Please cite the following paper when using this dataset:

N. Thakur, “MonkeyPox2022Tweets: The first public Twitter dataset on the 2022 MonkeyPox outbreak,” Preprints, 2022, DOI: 10.20944/preprints202206.0172.v2



To examine the relationship between meterological context and cellular traffic loads, telecommunication and weather data from the city of Milan is presented. The dataset consists of aggregated telecommunication and weather data from the city of Milan during the period of 1st of November 2013 to 1st of January 2014. The telecommunication data consists of aggregated information of received SMS, sent SMS, incoming call, outgoing call, and internet activity, and is measured through Call Detail Records (CDRs), a measure of volume of cellular traffic.


Nowadays, with the rapid increase in the number of applications and networks, the number of cyber multi-step attacks has been increasing exponentially. Thus, the need for a reliable and acceptable Intrusion Detection System (IDS) solution is becoming urgent to protect the networks and devices. However, implementing a robust IDS needs a reliable and up-to-date dataset in order to capture the behaviors of the new types of attacks, especially multi-step attacks. In this work, a new benchmark Multi-Step Cyber-Attack Dataset (MSCAD) is introduced.


An indoor positioning testbed was set up to collect location fingerprint dataset for multi-floor environments and an extensive fingerprint measurement campaign was carried out at the second and third floors of Wing B of the Faculty of Engineering (FOE), Multimedia University, on its campus in Cyberjaya, Malaysia. The total area of the evaluation site is approximately around 1112 m2.


Measurement trace from wireless network at Dartmouth College.

This dataset includes measurement trace for over 450 access points and several thousand users at dartmouth college.



last modified: 2006-11-14

reason for most recent change: Infocom 2004 trace is added.

short description: Two-year records showing the location (AP association) of each wireless card seen on campus.

description: Over three years of nearly continuous records showing the location (access-point association) of each wireless card seen on campus. We used this data for our study of location predictors, published in [INFOCOM'04 paper] and a subsequent, expanded [technical report]. This data is derived from the syslog data.

The trace used for this paper is gzipped tar file [51MB].


release date: 2004-08-05

methodology: We extracted user traces from dartmouth/campus/syslog. Each user's trace is a series of locations, that is, access-point names. We introduced the special location 'OFF' to represent the user's departure from the network (which occurs when the user turns off their computer or their wireless card, or moves out of range of all access points). The traces varied widely in length (the number of locations in the sequence). Users with longer traces were either more active (using their card more), more mobile (thus changing access points more often), or used the network for a longer period (some users have been on the network since April 2001, and some others have only recently arrived on campus).


sanitization: same as dartmouth/campus/syslog

disruptions to data collection: same as dartmouth/campus/syslog

limitation: same as dartmouth/campus/syslog


Emulating a RT task and measuring the response latency of its thread by means of the high-resolution testing tool Cyclictest. The thread was clocked at 10ms, and a FIFO scheduling policy was used, with the thread being assigned the highest priority. Measurements were performed in distinct testing environments, some of which had best effort concurrent threads competing for the machine resources. For this purpose, the workload generator tool stress was used.


Machine learning methods are poised to drastically improve the performance of many aspects of communication engineering, across all layers of the communication stack: from the physical layer to the application one.  In this competition, we focus on the problem of federated training of a deep CSI compressor for massive MIMO in 5G protocols and beyond.

Last Updated On: 
Mon, 06/13/2022 - 14:28

Network topologies with link parameters; some statistical data.


This dataset contains the raw data of the measurements/simulations presented in "Modulation Scheme Analysis for Low-Power Leadless Pacemaker Synchronization Based on Conductive Intracardiac Communication" by A. Ryser et al. This work analyzed the bit error rate (BER) performance of a prototype dual-chamber leadless pacemaker both in simulation and in-vitro experiments on porcine hearts.


This dataset was created using Wireshark. The dataset contains a total of 30 encrypted communication records, 3 records (.pcap) were created for each application. The records were obtained from a mobile device that was connected to the laptop using wifi technology. The laptop was connected to the Internet and contained a running instance of Wireshark to create a record. The telephone had been restarted before each record was created. After connecting to the network, the device was left without user interaction for 5 minutes.