Alerts Analysis and Visualization in Network-based Intrusion Detection Systems

No abstract is available for this paper.

• Publication year

  2010

• Venue

  2010 IEEE Second International Conference on Social Computing

• Publication date

  2010-08-20

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1109/SocialCom.2010.120
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Visual support for analyzing network traffic and intrusion detection events using TreeMap and graph representations

  2009cited by this paper
• RAAS: a reliable analyzer and archiver for snort intrusion detection system

  2007cited by this paper
• Tool update: high alarm count issues in IDS rainstorm

  2006cited by this paper
• An intelligent, interactive tool for exploration and visualization of time-oriented security data

  2006cited by this paper
• Visualizations to improve reactivity towards security incidents inside corporate networks

  2006cited by this paper
• Understanding multistage attacks by attack-track based visualization of heterogeneous event streams

  2006influential reference
• A visualization paradigm for network intrusion detection

  2005cited by this paper
• Preserving the big picture: visual network traffic analysis with TNV

  2005cited by this paper
• A user-centered approach to visualizing network traffic for intrusion detection

  2005cited by this paper
• SnortView: visualization system of snort logs

  2004cited by this paper
• Clustering intrusion detection alarms to support root cause analysis

  2003cited by this paper
• Data Mining for Network Intrusion Detection

  2002cited by this paper
• Data Mining - Concepts and Techniques

  2002cited by this paper
• Applying data mining to intrusion detection: the quest for automation, efficiency, and credibility

  2002cited by this paper
• Using q-grams in a DBMS for Approximate String Processing.

  2001cited by this paper
• Temporal sequence learning and data reduction for anomaly detection

  1999cited by this paper
• The Advanced Computing Systems Association Proceedings of the Workshop on Intrusion Detection and Network Monitoring Learning Program Behavior Profiles for Intrusion Detection Learning Program Behavior Prooles for Intrusion Detection

  year unknowncited by this paper

• Hybrid Machine Learning Algorithm for Intrusion Detection Systems

  2024cites this paper
• PROPOSTA DE UMA CLASSIFICAÇÃO DE AGRUPAMENTO DINÂMICA BASEADA EM ALERTAS DE UM IDS SNORT

  2020cites this paper
• Hybrid Approach for Network Intrusion Detection System Using Random Forest Classifier and Rough Set Theory for Rules Generation

  2019cites this paper
• VISNU: A Novel Visualization Methodology of Security Events Optimized for a Centralized SOC

  2018cites this paper
• Entropy-Based Anomaly Detection in a Network

  2018cites this paper
• A Survey on Information Visualization for Network and Service Management

  2016cites this paper
• Mining intrusion detection alert logs to minimise false positives & gain attack insight

  2016cites this paper
• Attack Type Active Attack Passive Attack Active attack Masquerade Alteration of message DOS Spoofing Replay Modification

  2016cites this paper
• Survey of Adaptive Resonance Theory Techniques in IDS

  2014cites this paper
• The State of the Art in Intrusion Prevention and Detection

  2014cites this paper
• The State of the Art in Intrusion Prevention and Detection

  2014cites this paper
• Introduction to Wireless Intrusion Detection Systems

  2014cites this paper
• Novel Visual Metaphors for Multivariate Networks

  2013cites this paper
• Intrusion detection technique by using fuzzy ART on computer network security

  2012cites this paper
• Visual Analytic Agent-Based Framework for Intrusion Alert Analysis

  2012cites this paper
• Comparison of Network Intrusion Detection Systems in cloud computing environment

  2012cites this paper
• VisSRA: Visualizing Snort Rules and Alerts

  2012cites this paper