New Devolopment of Information Security——For the 60th Anniversary of Journal of Computer Research and Development
-
摘要: 首先提出了信息安全发展过程中最大的趋势：在系统安全领域不断引入密码技术并产生新的密码问题，使得密码安全不断地渗透到系统的方方面面.其次，阐述了“渗透”加上新的服务运营模式导致现代密码学呈现了新的景象，即“端端”单方模式改变为多方模式、“位置”本地模式改变为异地模式与“安全模型”由信道安全改变为“信道安全+”模型等.在此基础上，较详细介绍了密文访问控制、安全外包计算、安全搜索、电子货币与区块链安全、人工智能与机器学习中的安全与隐私保护等方面的最新理论研究进展与未来发展方向.此外，还介绍了一些成果的应用，包括加密数据共享移动设备硬件研制与基于生物信息的身份鉴别类应用等.Abstract: This article firstly identifies the most important trend in the development of information security is that finding new security issues by introducing cryptographic techniques into the field of system security, which enables that cryptographic security has been increasingly applied in almost every aspect of the computer system. Besides, we present the new characteristics of modern cryptography resulted from this new application and new types of service mode, including that the entity has been transformed from single mode to multiparty mode, the position has been transformed from local mode to remote mode, and the security model has been transformed from channel security model to “channel security plus” model. Based on the new features given above, we mainly focus on discussing both the state-of-the-art and the future directions for theorectical research in the aspects of ciphertext access control, secure outsourced comutation, secure search, electronic currency and blockchain security, and privacy-preserving in artificial intelligence and machine learning. Finally, we also introduce some application results, including the hardware development of the mobile device for encrypted data sharing and the identity authentication based on biological information.
-
-
期刊类型引用(9)
1. 李振华，王泓懿，李洋，林灏，杨昕磊. 大规模复杂终端网络的云原生强化设计. 计算机研究与发展. 2024(01): 2-19 . 
本站查看
2. 赵旭康，刘晓锋，徐洁. 融合多样频度与分布差异的Android恶意软件检测. 计算机工程与设计. 2024(02): 390-395 . 百度学术
3. 方加娟，丁乙恒. 基于关联规则的Android恶意软件检测技术. 电脑与信息技术. 2024(03): 115-118 . 百度学术
4. 陈志强，韩萌，武红鑫，李慕航，张喜龙. 分段加权的概念漂移检测方法. 计算机应用. 2023(03): 776-784 . 百度学术
5. 李汇来，杨斌，于秀丽，唐晓梅. 软件缺陷预测模型可解释性对比. 计算机科学. 2023(05): 21-30 . 百度学术
6. 潘建文，崔展齐，林高毅，陈翔，郑丽伟. Android恶意应用的静态检测方法综述. 计算机研究与发展. 2023(08): 1875-1894 . 本站查看
7. 殷建艳. 面向云数据库的Android应用风险评估方法. 信息与电脑(理论版). 2023(17): 177-179 . 百度学术
8. 张皓. 基于深度学习的恶意软件动态检测方法研究. 电子技术与软件工程. 2022(03): 43-46 . 百度学术
9. 刘光源. 基于DoI-RNNs模型的恶意软件动态检测方法. 信息与电脑(理论版). 2022(23): 38-40 . 百度学术
其他类型引用(6)
计量
- 文章访问数: 1705
- HTML全文浏览量: 4
- PDF下载量: 833
- 被引次数: 15
下载:
