Cyber Security

The dataset is generated by performing different Man-in-the-Middle (MiTM) attacks in the synthetic cyber-physical electric grid in RESLab Testbed at Texas AM University, US. The testbed consists of a real-time power system simulator (Powerworld Dynamic Studio), network emulator (CORE), Snort IDS, open DNP3 master, SEL real-time automation controller (RTAC), and Cisco Layer-3 switch. With different scenarios of MiTM attack, we implement a logic-based defense mechanism in RTAC and save the traffic data and related cyber alert data under the attack.


This dataset is used to illustrate an application of the "klm-based profiling and preventing security attack (klm-PPSA)" system. The klm-PPSA system is developed to profile, detect, and then prevent known and/or unknown security attacks before a user access a cloud. This dataset was created based on “a.patrik” user logical attempts scenarios when accessing his cloud resources and/or services. You will find attached the CSV file associated with the resulted dataset. The dataset contains 460 records of 13 attributes (independent and dependent variables).


Distributed Denial of Service (DDoS) attacks first appeared in the mid-1990s, as attacks stopping legitimate users from accessing specific services available on the Internet. A DDoS attack attempts to exhaust the resources of the victim to crash or suspend its services. Time series modeling will help system administrators for better planning of resource allocation to defend against DDoS attacks. Different Time Series analysis techniques are applied to detect the DDoS attacks.


The availability of labelled Cyber Bulling Types dataset has been exhibited for high profile Natural Language Processing (NLP), which constantly leads the advancement of constructing and model creation-based text. I aim at extracting diverse and efficient Cyber Bully Tweets from the Twitter Social Media Platform. This dataset contains 5 types of cyber bullying samples. They are

1.    Sexual Harassment

2.    Doxing

3.    Cyberstalking


66% of Prestashop websites are at high risk from cyber criminals.

Common Hacks in Prestashop


This dataset supports researchers in the validation process of solutions such as Intrusion Detection Systems (IDS) based on artificial intelligence and machine learning techniques for the detection and categorization of threats in Cyber Physical Systems (CPS). To that aim, data have been acquired from a water distribution hardware-in-the-loop testbed which emulates water passage between nine tanks via solenoid-valves, pumps, pressure and flow sensors. The testbed is composed by a real partition which is virtually connected to a simulated one.


This dataset is captured from a Mirai type botnet attack on an emulated IoT network in OpenStack. Detailed information on the dataset is depicted in the following work. Please cite it when you use this dataset for your research.

  • Kalupahana Liyanage Kushan Sudheera, Dinil Mon Divakaran, Rhishi Pratap Singh, and Mohan Gurusamy, "ADEPT: Detection and Identification of Correlated Attack-Stages in IoT Networks," in IEEE Internet of Things Journal.


Presented here is a dataset used for our SCADA cybersecurity research. The dataset was built using our SCADA system testbed described in our paper below [*]. The purpose of our testbed was to emulate real-world industrial systems closely. It allowed us to carry out realistic cyber-attacks.



Cyber-Physical Production Systems (CPPS) are the key enabling for industrial businesses and economic growth. The introduction of the Internet of Things (IoT) in industrial processes represents a new Internet revolution, mostly known as 4th Industrial Revolution, towards the Smart Manufacturing concept. Despite the huge interest from the industry side to innovate their production systems, in order to increase revenues at lower costs, the IoT concept is still immature and fuzzy, which increases security related risks in industrial systems.


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.