An Event-Driven Architecture for Fine Grained Intrusion Detection and Attack Aftermath Mitigation

2007 ◽  
Author(s):  
Jianfeng Peng ◽  
Chuan Feng ◽  
Haiyan Qiao ◽  
Jerzy Rozenblit
Keyword(s):  
Intrusion Detection ◽  
Fine Grained ◽  
Event Driven

Event-Driven Architecture for Intrusion Detection Systems Based on Patterns

2008 ◽  
Author(s):  
Jesuss J. Martínez Molina ◽  
Miguel A. Hernandez Ruiz ◽  
Manuel Gil Perez ◽  
Gregorio Martinez Perez ◽  
Antonio F. Gomez Skarmeta
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection Systems ◽  
Detection Systems ◽  
Event Driven

scholarly journals Event Based Approach for Web Services Composition

2014 ◽  
pp. 52-58
Author(s):  
A. Vani Vathsala ◽  
Hrushikesha Mohanty
Keyword(s):  
Web Services ◽  
Service Oriented Architecture ◽  
Research Work ◽  
Ongoing Research ◽  
Loosely Coupled ◽  
Fine Grained ◽  
Business Applications ◽  
Event Driven ◽  
Service Oriented ◽  
Event Based

The success of the Internet and the ongoing globalization led to a demand for new solutions to meet the requirements for ITsystems. The paradigm of service-oriented and event-driven architecture with fine grained and loosely coupled services tries to cope with those needs. Service Oriented Architecture (SOA) and Event Driven Architecture (EDA) are two acknowledged architectures for the development of business applications and information systems, which have evolved separately over the years. Today both architectures are acknowledged, but their synergy is not. There are numerous benefits of having an architecture that supports coexistence between operations and events, and composition of services based on operation invocation and event triggering. As part of our ongoing research work, we have tried to analyze in this paper, the basic design of Event based systems, issues that have to be addressed when event based approach is used for composing and coordinating web services. Then we have specified the techniques available that handle these issues, and gave a comparative study on these techniques. Finally we have attempted to sort out the unhandled/ partially handled issues that could be addressed as part of our research.

Robust WLAN-Based Indoor Fine-Grained Intrusion Detection

2016 ◽  
Author(s):  
Jiguang Lv ◽  
Wu Yang ◽  
Liangyi Gong ◽  
Dapeng Man ◽  
Xiaojiang Du
Keyword(s):  
Intrusion Detection ◽  
Fine Grained

Hardware support for fine-grained event-driven computation in Anton 2

2013 ◽  
Vol 41 (1) ◽  
pp. 549-560
Author(s):  
J. P. Grossman ◽  
Jeffrey S. Kuskin ◽  
Joseph A. Bank ◽  
Michael Theobald ◽  
Ron O. Dror ◽  
...  
Keyword(s):  
Hardware Support ◽  
Fine Grained ◽  
Event Driven

Police Patrols and Fire Alarms in U.S. Foreign Policy

2015 ◽  
Author(s):  
Linda L. Fowler
Keyword(s):  
Foreign Policy ◽  
National Security ◽  
Foreign Relations ◽  
Democratic Accountability ◽  
Fire Alarm ◽  
Police Patrol ◽  
Fine Grained ◽  
Public Hearings ◽  
Event Driven ◽  
Armed Services

This chapter examines partisan calculations about party reputations as influences on routine and event-driven public hearings, using the classic typology of police patrols and fire alarms. It considers committee choices regarding the content of national security oversight hearings by comparing routine inquiries to reviews of major crises and scandals. The chapter uses the unique characteristics of fine-grained coding of hearings to develop measures for police patrol and fire alarm oversight of national security. It also discusses expectations about committee behavior as well as the distribution of patrols and alarms for the Senate Armed Services and Foreign Relations committees, particularly as they relate to changes in military casualties from 1947 to 2008. Finally, it explores crisis oversight as a form of committee review that is particularly important to democratic accountability.

scholarly journals Indoor NLOS Positioning System Based on Enhanced CSI Feature with Intrusion Adaptability

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1211 ◽  
Author(s):  
Ke Han ◽  
Lingjie Shi ◽  
Zhongliang Deng ◽  
Xiao Fu ◽  
Yun Liu
Keyword(s):  
Intrusion Detection ◽  
Indoor Localization ◽  
Calibration Method ◽  
Support Vector ◽  
Positioning System ◽  
Fine Grained ◽  
High Discrimination ◽  
Multiple Support ◽  
Indoor Scenarios ◽  
Indoor Positioning System

With the wide deployment of commercial WiFi devices, the fine-grained channel state information (CSI) has received widespread attention with broad application domain including indoor localization and intrusion detection. From the perspective of practicality, dynamic intrusion may be confused under non-line-of-sight (NLOS) conditions and the continuous operation of passive positioning system will bring much unnecessary computation. In this paper, we propose an enhanced CSI-based indoor positioning system with pre-intrusion detection suitable for NLOS scenarios (C-InP). It mainly consists of two modules: intrusion detection and positioning estimation. The introduction of detection module is a prerequisite for positioning module. In order to improve the discrimination of features under NLOS conditions, we propose a modified calibration method for phase transformation while the amplitude outliers are filtered by the variance distribution with the median sequence. In addition, binary and improved multiple support vector classification (SVC) models are established to realize NLOS intrusion detection and high-discrimination fingerprint localization, respectively. Comprehensive experimental verification is carried out in typical indoor scenarios. Experimental results show that C-InP outperforms the existing system in NLOS environments, where the mean distance error (MDE) reached 0.49 m in the integrated room and 0.81 m in the complex garage, respectively.

scholarly journals Application-Level Unsupervised Outlier-Based Intrusion Detection and Prevention

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Omar Iraqi ◽  
Hanan El Bakkali
Keyword(s):  
Intrusion Detection ◽  
Variable Structure ◽  
Behavioral Model ◽  
Relevant Information ◽  
Distance Functions ◽  
Business Context ◽  
Fine Grained ◽  
Detection Algorithms ◽  
Software Applications ◽  
Intrusion Detection And Prevention

As cyber threats are permanently jeopardizing individuals privacy and organizations’ security, there have been several efforts to empower software applications with built-in immunity. In this paper, we present our approach to immune applications through application-level, unsupervised, outlier-based intrusion detection and prevention. Our framework allows tracking application domain objects all along the processing lifecycle. It also leverages the application business context and learns from production data, without creating any training burden on the application owner. Moreover, as our framework uses runtime application instrumentation, it incurs no additional cost on the application provider. We build a fine-grained and rich-feature application behavioral model that gets down to the method level and its invocation context. We define features to be independent from the variable structure of method invocation parameters and returned values, while preserving security-relevant information. We implemented our framework in a Java environment and evaluated it on a widely-used, enterprise-grade, and open-source ERP. We tested several unsupervised outlier detection algorithms and distance functions. Our framework achieved the best results in terms of effectiveness using the Local Outlier Factor algorithm and the Clark distance, while the average instrumentation overhead per intercepted call remains acceptable.

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