The Experts below are selected from a list of 33 Experts worldwide ranked by ideXlab platform

Frank Ebbers - One of the best experts on this subject based on the ideXlab platform.

  • a large scale analysis of iot Firmware Version distribution in the wild
    arxiv:eess.SY, 2020
    Co-Authors: Frank Ebbers
    Abstract:

    This paper examines the up-to-dateness of installed Firmware Versions of IoT devices accessible via public internet. It analyzes datasets of 1.06m devices collected from the IoT search engine Censys and maps the results against the latest Firmware Version each manufacturer offers. By applying the SEMMA data mining process, a fully scalable and adaptive approach is developed. This approach relies on three data artifacts: raw data from Censys, a mapping table with Firmware Versions and a keyword search list. The preliminary results confirm the heterogeneity of connected IoT devices. They show that manufacturer, device type and country influence the up-to-dateness of Firmware. The results suggest users as a "weak link" as they do not update the Firmware of their devices in a timely manner. However, the heterogeneity leads to results not showing a high reliability, yet.

Ben Jones - One of the best experts on this subject based on the ideXlab platform.

  • validity of real time data generated by a wearable microtechnology device
    Journal of Strength and Conditioning Research, 2017
    Co-Authors: Dan Weaving, Sarah Whitehead, Kevin Till, Ben Jones
    Abstract:

    The purpose of this study was to investigate the validity of global positioning system (GPS) and micro-electrical-mechanical-system (MEMS) data generated in real time through a dedicated receiver. Postsession data acted as the criterion as it is used to plan the volume and intensity of future training and is downloaded directly from the device. Twenty-five professional rugby league players completed 2 training sessions wearing an MEMS device (Catapult S5, Firmware Version: 5.27). During sessions, real-time data were collected through the manufacturer receiver and dedicated software (Openfield v1.14), which was positioned outdoors at the same location for every session. The GPS variables included total-, low- (0–3 m·s-1), moderate- (3.1–5 m·s-1), high- (5.1–7 m·s-1), and very high-speed (>7.1 m·s-1) distances. Micro-electrical-mechanical-system data included total session PlayerLoad. When compared to postsession data, mean bias for total-, low-, moderate-, high-, and very high-speed distances were all trivial, with the typical error of the estimate (TEE) small, small, trivial, trivial and small, respectively. Pearson correlation coefficients for total-, low-, moderate-, high- and very-high-speed distances were nearly perfect, nearly perfect, perfect, perfect, and nearly perfect, respectively. For PlayerLoad, mean bias was trivial, whereas TEE was moderate and correlation nearly perfect. Practitioners should be confident that when interpreting real-time speed-derived metrics, the data generated in real-time are comparable with those downloaded directly from the device postsession. However, practitioners should refrain from interpreting accelerometer-derived data (i.e., PlayerLoad) or acknowledge the moderate error associated with this real-time measure.

Yuanfa Ji - One of the best experts on this subject based on the ideXlab platform.

  • analysis of igs data based on military action prediction
    IOP Conference Series: Materials Science and Engineering, 2019
    Co-Authors: Qiang Fu, Wentao Fu, Yuanfa Ji
    Abstract:

    In order to verify that the analysis of satellite navigation signal observation data can be used as a means of predicting military operations, this paper combines the recent Iranian shooting down of UAV event, using RTKLIB software to analyze the parameter of visible satellite numbers, SNR(signal-to-noise ratio), and accuracy factor, multipath error, positioning accuracy and other indicators in order to avoid errors in the analysis results of a single type of receiver data analysis, further IGS in the vicinity of Iran and around the world according to the type of receiver, antenna type, and Firmware Version used. Observe the data for analysis. The analysis shows that the signal power of the GPS L2 frequency is enhanced in the United States from 15:00 on June 20, 2019 to 9:00 on June 21, 2019. The enhancement range is global. The analysis system of this paper can as an effective means of accurately predicting and judging military operations.

Lüders Stefan - One of the best experts on this subject based on the ideXlab platform.

  • Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk
    'MDPI AG', 2019
    Co-Authors: Agarwal Sharad, Oser Pascal, Lüders Stefan
    Abstract:

    The introduction of the Internet of Things (IoT), i.e., the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like closed circuit television (CCTV) cameras, internet protocol (IP) phones, and oscilloscopes, is overwhelming for end users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the Firmware Version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world

Jong-hyouk Lee - One of the best experts on this subject based on the ideXlab platform.

  • Blockchain-based secure Firmware update for embedded devices in an Internet of Things environment
    Journal of Supercomputing, 2017
    Co-Authors: Boohyung Lee, Jong-hyouk Lee
    Abstract:

    Embedded devices are going to be used extremely in Internet of Things (IoT) environments. The small and tiny IoT devices will operate and communicate each other without involvement of users, while their operations must be correct and protected against various attacks. In this paper, we focus on a secure Firmware update issue, which is a fundamental security challenge for the embedded devices in an IoT environment. A new Firmware update scheme that utilizes a blockchain technology is proposed to securely check a Firmware Version, validate the correctness of Firmware, and download the latest Firmware for the embedded devices. In the proposed scheme, an embedded device requests its Firmware update to nodes in a blockchain network and gets a response to determine whether its Firmware is up-to-date or not. If not latest, the embedded device downloads the latest Firmware from a peer-to-peer Firmware sharing network of the nodes. Even in the case that the Version of the Firmware is up-to-date, its integrity, i.e., correctness of Firmware, is checked. The proposed scheme guarantees that the embedded device's Firmware is up-to-date while not tampered. Attacks targeting known vulnerabilities on Firmware of embedded devices are thus mitigated.