Complexeventprocessingand the CoMiFinproject

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1 Complexeventprocessingand the CoMiFinproject Gönczy László Budapesti Műszaki és Gazdaságtudományi Egyetem Méréstechnika és Információs Rendszerek Tanszék 1

2 CEP basics Complex event o A logical composition of atomic events Main characteristics o Timing(e.g., sliding window) o Asynchron operation o Causility, hierarchy of events o Correlation SQL-like languages o E,g.. EPL: Event Processing Language, JAQL, o Queries as basic steps of event processing Distributed data sources o Databases, online transaction handling systems, monitoring systems, etc. Scalability o Distributed, cloud-based deplyoment o ~100k/sec transcations 2

3 CEP applicationareas Business&finance o Investments, stock exchange o Treasury o Risk assessment o Transport tracking Business Activity Monitoring Online fraud detection/prevention o Transaction scanning o Online betting(pl. UEFA) Operation of large IT systems o Detection complex patterns in operation o Metrics evaluation Security o E.g.,. Early detection of ddos 3

4 Map odata split Reduce o Data processing Example Map/Reducealgorithm osplit a text towords, countoccurencesoccurences o Implementation in multiple languages Apache implementation o Distributed architecture o Hadoop(+ Hadoop Distributed File System) o Schedule : Job Tracker, Task Tracker 4

5 Esper Drools Fusion CEP tools IBM InfoSphereStreams(System S) OpenESB- Intelligent Event Processor Apache Hadoop + extending projects Main features o Event processing logic o Throughput o Requested response time( low latency ) 5

6 Casestudy: CoMiFinproject From public material of the CoMiFin consortium 6

7 CoMiFin Communication Middleware for Financial Infrastructures Motivation o Banking systems are more and more dependable on IT services o Attacks are becoming more sophisticated o Criticalinfrastructures(network, telco, powersupply) interconnected o Traditionaloffline communicationis slow(e.g., 8 daystoclosea bug) Aim o Schemetosetupand managea secureenvironment(software, hardware, monitoring tools, etc.) forinformationexchangeand analysis Demonstrator lead by a BME spin-off(optxware) 7

8 Information Federation Purpose: detect events(attacks) in a collaborative way o Security: collaboration, not competition o Collaborative network of certified participants o Security measures implemented o Resilient by its distributed nature o Systematicmodel-basedmanagement and monitoring Privacy assurance o Working on data about transactions o No transaction details o Anonymization o seecomifin.eu

9 Example: logicalinterconnections 9

10 Attacktypes(IT) Distributed Denial of Service (ddos) oe.g., botnets Man inthemiddle oe.g., phishing Identity theft and many combinations 10

11 Attacksurface Banking systems with lot of entry points Martin Goulet and Morten Nygaard, Managing 21st Century Business and Technology Innovation: Reduce Operational Risk, Enable Compliance, Protect Privacy with IBM System z, IBM s Global Banking community, ibm.com/banking. 11

12 CoMiFintopology ENEL TELECOM UNICREDIT LLYODS TSB Control Centre CoMiFin Control Service Centre AT&T AIG Intra-communications Inter-communications SWIFT 12

13 SemanticRoomconcept Basic unit of information federation Logical separation of entities SR features: a SaaS offerof theunderlying CoMiFin infrastructure o Membership management o Resource allocation o Monitoring o Information exchange 13

14 Online dataanalysis(cep) 14

15 Logicalcomponents 15

16 Model-drivensystemmonitoring 16

17 Resource level o Network, Disk o Memory, CPU o SR Administrator View Application level o Event processing o Evaluation of alerts Levels for metrics o SR Administrator, o SR Manager View o FI specific parts. SR Member Business level o What CoMiFin produces? o Alerts are also displayed o SR Manager, SR Member

18 Example:Metric definition Name Definition Performance capability of web server The number of threads that can receive and process HTTP requests. States Normal Operational State: The number of threads matches the estimated capacity of the underlying resources. Measuring Overloaded Operational State: The number of threads are higher than the maximal estimated for the underlying resources. Unusable Operational State: The number of processing threads cannot be determined. Measurement Unit piece Range non-negative integer Type Low level The web server should be instrumented with an SNMP agent exposing this attribute. Frequency periodical, every 3 minutes Evaluation Method classification (see states above) Time range evaluation is instantaneous

19 Architectural Example: Monitoring of the Gateway

20 Advanced Evaluation Simple evaluations (average, etc.) Rule-based evaluation with Drools Information manager is such an evaluator, calculating trust Evaluation with CoMiFin CEP?

21 Evaluation of measurements Advanced Evaluator plugin for monitoring Nagios integrated with Drools o Nagios: monitoring o Drools: correlation of events sent by Nagios Motivation o CoMiFin is itself a critical infrastructure advanced monitoring of resource should be ensured e.g. COBIT/SOX/ directives odetecting meaningful patterns within CoMiFin could be beneficial

22 Overview of advanced evaluation Infrastructure Nagios Nagios stores the plugins output in the database Event Correlation Monitoring Database data We check the database periodically for new information and forward it to the rule engine Rule Engine advice, alerts, action Alert Rules logic The rule engine matches the rules against the received information If a rule matched we could react

23 CoMiFinControlLoop

24 Examplemetric Name Definition Performance capability of web server The number of threads that can receive and process HTTP requests. States Normal Operational State: The number of threads matches the estimated capacity of the underlying resources. Measuring Overloaded Operational State: The number of threads are higher than the maximal estimated for the underlying resources. Unusable Operational State: The number of processing threads cannot be determined. Measurement Unit piece Range non-negative integer Type Low level The web server should be instrumented with an SNMP agent exposing this attribute. Frequency periodical, every 3 minutes Evaluation Method classification (see states above) Time range evaluation is instantaneous 24

25 Rule-basedeventdetection 25

26 Session Hijack detection Session hijack: modify the sesison by observing/modifying user communication Configuration: sample banking app o User management o Transaction management Monitoring of application level information osession ID o Client data fault injection oattacks

27 Session Hijacking Application Server Bad Guy Ordinary Client

28 Session hijackdetection CheckingIP and session ID withdrools WARNING: possible session hijack: { currentaddress= , remoteaddress= , sessionid=21...b6 } and the possible attacker with the same session: { currentaddress= , remoteaddress= , sessionid=21...b6 }

29 Demo 2: Missingbackup problem Information from multiple aplications/ event sources Related standards o e.g. COBIT PO-4 Define the IT Processes, Organization and Relationships o COBIT PO-9 Manage IT Human Resources 0 - OK 1 - WARNING 1 Backup failure Time Value Bckp Value Admin Problem stil exists Administrator absent

30 Droolsbaseddetection Nagios (Simulator) Event Correlation Alert Rules logic data Rule Engine advice, alerts, action

31 Connectivity of Semantic Rooms Vision: CoMiFin as a platform (D6.5) o Framework for information sharing among FIs o A trusted third party platform Connectivity in CoMiFin o Allows for propagating alerts among SRs oimproves the quality of Event Processing with additional input o Improves the capability of CoMiFin to detect attacks ofacilitates the creation of new services built on a combination of SRs improves the ability of FIs to prevent attacks

32 Architecture Financial Institutions (FI) emulated by Gateways Monitoring and evaluation SLA management, visualization Logical management (SR creation, ) Reliable communication (currently: Java Message Service) CoMiFinmanagement components (OptXware testbed, Budapest) ED Event Processing (DHT) (ED Testbed, Rome) IBM Event Processing (AGILIS) (IBM Testbed, Haifa) 32

33 What to Measurein CoMiFin? Message processing performance (anonymization, filtering,aggregation) Input from FI Message compliance Resource level metrics (all components) Communication performance Comm. errors Trust of Financial Institutions Event processing metrics Alerts

34 Sampleresults 34

35 SR Composition (1) Vertical, hierarchical composition othe goal of the collaborating SRs is identical othe topmost SR has an aggregatedglobal view o The underlying SRs have detailed local view o Example: Banks and the Financial Supervisory Authority Authority Headquarters Branches

36 SR Composition (2) Horizontal, sequential composition o Communicating SRs have different goals o Complex/combined attacks can be detected by information fusion oe.g., alerts generated in PortscanSR contributes to the Blacklist managed in MitM SR

37 Demo Scenario SR1 (Port Scanning) is setup Alertsgenerated by SR1 SR2 (MitM) is setup Alertsgenerated by SR2 onitsown

38 Demo -Scenario SR1 (Port Scanning) is setup SR Connectivity between the two SRsis activated SRC notifies SR2 about suspicious IPs SR2 (MitM) is setup Attacks from suspicious IPs also considered

39 SR Connectivity Metrics # of sent and received messages # of corrupt messages Time required to forward the messages

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