会议名称：
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
会议时间：
2008-07-12
会议地点：
昆明
会议论文集名称：
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)论文集
关键词：
digital forensics;digital image forgery;tempering detection;passive-blind image forgery
摘要：
With the huge increasing use of digital photography, and the advent of high-performance commodity hardware and the presence of low-cost image editing softwares over the past few years, finding a credible method to detect digital image's authenticity and getting the result that which method the tampered image was applied to becomes a very valuable topic. In this paper, associating with the common forge methods, we propose the process of passive-blue detection of digital image's forging method, and then review the latest development of the passive-blind detection of image forging method, mainly include the detection of copy-move forgery, detection of blur forgery and detection of re-sample forgery.
摘要：
This paper firstly analyzed the front pattern matching algorithm of intrusion detection system, and improved on the pattern matching algorithm. Having immediately analyzed Rete algorithm and aimed at its shortage, the paper introduced the FRete net algorithm on the basis of Rete net algorithm constituting an inference machine based on FRete matching algorithm, which could infer logical suspicious facts. Then the authors discussed and designed an intrusion detection system based on high-speed networks, and finally established a simulation and experiment platform to test the performance of IDS.
摘要：
With the deeply research on intrusion detection techniques and the widely use of intrusion detection products, the study of evaluation techniques of intrusion detection systems became important. In the paper, relative works of the evaluation of intrusion detection systems was introduced. The primary aspects of intrusion detection systems in an evaluation were discussed. An evaluation system for intrusion detection systems was proposed. In the system, a supervisor module controls the whole system. The supervisor module schedules the traffic control module and the attack emulation module. The data in the evaluation environment are recorded and input to the evaluation module. The functions such as emulation of network traffic and host usage, emulation of attacks and evaluation report generation are implemented.
摘要：
The paper proposed modeling and simulation of distributed WLAN in OPNET. This model comprises of network model, node model and process model. Network model is the basic topology structure, node model describes the inside function module of all kinds of communication nodes, process model is used to make certain the management manner and management process of data. Moreover, we compare two primary channel allocation mechanisms of MAC level in IEEE 802.11 WLAN, Distributed Coordination Function (DCF) and Point Coordination Function (PCF).
会议论文集名称：
Lecture Notes in Engineering and Computer Science
关键词：
information audit;pattern matching;BM algorithms;network processor
摘要：
At present, network information audit system is almost based on text information filtering, Text categorization is the basic technology of text information filtering. Pattern matching algorithms are very important for the rule based information audit system. It directly influence the accuracy and real-time performance of the system. The KMP and BM algorithms are introduced in this paper. Research is carried out to improve the BM algorithm and a better BM algorithm is proposed According to the situation that the system characters group is bigger and that characters of the pat tern are less, the thesis puts forward an improved string-matching algorithm. The results of our experiments prove that it promotes the precision of text categorization.
关键词：
information audit;badness information;text character;Fuzzy neural network
摘要：
At Intelligent Methods for information audit system is hot spot in the field of network security, and application of pattern recognition and data mining in information audit system is world widely concerned and worldwide studying. As an important method of pattern recognition, Fuzzy neural network has the capability of self-organization, self-learning and generalization. Application of Fuzzy neural network in information audit system can not only identify the known badness information, but also can detect the new badness information and abnormal event.
摘要：
Although the current E-Learning systems have many Merits, Many of them only treat advanced information technology as simple communication tools, and release some learning contents and exercises in the network. In this paper, a one-class-in one network for emotion recognition system in E-learning is proposed and implemented in the paper. Using a large database of phoneme-balanced Chinese words read by speakers consciously trying to portray an emotion, we trained and tested this module. We achieved a recognition rate of approximately 55%. The results obtained in this study demonstrate that emotion recognition in speech is feasible, and that neural networks are well suited for this task.
通讯机构：
[Yin, Qian] B;Beijing Normal Univ, Coll Informat Sci & Technol, Beijing 100875, Peoples R China.
摘要：
In this paper, a new simple representation of the Berlekamp-Massey algorithm was proposed, which resolves the problem of the length of the shortest linear recurrence in the flowing cipher study. In the process of investigating the Berlekamp-Massey algorithm, using matrix-method can help to simplify the representation of the Berlekamp-Massey algorithm and easily calculate the distributing regulation of the shortest linear recurrence length compared to the traditional method.
摘要：
The paper proposes a new network intrusion detection system based on fuzzy neural network by redesigning the intrusion detection system's architecture and arithmetic. In order to overcome the difficulty of specifying the membership function of rules depending on experiences of experts in multi-dimension space.,neural network is introduced to distinguish non-linearly input/output characteristics of complex system and to generate rule sets and membership functions automatically. The new architecture adopts the network processor to collect and analyse the data in the low layer of network.,and to establish a prototype system. This system demonstrated in this experiment appears to be better intrusion detection ability, moreover, which is able to detect unknown attack and plays down false alarms.
会议名称：
Digital Media and its Application in Museum & Heritages, Second Workshop on
摘要：
The pest catastrophe prediction in ecology catastrophe is one of important part in expert system of intelligence agriculture for prevent and control pest catastrophe occurrence efficiently. The paper introduces the basic principles and methods of current catastrophe prediction in ecology. By modeling for the dynamic process of population, up-grown and amount of spawn, the paper finds out the trigger point and critical value, inducing the pest catastrophe and implements the catastrophe prediction Of cnaphalocrosis medinalis guenee before catastrophe to prevent big population coming into being.
关键词：
security E-government;security management;Distributed Access Control
摘要：
Since the method of using username and password and the traditional access-control list mechanism can no more keep up with the further development of E-Government, we realized a distributed-access-control model to settle this problem. This model divides the security management into two levels: First is global security management level which is responsible for harmonizing and controlling the security management of all the control objects of the e-government network; Second is local security management level which is in charge of the security management of local departments or objects inside local project group. By recompiling of the kernel of FreeBSD 5.0 version RC2, we have realized the access control model described above.
会议名称：
Applied Artificial Intelligence - 7th International FLINS Conference
摘要：
A novel Grey forecasting model for predicting S. sclerotiorum (Lib) de Bary disease on winter rapeseed (B. nopus) is built based on Grey GM (1,1) model. The residual error test and the posterror test methods were used for calibration of the model. Different from other conventional forecasting methods, the GM (1,1)-based Grey calamity prediction forecasts a prediction Delta T to infer the probable year of Sclerotinia disease outbreaks according to the origin, and then uses the result to recommend spraying a field or not in order to avoid unnecessary fungicide application. Based on practical experiments in Hunan province, the threshold (integral) of the disease rate at the time when winter rapeseed begins to flower is defined as 5, and (f < 5) is called a down-calamity. The Grey forecasting model was tested at the 7 stations in 2004 and 2005 and predicted the probable year of Sclerotinia disease outbreaks and the need for fungicide application with the first-class grade and high accuracy.
