The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Unknown protocol inference are useful for many security application, including intrusion detection which always depends on deep packet inspection. However, mining distinguishers with unknown protocol format generally turns to protocol reverse engineering. In this paper, we propose a novel method for automatically abstracting protocol distinguishers based on statistic and our method is proved to be...
Although a lot of users share their information via Distributed Hash Table (i.e., DHT) network, a noticeable shortcoming of such a file-sharing system is that they can hardly preserve the users' privacies. To address such a problem, in this paper we propose a suite of security strategies for the DHT network in BitTorrent system, such as the DHT interdiction and the DHT vulnerable examining methods...
Network anomaly detection is a classically difficult research topic in intrusion detection. However, existing research has been solely focused on the detection algorithm. An important issue that has not been well studied so far is the selection of normal training data for network anomaly detection algorithm, which is highly related to the detection performance and computational complexity. Based on...
This paper introduces the process algebra language with its powerful standard model-checking tools for trusted software architectures, which deals with incompatibility between two components due to a single interaction or the combination of several interactions and with the lack of interoperability among a set of components through architectural compatibility check and interoperability check relying...
Spam fighting is a classic puzzle in network security. In the past decades, many filtering spam solutions have been proposed. However, currently the conventional techniques still suffer from high false positives and false negatives, especially the former which usually cannot be accepted by the end users. This paper proposes a novel online URL-based spam filter (UBSF) on the basis of analyses over...
Spam prevention is a classic puzzle in the research area of network security. The conventional spam filtering techniques still result to high false positives and have weak on-line processing ability. This paper presents a novel two-tier spam filter (TTSF) on the basis of analyses over the conventional anti-spam techniques. TTSF on-line filters spam by using URLs and off-line filters spam using digest-based...
An appropriate feature set helps to build efficient decision model as well as reduced feature set lights up the training and testing process considerably. In this paper, we propose a new approach to build efficient Intrusion detection system (IDS) based on principal component analysis and C4.5. Our method is able to significantly decrease training and testing times while retaining high detection rates...
Intrusion detection is a critical component of secure information systems. Current intrusion detection systems (IDS) especially NIDS (network intrusion detection system) examine all data features to detect intrusions. However, some of the features may be redundant or contribute little to the detection process and therefore they have great impact on the system performance. This paper proposes a lightweight...
Spam filtering is a great problem nowadays. The conventional spam filtering techniques still result in high false positives and false negatives. This paper proposes a novel online spam filter based on URLs and maximum entropy model. The filter identifies spam by classifying the e-mails with the pre-trained classifier based on the maximum entropy model and filters the spam online in terms of the characteristics...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.