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A wireless sensor network (WSN) can provide a low cost and flexible solution to sensing and monitoring for large distributed applications. To save energy and prolong the network lifetime, the WSN is often partitioned into a set of spatial clusters. Each cluster includes sensor nodes with similar sensing data, and only a few sensor nodes (samplers) report their sensing data to a base node. Then the...
Nowadays, many organizations collect large volumes of event log data on a daily basis, and the analysis of collected data is a challenging task. For this purpose, data mining methods have been suggested in past research papers, and several data clustering algorithms have been developed formining line patterns from event logs. In this paper, we introduce an open-source tool called LogClusterC which...
With more companies turning towards cloud computing for storage and processing of their data, the security of the cloud becomes essential. However, cloud computing is vulnerable to many security threats, including data leakages, compromised credentials, presence of unauthorized users or entities, execution of insecure applications or programming interfaces and APIs, shared technology vulnerabilities,...
The constrained capacity of wireless sensor nodes and harsh, unattended deploy environments make the data collected by sensor nodes usually unreliable. We have proposed a count-min sketch based anomaly detection scheme with the goal of detecting the anomaly data values in WSN. In this paper, we analyze the performance of the proposed scheme thoroughly. We show through experiments with real sensed...
Data aggregation is an efficient way to prolong the lifetime of wireless sensor networks (WSNs) by reducing communication traffic. However, sensor nodes are usually deployed in harsh or hostile environments. They are easy to be malfunctioning or become compromised nodes, which makes the sensor data unreliable and affects the accuracy of data aggregation. This paper proposes a secure data aggregation...
Intrusion detection Systems(IDS) can produce large amount of alert data which usually possesses the characteristics of high redundancy and high repetition. Such kind of data makes the event processing for network security significantly difficult. Current cluster algorithms use cluster center to calculate the distance which leads to fairly big calculation errors. In order to aggregate the massive alert...
A huge amount of information about real-time events are being generated in every second in a running IT-Infrastructure and recorded by the system logs, application logs, as well as the output from the deployed security or management methods, e.g., IDS alerts, firewall logs, scanning reports, etc. To rapidly gather, process, correlate, and analyze the massive event information is a challenging task...
Trust is a concept taken from social sciences and is considered as a soft security approach that is effective in reducing risk. In this paper, for estimating the trust between unknown nodes, a group-based trust propagation method has been proposed. Most of the conventional trust propagation methods are not applicable for trust evaluation of today's large trust graphs. Our trust propagation method...
Network anomaly detection is a critical aspect of network management for instance for QoS, security, etc. The continuous arising of new anomalies and attacks create a continuous challenge to cope with events that put the network integrity at risk. Most network anomaly detection systems proposed so far employ a supervised strategy to accomplish the task, using either signature-based detection methods...
Index partitioning techniques-where indexes are broken into multiple distinct sub-indexes-are a proven way to improve metadata search speeds and scalability for large file systems, permitting early triage of the file system. A partitioned metadata index can rule out irrelevant files and quickly focus on files that are more likely to match the search criteria. Also, in a large file system that contains...
This paper describes an automatic text analysis of values contained in the Enron email dataset that seeks to explore the potential to apply value patterns to cluster a social network. Two hypotheses are posed: individuals communicate more frequently with other individuals who share similar value patterns than with individuals with different value patterns; and people who communicate more frequently...
Signature based network intrusion detection systems (NIDSs) often report a massive number of elementary alerts of low-level security-related events which are logically involved in a single multi-stage attack. Since be overwhelmed by these alerts, security administrators almost unable to discover complicated multistage attack in time. It is necessary to develop a real-time system to extracting useful...
Intrusion detection can be defined as the process of identifying malicious behavior that targets a network and its resources. An important problem in the field of intrusion detection is the management of alerts. This paper describes a realtime aggregation and correlation system named Alertclu. With the aid of similarity-based alert clustering analysing technology, Alertclu can improve the aggregation...
Though the security of wireless sensor networks (WSNs) has been studied deeply, the inside attacks still are very difficult to defend. The inside attacks are not detectable with only the classic cryptographic techniques and the attacks mainly include two types of attack: exceptional message attack and abnormal behavior attack. In this paper, we present an inside attacker detection approach, which...
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