The proliferation of IoT systems, has seen them targeted by malicious third parties. To address this challenge, realistic protection and investigation countermeasures, such as network intrusion detection and network forensic systems, need to be effectively developed. For this purpose, a well-structured and representative dataset is paramount for training and validating the credibility of the systems. Although there are several network datasets, in most cases, not much information is given about the Botnet scenarios that were used.

  • IoT
  • Last Updated On: 
    Wed, 10/16/2019 - 02:53

    One of the major research challenges in this field is the unavailability of a comprehensive network based data set which can reflect modern network traffic scenarios, vast varieties of low footprint intrusions and depth structured information about the network traffic. Evaluating network intrusion detection systems research efforts, KDD98, KDDCUP99 and NSLKDD benchmark data sets were generated a decade ago. However, numerous current studies showed that for the current network threat environment, these data sets do not inclusively reflect network traffic and modern low footprint attacks.

  • Artificial Intelligence
  • Last Updated On: 
    Wed, 10/16/2019 - 02:31

    The modified CASIA dataset is created for research topics like: percetual image hash, image tampering detection, user-device physical unclonable function and so on. 

  • Image Processing
  • Last Updated On: 
    Tue, 10/15/2019 - 03:30

    We captured ten days real-world DNS traffic from campus network comprising of 4000 hosts in peak load hours.

  • Security
  • Last Updated On: 
    Tue, 10/22/2019 - 11:07


    每个特定的txt文档包含500个样本数据,平均分为5类,分别表示为N = 5,12,18,23,30。

  • Security
  • Last Updated On: 
    Fri, 10/04/2019 - 03:34

    This study seeks to obtain data which will help to address machine learning based malware research gaps. The specific objective of this study is to build a benchmark dataset for Windows operating system API calls of various malware. This is the first study to undertake metamorphic malware to build sequential API calls. It is hoped that this research will contribute to a deeper understanding of how metamorphic malware change their behavior (i.e. API calls) by adding meaningless opcodes with their own dissembler/assembler parts.

  • Security
  • Last Updated On: 
    Tue, 07/30/2019 - 11:07

    The compressed file contains C++ source code for performance measurement

  • Security
  • Last Updated On: 
    Sun, 07/07/2019 - 04:11

    Dataset for an article in IEEE Transactions on Industrial Informatics

  • Standards Research Data
  • Last Updated On: 
    Sat, 06/15/2019 - 12:01

    The malicious traffic detection system monitors the communication between the industrial equipment and analyzes the protocol in real time. At the same time, we launch a variety of attacks on the industrial system, such as Denial of Service attack, Man-in-the-Middle attack and so on. These attacks are also the major threat in the ICS currently. Then, we collect and classify different kinds of attack flow. These flows are intercepted from multiple collection stations during different periods.

  • Communications
  • Last Updated On: 
    Thu, 05/30/2019 - 04:51

    The data that we used to test the performance of different encryption methods

  • Security
  • Last Updated On: 
    Wed, 05/29/2019 - 04:07