李涛
网络安全技术及应用;智能信息系统。
个性化签名
- 姓名:李涛
- 目前身份:
- 担任导师情况:
- 学位:
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学术头衔:
博士生导师, 教育部“新世纪优秀人才支持计划”入选者
- 职称:-
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学科领域:
计算机科学技术
- 研究兴趣:网络安全技术及应用;智能信息系统。
李涛,教授、博士生导师,计算机网络与安全研究所所长、教育部新世纪优秀人才、国家政府特殊津贴专家、四川省学术和技术带头人、成都市有突出贡献的优秀专家。
1995 年 3 月毕业于电子科技大学,获电子科技大学工学博士学位。 1995 年 4 月任教四川大学, 1995 年 11 月破格晋升为教授, 1996 年创建四川大学计算机网络与安全研究所、任所长, 2001 年入选四川省党政网络信息安全领导小组专家成员, 2003 被评为四川省学术和技术带头人、成都市有突出贡献的优秀专家, 2004 年首批入选教育部新世纪优秀人才计划,同年享受国家政府津贴, 2005 年入选国家计算机网络与信息安全专项计划专家组管理专家。
主持并完成了10多项国家级科研项目的研究,在 IEEE会刊 、 ACM会刊 、《中国科学》、《科学通报》、《自然科学进展》等国内外权威刊物及学术会议上发表论文 200 余篇, 60 多篇论文被 SCI 、 EI 收录,独著或主编《计算机免疫学》、《网络安全概论》、《信息系统容灾抗毁原理与应用》等学术专著 4 本,申请及获准网络安全国家发明专利、国防发明专利共计 29项,以第一完成人身份先后4次获省部级科技进步奖(其中一等奖3次,二等奖1次),相关成果被科技部、国家发改委列入“国家科技成果重点推广计划”、“国家高技术产业化示范工程”等。
主要研究方向:网络安全技术及应用;智能信息系统。
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593
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成果数
11
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引用
【期刊论文】Family Gene Based Grid Trust Model
李涛, Tiefang Wang, Tao Li, Xun Gong, Jin Yang, Xiaoqin Hu, Diangang Wang, and Hui Zhao
L. Jiao et al. (Eds.): ICNC 2006, Part II, LNCS 4222, pp. 110-113, 2006.,-0001,():
-1年11月30日
This paper analyzes the deficiencies of current grid trust systems based on PKI (Public Key Infrastructure), ambiguity certificate principal information, and complicated identification process. Inspired by biologic gene technique, we propose a novel grid trust model based on Family Gene (FG) model. The model answers the existing questions in tradition trust model by adopting the technology of family gene. The concepts and formal definitions of Family Gene in the grid trust security domains are given. Then, the mathematical models of Family Gene are established. Our theoretical analysis and experimental results show that the model is a good solution to grid trust domain.
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39浏览
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【期刊论文】Grid Intrusion Detection Based on Immune Agent
李涛, Xun Gong, Tao Li, Tiefang Wang, Jin Yang, Gang Liang, and Xiaoqin Hu
L. Jiao et al. (Eds.): ICNC 2006, Part II, LNCS 4222, pp. 73-82, 2006.,-0001,():
-1年11月30日
This paper proposes a novel grid intrusion detection model based on immune agent (GIDIA), and gives the concepts and formal definitions of self, nonself, antibody, antigen, agent and match algorithm in the grid security domain. Then, the mathematical models of mature MoA (mature monitoring agent), and dynamic memory MoA (memory monitoring agent) survival are established. Besides, effects of the important parameter Τ in the model of mature MoA on system performance are showed. Our theoretical analysis and experimental results show that the model that has higher detection efficiency and steadier detection performance than the current models is a good solution to grid intrusion detection.
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【期刊论文】A New Model for Dynamic Intrusion Detection
李涛, Tao Li, Xiaojie Liu, and Hongbin Li
Y.G. Desmedt et al. (Eds.): CANS 2005, LNCS 3810, pp. 72-84, 2005.,-0001,():
-1年11月30日
Building on the concepts and the formal definitions of self, nonself, antigen, and detector introduced in the research of network intrusion detection, the dynamic evolution models and the corresponding recursive equations of self, antigen, immune-tolerance, lifecycle of mature detectors, and immune memory are presented. Following that, an immune-based model, referred to as AIBM, for dynamic intrusion detection is developed. Simulation results show that the proposed model has several desirable features including self-learning, self-adaption and diversity, thus providing a effective solution for network intrusion detection.
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【期刊论文】An immune based dynamic intrusion detection model
李涛, LI Tao
Chinese Science Bulletin 2005 Vol. 50 No. 22 2650-2657,-0001,():
-1年11月30日
With the dynamic description method for self and antigen, and the concept of dynamic immune tolerance for lymphocytes in network-security domain presented in this paper, a new immune based dynamic intrusion detection model (Idid) is proposed. In Idid, the dynamic models and the corresponding recursive equations of the lifecycle of mature lymphocytes, and the immune memory are built. Therefore, the problem of the dynamic description of self and nonself in computer immune systems is solved, and the defect of the low efficiency of mature lymphocyte generating in traditional computer immune systems is overcome. Simulations of this model are performed, and the comparison experiment results show that the proposed dynamic intrusion detection model has a better adaptability than the traditional methods.
intrusion detection, artificial immune system, immune tolerance, immune memory, negative selection.,
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【期刊论文】An immunity based network security risk estimation
李涛, LI Tao
Science in China Ser. F Information Sciences 2005 Vol.48 No.5 557-578,-0001,():
-1年11月30日
According to the relationship between the antibody concentration and the pathogen intrusion intensity, here we present an immunity-based model for the network security risk estimation (Insre). In Insre, the concepts and formal definitions of self, nonself, antibody, antigen and lymphocyte in the network security domain are given. Then the mathematical models of the self-tolerance, the clonal selection, the lifecycle of mature lymphocyte, immune memory and immune surveillance are established. Building upon the above models, a quantitative computation model for network security risk estimation, which is based on the calculation of antibody concentration, is thus presented. By using Insre, the types and intensity of network attacks, as well as the risk level of network security, can be calculated quantitatively and in real-time. Our theoretical analysis and experimental results show that Insre is a good solution to real-time risk evaluation for the network security.
artificial immune system, intrusion detection, network security, risk estimation.,
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49浏览
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李涛
科学通报,2005,50(17):1912~1919,-0001,():
-1年11月30日
提出了一种新的基于免疫的动态入侵检测模型(Idid),建立了入侵检测中有关自体、抗原的动态描述方法,提出了免疫细胞的动态耐受概念,并建立了成熟细胞的生命周期以及免疫记忆等的动态模型及其递推方程. 解决了计算机免疫系统中自体、非自体的动态描述问题,并同时有效地克服了传统计算机免疫系统中成熟细胞生成效率较低等缺陷. 对模型进行了仿真,对比实验表明这种新型的入侵检测模型较传统方法具有更好的适应性.
入侵检测, 人工免疫, 耐受, 免疫记忆, 否定选择
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103浏览
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李涛
中国科学E辑信息科学学报,2005,35(8):798~816,-0001,():
-1年11月30日
依据人体免疫系统抗体浓度的变化与病原体入侵强度的对应关系,提出了一种基于免疫的网络安全风险检测模型(Insre),给出了网络环境下自体、非自体、抗体、抗原、免疫细胞等的表示方法, 建立了自体演化、抗体基因库、自体耐受、克隆选择、成熟细胞的产生与淘汰机制、动态免疫记忆、免疫监视等的抽象数学模型及相应的递推方程,在此基础上建立了基于抗体浓度的网络安全风险检测的定量计算模型,并给出了其理论推导和证明.利用该模型,可以实时定量地计算出网络当前所面临攻击的类别、数量、强度及风险指标等.理论分析和实验结果表明该方法是网络安全风险在线检测一种有效的新途径.
网络安全, 人工免疫, 风险评估, 入侵检测
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李涛, Khaled Amleh, Member, IEEE, Hongbin Li, and Tao Li
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 53, NO. 6, NOVEMBER 2004,-0001,():
-1年11月30日
In this paper, we present a group of subspace code-timing estimation algorithms for asynchronous code-division multiple-access (CDMA) systems with bandlimited chip waveforms. The proposed schemes are frequency-domain based techniques that exploit a unique structure of the received signal in the frequency domain. They can be implemented either blindly or in a training-assisted manner. The proposed blind code-timing estimators require only the spreading code of the desired user, whereas the training-assisted schemes assume the additional knowledge of the transmitted symbols of the desired user. Through a design parameter of user choice, the proposed schemes offer flexible tradeoffs between performance, user capacity, and complexity. They can deal with both time-and frequency-selective fading channels. Numerical simulations show that the proposed schemes are near-far resistant, and compare favorably to an earlier subspace code-timing estimation scheme that is implemented in the time domain.
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