Network security using data mining concepts

Network security using data mining concepts

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  NETWORK SECURITY USING DATAMINING CONCEPTS A SEMINAR ON: SUBMITTED TO: DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING INSTITUTE OF TECHNOLOGY AND MANAGEMENT, GIDA, GORAKHPUR GUIDE: MR. NAFEES AKHTER FAROOQUI BY: JAIDEEP GHOSH
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  OUTLINE INTRODUCTION SECURITY THREATS DATA MINING NETWORKSECURITY INTEGRATION OF DATA MINING CONCEPTS WITH NETWORK SECURITY SYSTEM STRUCTURE ADVANTAGES CONCLUSION INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  INTRODUCTION  Network Securityis a major part of a network that needs to be maintained because information is being passed between computers etc. and is very vulnerable to attack.  Data Mining is the process of extraction of required/specific information from data in database.  Data mining is integrated with network security and can be used with various security tools as well as hacking tool. INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  SECURITY THREATS TYPES OFATTACK ON NETWORK ACTIVE ATTACK PASSIVE ATTACK An event which can target the security region with the intension to harm/access the system without authentication is called Security Threats. Attack is an action is taken against a target with the intension of doing harm. INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  SECURITY THREATS  ACTIVEATTACK: An active attack attempts to alter system resources or affect their operations.  PASSIVE ATTACK: A passive attack attempts to learn or make use of information from the system but does not affects system resources. Some other attacks are:  DISTRIBUTED ATTACK  INSIDER ATTACK  CLOSE-IN ATTACK  PHISHING ATTACK  HIJACK ATTACK  PASSWORD ATTACK INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  SECURITY THREATS VIRUSES ANDWORMS TROJAN HORSES SPAM PHISHING PACKET SNIFFERS MALICIOUSLY CODED WEBSITES PASSWORD ATTACKS HARDWARE ATTACKS AND RESIDUAL DATA FRAGMENTS SHARED COMPUTERS ZOMBIE COMPUTERS AND BOTNETS INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  DATA MINING  DataMining is the process of extraction of required/specific information from data in database.  Data Mining is the process of analysing data from different perspectives and summarising it into useful information.  Data Mining is the process of finding co-relations or patterns among several fields in large relational database. INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  DATA MINING FORNETWORK SECURITY Data Mining is being applied to problems such as intrusion detection and auditing.  ANAMOLY DETECTION TECHNIQUES could be used to detect unusual patterns and behaviours.  LINK ANALYSIS may be used to trace self propagating malicious code to its authors.  CLASSIFICATION may be used to group various cyber attacks and then use the profiles to detect an attack when it occurs.  PREDICTION may be used to determine potential future attacks depending in a way on information learnt about terrorist through E-Mail and Phone conversations. INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  DATA MINING FORINTRUSION DETECTION An Intrusion can be defined as any set of action that attempt to compromise the integrity, confidentiality or availability of a resource. TECHNIQUES OF IDS Anomaly Detection System Misuse Detection System INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  DATA MINING FORINTRUSION DETECTION TYPES OF IDS: Host Based Detects attacks against a single host. Distributed IDS Detects attacks involving multiple hosts. Network Based IDS Detects attacks from any network. INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  NETWORK SECURITY Network Securityconsist of the policies adopted to prevent and monitor unauthorized access, misuse, modification or Daniel of computer networks and network accessible resources. INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  PASSWORD DISCOVERY TABLE #OF CHARACTER POSSIBLE COMBINATION 1 36 2 1300 5 6 Crore HUMAN COMPUTER 3 Min .000018 Sec 2 Hours .00065 Sec 10 Years 30 Sec  Possible character includes the letter A-Z and Numbers 0-9.  Human discovery assumes 1 try in every second.  Computer discovery assumes 1 Million tries per second.  Average time assumes the password would be discovered in approximately half the time it would take to try all possible combinations. INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  ARCHITECTURE OF DATAMINING INETHICAL HACKING TOOLS DATA SOURCE 1 DATA SOURCE 2 DATA SOURCE 3 DATA WAREHOUSE ETHICAL HACKING TOOLS ETL TOOL Fig:1 WORKING ARCHITECTURE OF DATA MINING IN ETHICAL HACKING TOOLS INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  WORM DETECTION Worms areself replicating program, that exploits software vulnerability on a victim or remotely infects other victims. TYPES OF WORMS:  E-mail Worms  Instant Messaging Worms  Internet Worms  File Sharing Network Worms INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  ADVANTAGES  Consumes veryless time in various network tools for decrypting password and other information.  Easy to implement such system.  Helps to record unwanted and unauthorized access on any network. INSTITUTE OF TECHNOLOGY AND MANAGEMENT
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  CONCLUSION The result ofmining in network security may be to discover following type of new information. INSTITUTE OF TECHNOLOGY AND MANAGEMENT  Protection from unauthorized access.  Blocking of IP in case when wrong password attempted several times.  Helps in prevention from various terrorist attacks by recording their information.  Concept can be implemented in various system like: IDS, WORM DETECTION etc.  Helps in Brute Force attack, Password cracking etc.
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