Bluetooth communication is widely adopted in IoMT devices due to its various benefits. Nevertheless, because of its simplicity as a personal wireless communication protocol, Bluetooth lacks the security mechanisms which may result in devastating outcomes for patients treated using wireless medical devices.

Figure Data Backup for paper, "Co-Evolution of Malware Threats in the U.S. Commercial Sector and Defense Industrial Base"

Producing secure software is challenging. The poor usability

of security Application Programming Interfaces (APIs) makes this even

harder. Many recommendations have been proposed to support developers

by improving the usability of cryptography libraries and APIs; rooted in

wider best practice guidance in software engineering and API design. In

this SLR, we systematize knowledge regarding these recommendations.

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.

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.

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.

'Test Dataset' folder:

-Real_sk:  random generated secret keys datasets

-Trace_data: traces generated from chosen ciphertexts

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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Simulation Code