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In order to optimize the fault feature database(FFD) and to improve the checking efficiency of software fault, in this paper, a novel method of software security checking based on similar feature tree(SFT) is proposed. All of fault feature patterns in FFD are considered as nodes of SFT. SFT is a special binary tree in which the left child of each node is a super-pattern of the node and the right child...
Software structure is very important for software security. But it is very difficult to obtain software structure by software execution trace. In this paper, by researching system call sequences in the process of software execution, similar call graph is proposed. We present how to generate similar call graph by observed system call sequences. Based on this, a knowledge base for software security...
In this article we discuss our research in developing general and systematic methods for intrusion detection. The key ideas are to use data mining techniques to discover consistent and useful patterns of system features that describe program and user behavior, and use the set of relevant system features to compute (inductively learned) classifiers that can recognize anomalies and known intrusions...
When large data repositories are coupled with geographic distribution of data, users and systems, it is necessary to combine different technologies for implementing high-performance distributed knowledge discovery systems. On the other hand, computational grid is emerging as a very promising infrastructure for high-performance distributed computing. Grid applications such as astronomy, chemistry,...
Intrusion detection system (IDS) is a security technology that attempts to identify and isolate ??Intrusions?? against computer systems. The major problem of IDS is the vulnerability to fragment attacks. For this problem we propose a new approach (ARD-FA : Association Rules to Detect Fragment Attack) using data mining techniques of links analyses. We develop this approach and show some improvement...
In this paper, we propose a self-protection model based on distributed intelligent agents. The major feather of this model is that autonomic agents can manage themselves given high-level objectives from administers. System can detect attacks and compromise, and recovering from security incidents without human intervention. We describe the model and the existing prototype, as well as some design and...
With the increase of the web applications in information society, Web application software security become more and more important. Recent investigations show that web application vulnerabilities have become the largest security threat. Websense security report shows that in the first half of year 2008 above 75% of the most popular Web site have utilized by the hackers to run malicious code. Detecting...
With the rapid development of computer network, the network is confronting a growing number of threats. Therefore, it is very important to assess the risks for the network information system. This paper draws data mining technology based on association rules into the field of risk assessment, demonstrating a network security risk assessment model based on association rules. The model mines data from...
Data mining in distributed systems has been facilitated by using high-support association rules. Less attention has been paid to distributed low-support/high-correlation data mining. This has proved useful in several fields such as computational biology, wireless networks, web mining, security and rare events analysis in industrial plants. In this paper we present distributed versions of efficient...
Intrusion detection systems (IDSs) are increasingly a key part of systems defense. Various approaches to intrusion detection are currently being used, but they are relatively ineffective. Recently applying artificial intelligence, machine learning and data mining techniques to IDS are increasing. Artificial intelligence plays a driving role in security services. This paper proposes an Immune based...
The specification language Z is almost entirely applied to design of large software system. However, nothing is done in applying Z to developing security-critical systems. The intrusion detection technology is one of the most important dynamic security technologies, which can be used in the critical security system construction and the basic service protection. Apparently, applying formal specification...
To analyze the behavior of investors in Shanghai stock market, we mine frequent itemsets and association rules from a real securities clearing dataset. The mining results indicate that, most investors do not diversify their capital to avert risks according to expected risks of a stock. Further analysis reveals that most of the frequent stocks itemsets only cover a few state-owned big-cap (SB) stocks,...
Recent attacks demonstrated that network intrusions have become a major threat to Internet. Systems are employed to detect internet anomaly play a vital role in Internet security. To solve this problem, a technique called frequent episode rules (FERs) base on data mining has been introduced into anomaly detection system (ADS). These episode rules are used to distinguish anomalous sequences of TCP,...
Privacy and security issues in data mining become an important property in any data mining system. A considerable research has focused on developing new data mining algorithms that incorporate privacy constraints. In this paper, we focus on privately mining association rules in vertically partitioned data where the problem has been reduced to privately computing Boolean scalar products. We propose...
Automatic configuration of large and heterogeneous ICT systems and their dependability mechanisms is both desirable and daunting for the inherent complexity of these systems.Configurations are commonly designed based on personal expertise, best practice, empirical evidence, without any automatic process and formal validation mechanism. This approach leads to frequent and reiterate errors with severe...
Numerous attacks made by the malware have presented serious threats to the security of computer users. Unfortunately, along with the development of the malware writing techniques, the number of file samples that need to be analyzed is constantly increasing on a daily basis. An automatic and robust tool to analyze and classify the file samples is the need of the hour. In this paper, resting on the...
Outsourcing of data mining to an outside service provider brings important benefits to the data owner. These include (i) relief from the high mining cost, (ii) minimization of demands in resources, and (iii) effective centralized mining for multiple distributed owners. However, security and integrity are issues that must be tackled before enterprises can indeed outsource data mining task. The service...
In order to find out the common features and general patterns in criminal cases, a new improved frequent predicate algorithm was proposed, with which multi-dimension association rules were drawn according to the minimum support and minimum confidence. This new algorithm was applied in the data mining model of criminal cases of Dalian Municipal Public Security Bureau.
This paper proposes a new approach of modeling the collaboration of sensor system artifacts to address the security and survivability concerns of sensor networks. The model considered is composed of sensors, base and users. Sensors are nodes that acquire and process data. Base is the node that acquires and processes data from sensors and provides an interface to access and monitor the sensor network...
Privacy is one of the most important properties an information system must satisfy. A relatively new trend shows that classical access control techniques are not sufficient to guarantee privacy when datamining techniques are used. Privacy Preserving Data Mining (PPDM) algorithms have been recently introduced with the aim of sanitizing the database in such a way to prevent the discovery of sensible...
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