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Tesis Doctoral Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems Defense udiger Gad Universidad de C´ adiz 2015-07-29

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Page 1: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Tesis Doctoral

Event-driven Principles and Complex Event Processing forSelf-adaptive Network Analysis and Surveillance Systems

Defense

Rudiger Gad

Universidad de Cadiz

2015-07-29

Page 2: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Outline

1 Introduction

2 Thesis Overview

3 Two Highlights

4 Summary and Conclusion

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 3: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Outline

1 Introduction

2 Thesis Overview

3 Two Highlights

4 Summary and Conclusion

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 4: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Motivation

IT is used ubiquitously.

Non-operational IT?→ Severe Consequences!

Importance of IT: Critical

Computer Networks

Fundamental for IT OperationNon-operational Networks? → Non-operational IT!Importance of Networks: Critical

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 5: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Assure Operational Computer Networks

BasisInformation

DetailedAccurateUp-to-date. . .

Network Analysis and Surveillance(“Network Reconnaissance” or “Network Monitoring”)

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 6: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Network Analysis and Surveillance (NAaS)

Challenging

DistributionSizeChangeTimelinessData Volume. . .

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 7: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Event-driven Principles and Complex Event Processing (CEP) for NAaS

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 8: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Event-driven Principles and Complex Event Processing (CEP) for NAaS

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 9: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Event-driven Principles and Complex Event Processing (CEP) for NAaS

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 10: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Event-driven Principles and Complex Event Processing (CEP) for NAaS

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 11: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Event-driven Architecture (EDA) and CEP for NAaS

Powerful Capabilities

Existing Related Work

Related Work, Limitations

Focused on Specific Use CasesConceptual/Architectural FocusReal-world Applicability?

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 12: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Outline

1 Introduction

2 Thesis Overview

3 Two Highlights

4 Summary and Conclusion

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 13: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Aims

Overarching Approach

Convergence of Heterogeneous DataSources

Flexible

Applicability

Performance

Complexity vs. Usability

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 14: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Thesis Outline

Analysis of Important Properties and Requirements

Architecture for Overarching Event-driven NAaS

Evaluation Prototype

Flexibility and Convergence of Data SourcesPerformance

Improvements in Distributed Contexts

Coalescence Problems, Analysis and Solutions

Improvements for Individual Components

Threats to Validity

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 15: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Thesis Outline

Analysis of Important Properties and Requirements

Architecture for Overarching Event-driven NAaS

Evaluation Prototype

Flexibility and Convergence of Data SourcesPerformance

Improvements in Distributed Contexts

Coalescence Problems, Analysis and Solutions

Improvements for Individual Components

Threats to Validity

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 16: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

General Architecture

Important Properties and Requirements

Event-driven Architecture

Focus on the Essentials

Unified Internal Event Representation

Components

Sensors (S)Event Transformer (ET). . .

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 17: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

General Architecture

Important Properties and Requirements

Event-driven Architecture

Focus on the Essentials

Unified Internal Event Representation

Components

Sensors (S)Event Transformer (ET). . .

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 18: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Prototype Implementation and Evaluation of Flexibility and Convergence

Prototype Based on Architecture

Evaluation of Flexibility andConvergence of Data Sources

Step-wise Defined Goals

Basic SystemRelocating FunctionalityConvergence of Sensors. . .

Results

Flexible NAaSConvergence of Sensors for NAaS

Figure: Evaluation Prototype

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 19: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Prototype Implementation and Evaluation of Flexibility and Convergence

Prototype Based on Architecture

Evaluation of Flexibility andConvergence of Data Sources

Step-wise Defined Goals

Basic System

Relocating FunctionalityConvergence of Sensors. . .

Results

Flexible NAaSConvergence of Sensors for NAaS

Figure: Evaluation Prototype

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 20: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Prototype Implementation and Evaluation of Flexibility and Convergence

Prototype Based on Architecture

Evaluation of Flexibility andConvergence of Data Sources

Step-wise Defined Goals

Basic SystemRelocating Functionality

Convergence of Sensors. . .

Results

Flexible NAaSConvergence of Sensors for NAaS

Figure: Evaluation Prototype

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 21: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Prototype Implementation and Evaluation of Flexibility and Convergence

Prototype Based on Architecture

Evaluation of Flexibility andConvergence of Data Sources

Step-wise Defined Goals

Basic SystemRelocating FunctionalityConvergence of Sensors

. . .

Results

Flexible NAaSConvergence of Sensors for NAaS

Figure: Evaluation Prototype

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 22: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Prototype Implementation and Evaluation of Flexibility and Convergence

Prototype Based on Architecture

Evaluation of Flexibility andConvergence of Data Sources

Step-wise Defined Goals

Basic SystemRelocating FunctionalityConvergence of Sensors. . .

Results

Flexible NAaSConvergence of Sensors for NAaS Figure: Evaluation Prototype

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 23: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Performance Evaluation

Evaluation Setup

Packet Capturing as “Worst Case” Scenario

Results

Example ResultsIt works.Most Critical: Sensor

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 24: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Performance Evaluation

Evaluation Setup

Packet Capturing as “Worst Case” Scenario

Results

Example Results

It works.Most Critical: Sensor

0

20

40

60

80

100

100 150 200 250 300

Cap

ture

Rat

io [%

]

Packet Rate [kpps]

clj Pcap Sing.

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 25: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Performance Evaluation

Evaluation Setup

Packet Capturing as “Worst Case” Scenario

Results

Example ResultsIt works!Most Critical: Sensor

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 26: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Outline

1 Introduction

2 Thesis Overview

3 Two Highlights

4 Summary and Conclusion

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 27: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Sensors: Cooperation for Improving the Performance, Foundations

Paper: 28th IEEE AINA 2014Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 28: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Sensors: Cooperation for Improving the Performance, Foundations

Paper: 28th IEEE AINA 2014Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 29: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Sensors: Cooperation for Improving the Performance, Foundations

Paper: 28th IEEE AINA 2014Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 30: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Sensors: Cooperation for Improving the Performance, Foundations

Paper: 28th IEEE AINA 2014Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 31: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Sensors: Cooperation for Improving the Performance, Foundations

Paper: 28th IEEE AINA 2014Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 32: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Cooperative Sensors, Architecture and Application

Sensors: Hosts A to D

Controller: Host E

LogicData MergingData Consumer

Traffic Generation

Host A → Host D

Paper: IEEE ICC 2015

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 33: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Cooperative Sensors: Performance, Scalability, and Traffic Load

0

25

50

75

100

100 200 300 400 500 600

Cap

ture

Rat

io [%

]

Packet Rate [kpps]1 Sensor2 Sensors

3 Sensors4 Sensors

0

100

200

300

400

500

600

100 200 300 400 500 600

Tra

ffic

Loa

d [M

bps]

Packet Rate [kpps]1 Sensor2 Sensors

3 Sensors4 Sensors

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 34: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Cooperative Sensors: Improving Operation and Usability via Self-adaptivity

Problem

Complexity ofOperation & Usability

Solution

Self-adaptation

Example

On-demand Cooperation

Aims

Capture as much as possible.Avoid overload.Reduce # of sensors.

Apply cooperation as necessary.

0

100

200

300

400

500

0 10 20 30 40 50 60 70 80 90 100

[kpp

s]

Time [s]

Send 3Send 2Send 1Drp. 1Drp. 2Drp. 3Pkt. Rt.Recv.

Figure: Detailed Results of an Example Experiment

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 35: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Improvements for Individual Components

Example: Sensor

Packet Capturing with Java & Clojure

Analyze the optimization potential in various areas.

Paper: 20th IEEE ISCC 2015

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 36: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Raw Data Acquisition: Improved Method vs. Old Method

0 1000 2000 3000 4000

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 0 25 50 75 100

[kpp

s]

Rel

. Std

. Dev

. [%

]

Packet Size [x100 byte]

Th.Pkt.Rt. 1 Gbps [kpps]Cap.Rt. (Dbl.Buf.) [kpps]CR Rel.SD (Dbl.Buf.) [%]

Th.Pkt.Rt. 10 Gbps [kpps]Cap.Rt. (Non-B.) [kpps]CR Rel.SD (Non-B.) [%]

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 37: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Example Results of Self-adaptive Performance-based Adjustment

0 200 400 600 800

1000 1200 1400

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 0 2 4 6 8 10 12 14

[kpp

s]

# of

Rul

es

Time [s]

Cap. Rt. [kpps]Pkt. Rt. [kpps]

Drop Rt. [kpps]Min. # Rules

# Act. Rules

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 38: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Outline

1 Introduction

2 Thesis Overview

3 Two Highlights

4 Summary and Conclusion

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 39: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Summary

Computer Networks: Critical Importance

Assuring Operating Networks → Information

Network Analysis and Surveillance(Network Reconnaissance, Network Monitoring)

“Good” Information → challenging.

(Contradicting) Requirements and Properties

EDA and CEP to the Rescue

Related Work: Too Focused, Real World Applicability?

Thesis Aims: Overarching and Applicable NAaS

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 40: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Answered Research Questions (I)

1 What are important properties and requirements foroverarching and flexible NAaS?

→ Enumeration and Discussion of Properties andRequirements

2 Does our NAaS approach offer convergence of datasources and is it flexible?

→ Convergence works.→ The architecture is flexible.

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 41: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Answered Research Questions (I)

1 What are important properties and requirements foroverarching and flexible NAaS?

→ Enumeration and Discussion of Properties andRequirements

2 Does our NAaS approach offer convergence of datasources and is it flexible?

→ Convergence works.→ The architecture is flexible.

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 42: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Answered Research Questions (II)

3 What are the performance limits and what is the mostrelevant bottleneck?

→ Detailed Performance Analysis→ CEP and EDA for NAaS works.→ Most Important Bottleneck: Sensors

4 Can the most relevant performance bottleneck beaddressed by leveraging distributed approaches?

→ Cooperative Sensors

5 Can the increased complexity of distributedapproaches be addressed?

→ Self-adaptive On-demand Cooperation

0

20

40

60

80

100

100 150 200 250 300

Cap

ture

Rat

io [%

]

Packet Rate [kpps]

clj Pcap Sing.

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 43: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Answered Research Questions (II)

3 What are the performance limits and what is the mostrelevant bottleneck?

→ Detailed Performance Analysis→ CEP and EDA for NAaS works.→ Most Important Bottleneck: Sensors

4 Can the most relevant performance bottleneck beaddressed by leveraging distributed approaches?

→ Cooperative Sensors

5 Can the increased complexity of distributedapproaches be addressed?

→ Self-adaptive On-demand Cooperation

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 44: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Answered Research Questions (II)

3 What are the performance limits and what is the mostrelevant bottleneck?

→ Detailed Performance Analysis→ CEP and EDA for NAaS works.→ Most Important Bottleneck: Sensors

4 Can the most relevant performance bottleneck beaddressed by leveraging distributed approaches?

→ Cooperative Sensors

5 Can the increased complexity of distributedapproaches be addressed?

→ Self-adaptive On-demand Cooperation

0

100

200

300

400

500

0 10 20 30 40 50 60 70 80 90 100

[kpp

s]

Time [s]

Send 3Send 2Send 1Drp. 1Drp. 2Drp. 3Pkt. Rt.Recv.

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 45: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Answered Research Questions (III)

6 May the distributed nature of our approach causeadditional performance issues and how can these beaddressed?

→ Problem: Accumulating Data→ Hierarchical Event Patterns, Multi-tiered Setups

7 What is the most relevant performance limit of ourapproach in a non-distributed scenario and how can itbe addressed?

→ Sensor→ Example: Packet Capturing→ Various Improvements

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 46: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Answered Research Questions (III)

6 May the distributed nature of our approach causeadditional performance issues and how can these beaddressed?

→ Problem: Accumulating Data→ Hierarchical Event Patterns, Multi-tiered Setups

7 What is the most relevant performance limit of ourapproach in a non-distributed scenario and how can itbe addressed?

→ Sensor→ Example: Packet Capturing→ Various Improvements

0 200 400 600 800

1000 1200 1400

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 0 2 4 6 8 10 12 14

[kpp

s]

# of

Rul

es

Time [s]

Cap. Rt. [kpps]Pkt. Rt. [kpps]

Drop Rt. [kpps]Min. # Rules

# Act. Rules

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 47: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Publications

Improving Network Traffic Acquisition and Processing with the Java Virtual Machine, R. Gad, M. Kappes,and I. Medina-Bulo, 20th IEEE ISCC 2015, in press

Monitoring Traffic in Computer Networks with Dynamic Distributed Remote Packet Capturing, R. Gad,M. Kappes, and I. Medina-Bulo, IEEE ICC 2015, in press

Analysis of the Feasibility to Combine CEP and EDA with Machine Learning using the Example ofNetwork Analysis and Surveillance, R. Gad, M. Kappes, and I. Medina-Bulo, JCIS – SISTEDES 2014

Bridging the Gap between Low-level Network Traffic Data Acquisition and Higher-level Frameworks, R.Gad, M. Kappes, and I. Medina-Bulo, IEEE COMPSACW 2014

Header Field Based Partitioning of Network Traffic for Distributed Packet Capturing and Processing, R.Gad, R. Mueller-Bady, M. Kappes, and I. Medina-Bulo, 28th IEEE AINA 2014

Employing the CEP Paradigm for Network Analysis and Surveillance, R. Gad, M. Kappes, J.Boubeta-Puig, and I. Medina-Bulo, AICT 2013

Leveraging EDA and CEP for Integrating Low-level Network Analysis Methods into Modern, DistributedIT Architectures, R. Gad, M. Kappes, J. Boubeta-Puig, and I. Medina-Bulo, JCIS – SISTEDES 2012

Hierarchical events for efficient distributed network analysis and surveillance, R. Gad, M. Kappes, J.Boubeta-Puig, and I. Medina-Bulo, WAS4FI 2012

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 48: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Open Source Software Contributions

Clojure and Java Packet Capturing Libraryhttps://github.com/ruedigergad/clj-net-pcap

Distributed Remote Packet Capturing (DRePCap)https://github.com/fg-netzwerksicherheit/drepcap

clj-jms-activemq-toolkithttps://github.com/fg-netzwerksicherheit/clj-jms-activemq-toolkit

drepcap-sensorhttps://github.com/fg-netzwerksicherheit/drepcap-sensor

drepcap-mergerhttps://github.com/fg-netzwerksicherheit/drepcap-merger

drepcap-frontendhttps://github.com/fg-netzwerksicherheit/drepcap-frontend

Patches for jNetPcap

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 49: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

Conclusion

EDA and CEP for Overarching NAaS

It works!

Improved the state of the art.

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems

Page 50: Tesis Doctoral 0.4cmEvent-driven Principles and Complex

Introduction Thesis Overview Two Highlights Summary and Conclusion

End

Thank you for your attention!

Questions?

Rudiger Gad

[email protected]

[email protected]

Rudiger Gad

Event-driven Principles and Complex Event Processing for Self-adaptive Network Analysis and Surveillance Systems