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.

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This dataset is from apache access log server. It contains: ip address, datetime, gmt, request, status, size, user agent, country, label. The dataset show malicious activity in IP address, request, and so on. You can analyze more as intrusion detection parameter.

Instructions: 

This dataset contains: ip address, datetime, gmt, request, status, size, user agent, country, label. Allowed traffic only from Indonesia, because the web is local purpose, so this dataset assume the traffic from abroad is prohobited.

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This dataset is composed of side channel information (e.g., temperatures, voltages, utilization rates) from computing systems executing benign and malicious code.  The intent of the dataset is to allow aritificial intelligence tools to be applied to malware detection using side channel information.

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'Test Dataset' folder:

-Real_sk:  random generated secret keys datasets

-Trace_data: traces generated from chosen ciphertexts

 

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The Android application samples for evaluation come from the following three sources: the Drebin dataset, AMD dataset, and the Google Play Store. We downloaded 7,681 popular benign applications from Google Play Store. 

Based on the above data sources, the following two datasets were generated for testing: Drebin4000 and AMD6000. 

We randomly selected 4,000 benign samples and 4,000 malicious samples from the Drebin dataset to form the Drebin4000 dataset.

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Cyber attacks are a growing concern for small businesses during COVID-19 . Be Protected While You Work. Upgrade Your Small Business's Virus Protection Today!

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Simulation Code

Instructions: 

To access the code, please click the Link  "Hidden Real Modulus RSA(HRM-RSA)"

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Simulation Code

Instructions: 

To see the code, please Click the URL "Hidden Modulus RSA (HRM-RSA)"?

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Network Address Translation (NAT), which is present in almost all routers and CPEs, maps private IP addresses to routable or public IP addresses. This feature has advantages such as reuse of private IP addresses but also has disadvantages such as creating “Shadow IT” where network admins do not have knowledge of all devices on their network. This dataset contains network traffic that is double-NATed thus replicating the scenario of shadow IT in an enterprise context.

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This data set contains the evaluation results of UMLsecRT:

  • All completed answers to the user-study on the usability of the adapted models.
  • The runtime-measurements and profiling outcomes of the experiment on the DaCapo benchmark.
Instructions: 

All results are formatted as CSV files (exported from LimeSurvey) or as LibreOffice spreadsheets (saved as *.odt)

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