Security
It is a challenging work to solve the geometric attack in the field of digital watermarking. In order to solve the synchronization between the host image and the watermark, image normalization is introduced. Firstly, the geometrically invariant space of image is constructed by using image normalization, and a region of interest (ROI) is obtained from the normalized image by utilizing the invariant centroid theory. Then, the contourlet transform is performed on the ROI. Low-pass sub-band coefficients are divided into non-overlapping blocks.
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The data set downloaded from Wikimedia Download is available as a test data set related to the key-value structure.Searchable encryption schemes that need to implement keyword search can use this dataset as test data.Wikimedia Commons is a media repository of free-to-use images, sounds, videos and other media.
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Oblivion Results is a TXT dataset which contains the report files generated in the experimental phase of Oblivion's development. Knowing the SHA256 hash of a file of interest, if this file is present in our list, the relative report can be consulted.
The set is organized as follows:
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This data collection focuses on capturing user-generated content from the popular social network Reddit during the year 2023. This dataset comprises 29 user-friendly CSV files collected from Reddit, containing textual data associated with various emotions and related concepts.
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FormAI is a novel AI-generated dataset comprising 112,000 compilable and independent C programs. All the programs in the dataset were generated by GPT-3.5-turbo using dynamic zero-shot prompting technique and comprises programs with varying levels of complexity. Some programs handle complicated tasks such as network management, table games, or encryption, while others deal with simpler tasks like string manipulation. Each program is labelled based on vulnerabilities present in the code using a formal verification method based on the Efficient SMT-based Bounded Model Checker (ESBMC).
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Smart homes contain programmable electronic devices (mostly IoT) that enable home automation. People who live in smart homes benefit from interconnected devices by controlling them either remotely or manually/autonomously. However, high interconnectivity comes with an increased attack surface, making the smart home an attractive target for adversaries. NCC Group and the Global Cyber Alliance recorded over 12,000 attacks to log into smart home devices maliciously. Recent statistics show that over 200 million smart homes can be subjected to these attacks.
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Over 34,000 frames from 60 commercial-off-the-shelf ZigBee devices were collected in various scenarios including indoor/outdoor and line-of-sight/non-line-of-sight (LOS/NLOS). The ZigBee devices are hybrid, with 36 equipped with power amplifiers and the other 24 not. The ZigBee device uses the CC2530 chip, while the power amplifier is the RFX2401C chip. The signal frames in each scenario are placed in a separate folder, where all device numbers are fixed. Each frame reaches its maximum length, which includes 266 symbols.
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This dataset consists of “.csv” files of 4 different routing attacks (Blackhole Attack, Flooding Attack, DODAG Version Number Attack, and Decreased Rank Attack) targeting the RPL protocol, and these files are taken from Cooja (Contiki network simulator). It allows researchers to develop IDS for RPL-based IoT networks using Artificial Intelligence and Machine Learning methods without simulating attacks. Simulating these attacks by mimicking real-world attack scenarios is essential to developing and testing protection mechanisms against such attacks.
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