Taxonomy on existing techniques of reducing false alarms in Annotated Bibliography

Taxonomy on existing techniques of reducing unreasonable alarms in sensor-based healthcare monitoring systems - Annotated Bibliography ExampleAccording to Qassim, Patel and Modzhin (2014), fuzzy logic take a chance analysis is utilise to reduce false alarm instances and maintain sufficient level of security against serious attacks in intrusion and detective work systems. The primary purpose of an intrusion and detection system is to identify attackers trying to infiltrate a network and expose vulnerable resources. By using a Fuzzy Logic-Risk Analysis (FLRA) model, the Qassim et al. (2014) aimed to reduce instances of false positives. By calculating the significance and severity of each suspected attack, the system establishes whether an act asivity can be classified as attempted attack or normal behavior miss judged by the detection system. The model comprises four layers integrated interface, knowledge manager, autonomic manager, and resource manager. The topmost layer represent s the integration occlusive of the system administrator and the intrusion detection system. At this level, strategies and policies are defined and implemented. The section responsible for false positive reduction is the Intrusion Detection Manager. This morsel layer referred as the Fuzzy Logic-Risk Analysis Intrusion Detection Manager is responsible comprises of four modules monitor module, analyzer, planner module and control module. All the modules act systematically to detect any attempts of intrusion, eliminate false positives and perform necessary changes to the protected element. Fuzzy Logic-Risk Analysis model works in two mechanisms identifying the risk and assessing the risk. at one time the risk has been identified it is assessed using weighted averages and consequently categorized. Threats are categorized based on their ability to cause harm to asset elements. Once the risk has been identified, residual and exposed risks are analyzed using Fuzzy logic from which differ ent countermeasures are applied to mitigate it. FLRA model works by taking the