Prasad Purnaye's picture
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First Name: 
Prasad
Last Name: 
Purnaye
Affiliation: 
Research Student

Datasets & Competitions

Cloud forensics is different than digital forensics because of the architectural implementation of the cloud. In an Infrastructure as a Service (IaaS) cloud model. Virtual Machines (VM) deployed over the cloud can be used by adversaries to carry out a cyber-attack using the cloud as an environment.

Instructions: 

 

 

 

 

 

 

 

 

About the dataset
The dataset generated is a KVM monitoring dataset however we proposed a novel feature-set. The methodology used to generate these novel features are under publication and will be updated once the research article is published. This is one portion of the dataset. where the features can be used to train ML models for evidence detection.  

The second portion of the dataset is published under the standard dataset of IEEE Dataport under the name of Memory Dumps of Virtual Machines for Cloud Forensics.  

How to use
These two datasets can be used together as they are the outcome of the same experiment. Memory dumps have timestamp and VMID, UUID features. 
or 
This Dataset can be used to study the impact of an attack (origin) on the Rate of Resource utilization of a VM monitored at the hypervisor.

 

Sr No

Category

Feature

Description

1

Meta-data

LAST_POLL

epoch timestamp

2

VMID

The ID of the VM

3

UUID

unique identifier of the domain

4

dom

domain name

5

Network

rxbytes_slope

Rate of received bytes from the network

6

rxpackets_slope

Rate of received packets from the network

7

rxerrors_slope

Rate of the number of receive errors from the network

8

rxdrops_slope

Rate of the number of received packets dropped from the network

9

txbytes_slope

Rate of transmitted bytes from the network

10

txpackets_slope

Rate of transmitted packets from the network

11

txerrors_slope

Rate of the number of transmission errors from the network

12

txdrops_slope

Rate of the number of transmitted packets dropped from the network

13

Memory

timecpu_slope

Rate of time spent by vCPU threads executing guest code

14

timesys_slope

Rate of time spent in kernel space

15

timeusr_slope

Rate of time spent in userspace

16

state_slope

Rate of running state

17

memmax_slope

Rate of maximum memory in kilobytes

18

mem_slope

Rate of memory used in kilobytes

19

cpus_slope

Rate of the number of virtual CPUs chaged

20

cputime_slope

Rate of CPU time used in nanoseconds

21

memactual_slope

Rate of Current balloon value (in KiB)

22

memswap_in_slope

Rate of The amount of data read from swap space (in KiB)

23

memswap_out_slope

Rate of The amount of memory written out to swap space (in KiB)

24

memmajor_fault_slope

Rate of The number of page faults where disk IO was required

25

memminor_fault_slope

Rate of The number of other page faults

26

memunused_slope

Rate of The amount of memory left unused by the system (in KiB)

27

memavailable_slope

Rate of The amount of usable memory as seen by the domain (in KiB)

28

memusable_slope

Rate of The amount of memory that can be reclaimed by balloon without causing host swapping (in KiB)

29

memlast_update_slope

Rate of The timestamp of the last update of statistics (in seconds)

30

memdisk_cache_slope

Rate of The amount of memory that can be reclaimed without additional I/O, typically disk caches (in KiB)

31

memhugetlb_pgalloc_slope

Rate of The number of successful huge page allocations initiated from within the domain

32

memhugetlb_pgfail_slope

Rate of The number of failed huge page allocations initiated from within the domain

33

memrss_slope

Rate of Resident Set Size of the running domain's process (in KiB)

34

Disk

vdard_req_slope

Rate of the number of reading requests on the vda block device

35

vdard_bytes_slope

Rate of the number of reading bytes on the vda block device

36

vdawr_reqs_slope

Rate of the number of write requests on the vda block device

37

vdawr_bytes_slope

Rate of the number of write requests on vda  the block device

38

vdaerror_slope

Rate of the number of errors in the vda block device

39

hdard_req_slope

Rate of the number of read requests on the hda block device

40

hdard_bytes_slope

Rate of the number of read bytes on the had block device

41

hdawr_reqs_slope

Rate of the number of write requests on the hda block device

42

hdawr_bytes_slope

Rate of the number of write bytes on the hda  block device

43

hdaerror_slope

Rate of the number of errors in the hda block device

44

TARGET

Status

Attack/Normal

 

Categories:
732 Views

The dataset contains memory dump data which is generated continuously. For the experiment we carried out, we implemented the volatile data dump module which generated around 360 VM memory dump images of average size 800Mb each (Total 288GB). These data files are compressed using gzip utility. Further zipped to 79.5GB one single file of memory evidence.
Out of these preserved and stored memory dump dataset, 79 files of size 17.3GB were generated during the attack. This means the data 21.76% of data (in size) is potential evidence.

Categories:
449 Views

Intrusion Detection System can be build for private cloud using OpenNebula. OpenNebula is a cloud computing platform for managing heterogenous distributed data center infrastructure. The database is generated using a private cloud setup using KVM and OpenNebula. OpenNebula provides API to monitor Virtual Machines (VMs) running on the infrastructure. Total 6 VMs were deployed on the infrastructure. The monitoring data was collected over 63 Hours. Attacks were simulated on few of the VMs for variable time duration.

Categories:
440 Views