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Distributed Secure Fusion Estimation With lossless data compression Against Stochastic Event-Based Attacks in Power Systems

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2025年

作者： Song, Yunbo Zhao, Jianrong Jiao, Ticao Shandong Univ Technol Sch Elect & Elect Engn Zibo 255000 Peoples R China

This paper investigates the issue of distributed secure fusion estimation in power systems under stochastic event-based (SEB) attacks. A lossless data compression method utilizing full rank decomposition transform is proposed to reduce redundant sensor data, thereby alleviating network transmission load. To further save communication resources and prolong network lifetimes, sensors use a stochastic event-triggered mechanism (SETM) to transmit compressed data to local estimators. However, SETM can be exploited by SEB attackers. We first derive local estimator iterations using Bayesian inference in both normal and attack scenarios. Moreover, the accuracy of fusion estimates can be guaranteed through the codesign of information compensation and an indexed transmission strategy that counteracts SEB attacks. Finally, this paper provides an upper bound for fusing error covariance under a diagonal matrix weighted fusion scheme, effectively balancing fusion estimation performance and resource demands. All theoretical results have been illustrated by the 5-Generator and 8-Line power system.

关键词： Estimation Power systems Event detection data compression Propagation losses Power measurement Optimization Generators data communication Accuracy distributed secure fusion lossless data compression stochastic event-based attacks

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lossless data compression for Communication Systems Based on Optical Frequency Discriminator

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IEEE ACCESS 2019年 7卷 19324-19331页

作者： Shan, Guangjun East China Univ Technol Sch Informat Engn Nanchang 330013 Jiangxi Peoples R China Huazhong Univ Sci & Technol Sch Opt & Elect Informat Wuhan 430074 Hubei Peoples R China

We propose a novel lossless data compression scheme for a high-speed communication system. Previous works have usually addressed the data compression issue within an identical plane by pure mathematical processing. Here, we convert the binary information into a novel sparse expression form in which the information is divided into two parts: time sequence information and difference value information, which are sent to the destination by two distinct means of transmission. Furthermore, by a deliberately designed symbol called the semantic wavelength, we can select a better compression scheme among candidates. It is expected that our scheme can reach 13.8% data compression ratio.

关键词： lossless data compression compressive sensing Huffman coding semantic wavelength optical frequency Discriminator

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lossless data compression: A particle dynamics model

Lossless data compression: A particle dynamics model

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3rd International Conference on Service Systems and Service Management

作者： Shuai, Diamun Shuai, Qing Dong, Yumin East China Univ Sci & Technol Shanghai 200237 Peoples R China Huazhong Univ Sci & Technol Huazhong Peoples R China Qingdao Technol Univ Qingdao Peoples R China

ISBN: (纸本)1424404509

This paper presents a new generalized particle model (GPM) to generate the prediction coding for lossless data compression We discuss the GPM-based parallel algorithm, its properties and realization scheme. The proposed GPM approach has advantages in terms of parallelism, scalability and easy hardware implementation over other sequential lossless compression methods.

关键词： prediction coding lossless data compression particle model distributed parallel algorithm

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lossless data compression methods based on neural network

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International Conference on Communication Technology

作者： Yang, GW Li, ZX Tu, XY Qingdao Univ Teachers Coll Ctr Comp Qingdao Peoples R China

ISBN: (纸本)7563506861

No lossless data compression method based on neural network is found before. A lossless compression method based on BP network for the long character-string of 0 and 1 is given by establishing specific mapping Y and specific integer function and with the non-linear approximation capability of concrete three-layer BP network in this paper, and the compression & decompression algorithms of the lossless compression method are provided. Experiments show that the compression ratio of the lossless compression method is usually around 16/11 and the method can effectively compress the data which have been compressed by Huffman coding, arithmetric coding or dictionary coding.

关键词： data compression lossless data compression neural network BP algorithm

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lossless data compression studies for the geostationary imaging Fourier transform spectrometer (GIFTS) with the bias-adjusted reordering preprocessing

Lossless data compression studies for the geostationary imag...

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Conference on Satellite data compression, Communications, and Archiving III

作者： Huang, Bormin Wei, Shih-Chieh Huang, Allen H. -L. Smuga-Otto, Maciek Knuteson, Robert Revercomb, Henry E. Smith, William L., Sr. Univ Wisconsin Ctr Space Sci & Engn Madison WI 53706 USA

ISBN: (纸本)9780819468314

The NASA Geostationary Imaging Fourier Transform Spectrometer (GIFTS) represents a revolutionary step in remote sensing of Earth's atmosphere that will demonstrate the technology and measurement concepts for future NOAA geostationary operational environmental satellites (GOES). GIFTS consists of a 128 x 128 large focal plane array (LFPA) imaging FTS with the spectral coverage from 685 to 1130 cm(-1) and 1650 to 2250 cm(-1). GIFTS was selected for flight demonstration on NASA's New Millennium Program (NMP) Earth Observing 3 (EO-3) Satellite Mission. GIFTS provides full disk global coverage obtained within an hour at moderate spectral resolutions (e.g. 1.2 cm(-1)) as well as regional sounding of atmospheric temperature and absorbing gas profiles at high spectral resolution (e.g. 0.6 cm(-1)). Given the unprecedented data volume produced by GIFTS, lossless data compression is critical for the overall success of the GIFTS experiment where the data is to be disseminated to the user community in real-time and archived for scientific studies and climate assessment. In this paper we will study lossless compression of GIFTS data that has been collected as part of the calibration or Ground Based Tests that were conducted in 2006. Standard compression methods such as JPEG-2000, JPEG-LS, and CCSDS IDC 9/7M & 5/3 are investigated for compression benchmarks to be used for future comparison with more effective custom-made compression methods. Our bias-adjusted reordering (BAR) preprocessing scheme is also studied to significantly improve the compression gains of JPEG-2000, JPEG-LS, and CCSDS IDC.

关键词： Geostationary Imaging Fourier Transform Spectrometer (GIFTS) bias-adjusted reordering (BAR) preprocessing lossless data compression JPEG-2000 JPEG-LS CCSDS IDC

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lossless data compression for Wireless Sensor Networks Based on Modified Bit-level RLE

Lossless Data Compression for Wireless Sensor Networks Based...

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8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM)

作者： Long, Shengchun Xiang, Pengyuan Zhejiang Univ Technol Coll Comp Sci & Technol Hangzhou Zhejiang Peoples R China Zhejiang Univ Technol Coll Informat Engn Hangzhou Peoples R China

ISBN: (纸本)9781612846835;9781612846828

Energy in wireless sensor networks is one of the most important resources, most of the energy is consumed in communication. The wireless transmission of a single bit requires over thousand times energy more than a single 32-bit computation, so data compression provides a viable approach towards the preserved energy by reducing packet size. In this article, a new simple and effective lossless data compression which suited to latency tolerant transmission in environmental monitoring WSNs is proposed. The algorithm realizes data transformation and rearrange of bits at first, then RLE is used to compress the rearranged bit stream, finally Huffman coding is used to record the run-length. At last, the proposed algorithm is evaluated and compared with other algorithms. The results show that it is remarkable in reducing storage space and increasing the compression ratio.

关键词： lossless data compression Run-Length Encoding (RLE) Huffman Coding wireless sensor networks (WSNs)

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lossless data compression Algorithm for Satellite Packet Telemetry data

Lossless Data Compression Algorithm for Satellite Packet Tel...

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International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC)

作者： Li Guojun Shi Jian Zhang Running DFH SATELLITE Co LTD Beijing Peoples R China

ISBN: (纸本)9781479925650

A brand-new satellite packet telemetry data compression algorithm is proposed by this paper, which utilizes the slowly-changing characteristic of satellite telemetry data. Unchanged bytes are removed from the original data and the other bytes are reorganized with position. If unchanged bytes are outnumbered by the changed ones in one packet, the whole packet data remains uncompressed. The compression algorithm is lossless. Bit error scatter is restricted within two bytes. Tests revealed that the average compression ratio of the algorithm is about 5. The algorithm can be used in satellite and spacecraft telemetry data process.

关键词： Satellite telemetry Space Packet protocol lossless data compression

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lossless data compression Techniques and Their Performance

Lossless Data Compression Techniques and Their Performance

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IEEE International Conference on Computing, Communication and Automation (ICCCA)

作者： Sharma, Komal Gupta, Kunal Amity Univ Dept Comp Sci Noida Uttar Pradesh India

ISBN: (纸本)9781509064717

This paper provides the study of various lossless data compression techniques and compares their performance and efficiency using time and space complexity. data compression is itself a huge field in a computer science and it is used in reducing the size of data by removing the redundant characters or encoding the bits in data. We have used only lossless data compression techniques for compressing various media format files like text, doc, bmp, png and way. Huffman coding which generates variable length codes for each symbol. LZW is a dictionary based technique and Shannon-Fano coding is used to generate binary code based on the frequency of each symbol. So we calculated the mean compression ratio, compression factor and compression time for various media files and result analysis of above data compression techniques will help to select the most appropriate method of compressing of any given file format in real world.

关键词： lossless data compression Huffman Algorithm Lempel-Ziv Coding Shannon-fano coding

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lossless data compression via Substring Enumeration for k-th Order Markov Sources with a Finite Alphabet

Lossless Data Compression via Substring Enumeration for k-th...

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38th Symposium on Information Theory and its Applications (SITA)

作者： Iwata, Ken-ichi Arimura, Mitsuharu Univ Fukui Dept Informat Sci Grad Sch Engn Fukui 9108507 Japan Shonan Inst Technol Dept Appl Comp Sci Fujisawa Kanagawa 2518511 Japan

A generalization of compression via substringe numeration (CSE) for k-th order Markov sources with a finite alphabet is proposed, and an upper bound of the code word length of the proposed method is presented. We analyze the worst case maximum redundancy of CSE for k-th order Markov sources with a finite alphabet. The compression ratio of the proposed method asymptotically converges to the optimal one fork-th order Markov sources with a finite alphabet if the length n of a source string tends to infinity.

关键词： lossless data compression universal source coding data compression via substring enumeration k-th order Markov sources maximum redundancy

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Efficient field-programmable gate array implementation of CCSDS 121.0-B-2 lossless data compression algorithm for image compression

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JOURNAL OF APPLIED REMOTE SENSING 2015年第1期9卷 097499-1-097499-15页

作者： Kranitis, Nektarios Sideris, Ioannis Tsigkanos, Antonios Theodorou, Georgios Paschalis, Antonios Vitulli, Raffaele Univ Athens Dept Informat & Telecommun Digital Syst & Comp Architecture Lab Athens 15784 Greece European Space Agcy NL-2201 AZ Noordwijk Netherlands

The Consultative Committee for Space data Systems (CCSDS) 121.0-B-2 lossless data compression standard defines a lossless adaptive source coding algorithm which is applicable to a wide range of imaging and nonimaging data. We introduce a field-programmable gate array (FPGA) implementation of CCSDS 121.0-B-2 as an intellectual property (IP) core with the following features: (a) it is enhanced with a two-dimensional (2-D) second-order predictor making it more suitable for image compression, (b) it is enhanced with near-lossless compression functionality, (c) its parallel, pipelined architecture provides high data-rate performance with a maximum achievable throughput of 205 Msamples/s (3.2 Gbps at 16 bit) when targeting the Xilinx Virtex-5QV FPGA, and (d) it requires very low FPGA resources. When mission requirements impose lossless image compression, the CCSDS 121.0-B-2 IP core provides a very low implementation cost solution. According to European Space Agency PROBA-3 Bridging Phase, the CCSDS 121.0-B-2 IP core will be implemented in a Microsemi RTAX2000 FPGA, hosted in the data processing unit of the Coronagraph Control Box, of the Association of Spacecraft for Polarimetric and Imaging Investigation of the Corona of the Sun Coronagraph System Payload. To the best of our knowledge, it is the fastest FPGA implementation of CCSDS 121.0-B-2 to date, also including a 2-D second-order predictor making it more suitable for image compression. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： lossless data compression image compression Consultative Committee for Space data Systems on-board payload data processing field-programmable gate array

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