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data mining techniques for malware detection.pptx

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Data Mining Techniques for malware detection -BY Aditya Deshmukh(TE-CSE1) -BY ULLAS KAKANADAN(TE-CSE1) -BY ANKIT GELDA(TE-CSE1) -BY SUDARSHAN RANDIVE(TE- CSE1)

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What is malware? And How is it detected? the different malwares

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Page 1: Data mining techniques for malware detection.pptx

Data Mining Techniques for malware detection

-BY Aditya Deshmukh(TE-CSE1)

-BY ULLAS KAKANADAN(TE-CSE1)

-BY ANKIT GELDA(TE-CSE1)

-BY SUDARSHAN RANDIVE(TE-CSE1)

Page 2: Data mining techniques for malware detection.pptx

CONTENTS

•DATA MINING???•TECHNIQUES???•WHAT IS MALWARE???•TECHNIQUES OVER MALWARE•VARIOUS APPLICATIONS•CONCLUSION•QUESTION?

Page 3: Data mining techniques for malware detection.pptx

WHY MINE DATA???

Lots of data is being collected and warehoused

Potentially valuable resource Stored data grows very fast Information is crucial

Page 4: Data mining techniques for malware detection.pptx

DATA MINING

Extracting IMPLICIT PREVIOUSLY UNKNOWN POTENTIALLY USEFUL

Needed: programs that detect patterns and regularities in the data

Knowledge Discovery in Data

Page 5: Data mining techniques for malware detection.pptx

Knowledge discovery process

Page 6: Data mining techniques for malware detection.pptx

Data, Information, and Knowledge

• Dataoperational or transactional datanonoperational datameta data - data about the data itself

• Informationpatterns, associations, or relationships among all this data

• Knowledge

Page 7: Data mining techniques for malware detection.pptx

How data mining works??

•Classes: Stored data is used to locate data in predetermined groups.

•Clusters: Data items are grouped according to logical relationships or consumer preferences

•Associations: Data can be mined to identify associations.

•Sequential patterns: Data is mined to anticipate behavior patterns and trends

Page 8: Data mining techniques for malware detection.pptx

What is malware???

Short for malicious software old as software itselfprogrammer might create malware most common types Virus Trojans Worms Zombies Spyware

Page 9: Data mining techniques for malware detection.pptx

virus

most well-known

not to cause damage, but to clone itself onto another host

virus causes damage it is more likely to be detected

very small footprint

remain undetected for a very long time

Page 10: Data mining techniques for malware detection.pptx

Worms

very similar to viruses in many ways

worms are network-aware

computer-to-computer hurdle by seeking new hosts on the network

capable of going global in a matter of seconds

Very hard to be controlled and stopped

Page 11: Data mining techniques for malware detection.pptx

trojans

conceal itself inside software

Greeks were able to enter the fortified city of Troy by hiding their soldiers in a big wooden horse given to the Trojans as a gift

Disguises that a trojan can take are only limited by the programmer’s imagination

Cyber-crooks often use viruses, trojans and worms

Trojans also drop spyware

Page 12: Data mining techniques for malware detection.pptx

zombies

works in a similar way to spyware

infection mechanisms remain the same

just sits there waiting for commands from the hacker

infect tens of thousands of computers, turning them into zombie machines

distributed denial of service attack

Page 13: Data mining techniques for malware detection.pptx

Algorithm in data mining

C4.5 and beyond

The k-means algorithm

Support vector machines

The Apriori algorithm

The EM algorithm

Page 14: Data mining techniques for malware detection.pptx

Malware detection techniques

• anomaly-based detection technique

• signature-based detection technique

Page 15: Data mining techniques for malware detection.pptx

K-means algorithm

• takes the number of components of the population equal to the final required number of clusters

• examines each component in the population

• assigns it to one of the clusters depending on the minimum distance

• centroid's position is recalculated everytime a component is added

Page 16: Data mining techniques for malware detection.pptx

flowchart

Page 17: Data mining techniques for malware detection.pptx

ADVANTAGES OF DATA MINING

Marking/Retailing

Banking/Crediting

Law enforcement

Researchers

Page 18: Data mining techniques for malware detection.pptx

DISADVANTAGES OF DATA MINING

Privacy Issues

Security issues

Misuse of information/inaccurate information


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