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Extracting metadata from academic papers has attracted much attention from researchers in past years. But how to extract metadata automatically from books is still seldom discussed. In this paper, we address this task on Chinese books and present a system to extract metadata from the title page of a book. This system consists of three components: metadata segmentation, metadata labeling, and post-processing...
Current practice for real-time security risk assessment typically takes intrusion detection systems alerts as the only source of risk factor. Their assessment results are more likely to suffer from the impact of false positive alerts in the increasingly complex and severe network security environment. This paper proposes a novel online fusion model for dynamical network risk assessment by using multiple...
Table of contents (TOC) recognition has attracted a great deal of attention in recent years. After reviewing the merits and drawbacks of the existing TOC recognition methods, we have observed that book documents are multi-page documents with intrinsic local format consistency. Based on this finding we introduce an automatic TOC analysis method through clustering. This method first detects the decorative...
Book documents usually have consistent typographies throughout the whole book, including headers, footers, columns, text line directions, and fonts used in the each level of headings. Such document-level typography information is of great value for downstream document processing applications. This paper presents a document analysis system that can extract a comprehensive set of typographies used in...
An intrusion detection system (IDS) generates alerts indicating what malicious behaviors are going on against the protected network system. When comparing the real-time reported IDS alerts with the network attack graph which provides all possible sequences of exploits that an intruder may use to penetrate the system, some prediction on future attacks can be made. In this paper we proposed a novel...
A network attack graph provides a global view of all possible sequences of exploits which an intruder may use to penetrate a system. Attack graphs can be generated by model checking techniques or intrusion alert correlation. In this paper we proposed a data mining approach to generating attack graphs. Through association rule mining, the algorithm generates multi-step attack patterns from historical...
In this paper a novel approach to assessing the threat of network intrusions is proposed. Unlike the present approaches which assess the attack threat either from a backward perspective (how probable a security state can be reached) or from the perspective of the attacks themselves (how much an attack would cause damage to the network), this approach assesses the attack threat from a forwarding perspective...
Continuously increasing volume of security data makes it important to develop an advanced alert correlation system that can reduce alert redundancy, intelligently correlate security alerts and detect attack strategies. In this paper, we propose a new method of constructing attack scenarios in order to recognize attacker's high-level strategies and predict upcoming attack intentions. We mine frequent...
With the growing deployment of network security devices, the large volume of alerts gathered from these devices often overwhelm the administrator, and make it almost impossible to discover complicated multistage attacks in time. It is necessary to develop a real-time system to detect the ongoing attacks and predict the upcoming next step of a multistage attack in alert streams, using known attack...
Huge volume of security data from different security devices can overwhelm security managers and keep them from performing effective analysis and initiating timely response. Therefore, it is important to develop an advanced alert correlation system that can reduce alert redundancy, intelligently correlate security alerts and detect attack strategies. In this paper, we proposed a new method of mining...
Since security audit data increased so dramatically, management and analysis of these security data become a challenge issue. In our system SATA (security alerts and threat analysis), we proposed a new method of learning multi-stage attack strategies through attack sequence mining method to recognize attacker's high-level strategies and predicting upcoming attack intentions. We first apply an attack...
Large volume of security data can overwhelm security managers and keep them from performing effective analysis and initiating timely response. Therefore, it is important to develop an advanced alert correlation system to reduce alert redundancy, intelligently correlate security alerts and detect attack strategies. In our system, we introduced statistical filtering method in attack plan recognition...
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