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2025年下半年信息安全工程师《综合知识》考试真题及答案解析正在更新中，具体如下：

1、网络安全法第二十一条规定，国家实行网络安全等级保护制度。网络安全等级保护的主要工作中，等级保护测评机构依据相应等级要求，对定级的保护对象进行测评，并出具相应的等级保护测评证书的过程被称为（ ）。

A.备案

B.定级

C.等级测评

D.运营维护

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2、国产密码算法是由国家密码相关研究机构自主研发，具有相关知识产权的商用密码算法。目前已经公布的国产密码算法主要有：SM1算法、SM2算法、SM3杂凑算法、SM4算法、SM9标识密码算法和ZUC算法等。其中SM1是一种对称的分组密码算法，其分组长度和密钥长度分别是（ ）。

A.256比特和128比特

B.64比特和128比特

C.256比特和256比特

D.128比特和128比特

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3、SSH协议是基于公钥的安全应用协议，可以实现加密、认证、完整性检查等多种安全服务。在SSH协议的子协议中，（ ）提供算法协商和密钥交换，并实现服务器认证，形成一个加密的安全连接，提供完整性、保密性和压缩选项服务。

A.SSH传输层协议

B.SSH连接协议

C.SSH端口转发技术

D.SSH用户认证协议

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4、访问控制是指对资源对象的访问者授权、控制的方法及运行机制。以下属于控制的是（ ）。

A.接收邮件

B.读写

C.删除

D.禁止访问

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5、防火墙和网闸都是保障内网安全的网络安全技术。以下关于防火墙和网闸的说法中，错误的是（ ）。

A.防火墙依赖规则库防御已知威胁

B.网闸对外提供开放端口

C.网闸可实现协议层面的完全隔离

D.防火墙支持双向通信与会话保持

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6~10、Biometric authentication is a system which is capable to identifying a （01） based on the inherent physical or behavioral traits associated with that person. In recent years the application of biometrics in authentication systems, increase gradually, one of the main reasons for its popularity is that biometric traits like a fingerprint, face and iris feature of a person are （02） during the whole life time and it is not easily guessed, forgotten and misplaced. Biometric based system is more secure and accurate compared to the traditional system which is based on user personal identification number （PIN） and the user set PIN can be easily guessed by the third party. Unimodal system which is based on single modality has several inherent problems like intra-class variation, spoofing attacks and failure-to-enroll rate. To overcome this limitation multibiometric is a good option where we can use （03） one modality at a time to improve the performance and accuracy level of the systems. A fusion process plays an important role in multibiometric where the features of more than one modality are combined together. The whole fusion process can be classified as sensor level, feature level （combining features from different biometrics）, score level （combining the genuine and imposter score）, decision level （combining the decisions） and rank level （combining the ranks）. Among all the fusion methods score level fusion is very popular and simple; lots of research has been done in the area of score level fusion. Researchers prefer to use score level fusion due to ease of combining matching score. Further score level fusion technique can be categorized as a） transformation-based score fusion like sum rule, weighted sum rule and the product rule. b） Classifier based like support vector machine （SVM） and c） density based fusion like likelihood ratio test. It is very （04） to deal with the feature level fusion because at this level the feature sets generated from multiple modalities are different in nature as in the case of fusion of fingerprint and face. Researchers preferred （05） use score level fusion due to ease of combining matching score. Due to lack of information it is very difficult to select a decision level, as a fusion strategy in a multibiometric system. In feature level fusion due to the large dimensionality of the feature set, it may affect the performance of the system, so some feature selection technique is used to identify and remove the irrelevant and redundant information and may allow learning algorithms to operate faster and more effectively.

（6）

A.person

B.server

C.device

D.computer

（7）

A.diferernt

B.safe

C.same

D.complete

（8）

A.of

B.more than

C.on

D.as

（9）

A.difficult

B.easy

C.relaxed

D.fast

（10）

A.with

B.to

C.for

D.by

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