Intrusion detection

Screened or impassable vents and intrusion-detection system. -Siting so greatest distance to a neighboring magazine is away from the weakest side, the headwall. 

Keywords wireless sensor network detection theory Kalman filtering target intrusion detection false alarm. 

The system parameter values depend on the particular application. When a house or a factory is to be monitored for intrusion detection, the cost of false alarms is relatively low. On the other hand, the financial and personnel cost of a false alarm is significantly higher when the perimeter security of a nuclear reactor is to be provided by deploying a SWSN to monitor unauthorized access. The cost of a false alarm might involve the transportation of special forces and/or personnel of related government agencies to the site, as well as the evacuation of residents in the surrounding area. 

Implement internal and external intrusion detection systems and establish twenty-... 

To be able to effectively respond to cyber attacks, establish an intrusion detection strategy that includes alerting network administrators of malicious network activity originating from internal or external sources. Intrusion detection system monitoring is essential twenty-four hours a day this capability can be easily set up through a pager. Additionally, incident response procedures must be in place to allow an... 

Alarm systems can be integrated with fire detection systems, intrusion detection systems (IDSs), access control systems, or closed circuit television (CCTV) systems, so that these systems automatically respond when the alarm is triggered. For example, a smoke detector alarm can be set up to automatically notify the fire department when smoke is detected, or an intrusion alarm can automatically trigger cameras to turn on in a remote location so that personnel can monitor that location. 

Network intrusion detection and prevention systems are software- and hardware-based programs designed to detect unauthorized attacks on a computer network system. 

It is worth noting that attacks may come from either outside or within the system (i.e., from an insider), and that network intrusion detection systems may be more applicable for detecting patterns of suspicious activity from inside a facility (i.e., accessing sensitive data, etc.) than are other information technology solutions. 

Network intrusion detection systems employ a variety of mechanisms to evaluate potential threats. The types of search and detection mechanisms are dependent upon the level of sophistication of the system. Some of the available detection methods include the following ... 

Protocol analysis. Protocol analysis is the process of capturing, decoding, and interpreting electronic traffic. The protocol analysis method of network intrusion detection involves the analysis of data captured during transactions between two or more systems or devices, and the evaluation of these data to identify unusual activity and potential problems. Once a problem is isolated and recorded, problems or potential threats can be linked to pieces of hardware or software. Sophisticated protocol analysis will also provide statistics and trend information on the captured traffic. 

Anti-intrusion detection system evasion techniques. These methods are designed for attackers who may be trying to evade intrusion detection system scanning. They include methods called IP defragmentation, TCP streams reassembly, and deobfuscation. 

One way to detect computer attacks is via an intrusion detection system (IDS). Such systems are characterized by two basic functions including the automatic detection of attacks, and the reporting of information about attacks to the administrator. An IDS works in real-time and monitors network traffic comparing it with templates from a database. If some template coincides with a template from a database, it means that the system has been attacked. 

The proposed method is universal to different attack types, and it enables to detect the status of remote attacking computer in the real time. The software module allows to promote the efficiency of corporate networks defense systems functioning, using its aggregation with the program complexes of the Intrusion Detection System. 

SNORT Intrusion Detection Sytem home page http //www.snort.org... 

Keywords intrusion detection alert management operational security security information management... 

Data enrichment is presented at the lower left comer of Figure 1. Data enrichment occurs when heterogeneous contextual information is entered in the event database. The same object can be represented by heterogeneous information depending on the data source. For example, the Windows NT event log can give us a host name, the network intrusion detection system a host IP address, and the wireless access point a MAC address, this for the same machine. The data enrichment functions attempt to complete and reconcile heterogeneous information entered in the database. 

This information is collected by the vulnerability assessment process. A vulnerability report is generated by a vulnerability assessment tool (for example Nessus3) as an XML file. Information in this file is imported in the events database as contextual information associated with hosts. Since vulnerability reports are associated with security references (bugtraq, CVE, etc.) and IDS signatures are also associated with the same information, it is fairly straightforward to infer the events that create a serious risk for the information system. If an event has as target the host associated with vulnerability X, and as signature one also associated with vulnerability X, then the risk is serious. This is a standard process that is in use in most intrusion-detection products. 

Curry, D., H. Debar, and B. Feinstein, The Intrusion Detection Message Exchange Format, Internet Draft, work in progress, expires July 8th, 2004. 

Debar, H. and A. Wespi, Aggregation and Correlation of Intrusion-Detection Alerts, In ... 

Recent Advances in Intrusion Detection (RAID 2001), Davis, CA, USA, pp. 85-103, Springer, 2001. 

Morin, B., L. Me, H. Debar, and M. Ducasse, M2D2 A Formal Data Model for IDS Alert Correlation, in Proceedings of the Fifth International Symposium on Recent Advances in Intrusion Detection (RAID), 2002. 

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