ） < br > Q2和Q4都通过FTS访问员工。 每次扫描Employee表时， （ ： ） < br > 因此， ， < br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555312316/paper/%E5%9B%BE%E7%89%8710.png" alt > < / p >
< h3 id = "Index-access" > < a href = "#Index-access" class = "headerlink" title = "Index access" > < / a > Index access< / h3 > < p > Customer表的SID=124， < br > Q1在城市Dallas上进行过滤， < br > Q3在城市Jackson上过滤， ， ， < br > 如果审核日志中的查询过滤了索引页的最小值和最大值范围内的值，则该页可以归因于该查询。< br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1555312359/paper/%E5%9B%BE%E7%89%8711.png" alt > < / p >
< h3 id = "Conclusions-and-future-work" > < a href = "#Conclusions-and-future-work" class = "headerlink" title = "Conclusions and future work" > < / a > Conclusions and future work< / h3 > < ul >
< li > 审计日志和其他内置DBMS安全机制旨在检测或阻止攻击者执行的恶意操作。这种机制的固有缺点是具有足够权限的攻击者可以绕过它们来隐藏它们的踪迹。< / li >
< li > 我们提供并全面评估DBDetective， ， < / li >
< li > 我们的方法依赖于对数据库存储的取证检查，并将此信息与审核日志中的条目相关联，以发现恶意操作的证据。< / li >
< li > 重要的是，数据库存储几乎不可能被欺骗，因此，与例如审计日志相比，它是更可靠的篡改证据来源。< / li >
< li > 鉴于存储快照提供的信息不完整， ， ， ， ， < / li >
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