Position-Based Cryptography from Noisy Channels

2014 ◽  
pp. 300-317 ◽  
Author(s):  
Stefan Dziembowski ◽  
Maciej Zdanowicz
Keyword(s):  
Noisy Channels

Detection of Malicious Spatial-Domain Steganography over Noisy Channels Using Convolutional Neural Networks

2020 ◽  
Vol 2020 (4) ◽  
pp. 76-1-76-7
Author(s):  
Swaroop Shankar Prasad ◽  
Ofer Hadar ◽  
Ilia Polian
Keyword(s):  
State Of The Art ◽  
Visual Quality ◽  
Channel Noise ◽  
Detection Accuracy ◽  
Noisy Channel ◽  
Noisy Channels ◽  
Reliable Transmission ◽  
Reliable Detection ◽  
Natural Noise ◽  
Will Force

Image steganography can have legitimate uses, for example, augmenting an image with a watermark for copyright reasons, but can also be utilized for malicious purposes. We investigate the detection of malicious steganography using neural networkbased classification when images are transmitted through a noisy channel. Noise makes detection harder because the classifier must not only detect perturbations in the image but also decide whether they are due to the malicious steganographic modifications or due to natural noise. Our results show that reliable detection is possible even for state-of-the-art steganographic algorithms that insert stego bits not affecting an image’s visual quality. The detection accuracy is high (above 85%) if the payload, or the amount of the steganographic content in an image, exceeds a certain threshold. At the same time, noise critically affects the steganographic information being transmitted, both through desynchronization (destruction of information which bits of the image contain steganographic information) and by flipping these bits themselves. This will force the adversary to use a redundant encoding with a substantial number of error-correction bits for reliable transmission, making detection feasible even for small payloads.

scholarly journals Fundamental limitations on distillation of quantum channel resources

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bartosz Regula ◽  
Ryuji Takagi
Keyword(s):  
Lower Bounds ◽  
Quantum Channel ◽  
Quantum Communication ◽  
Fault Tolerant ◽  
State Of The Art ◽  
Quantum Systems ◽  
Noisy Channels ◽  
General Transformation ◽  
Fundamental Limitations ◽  
Strong Converse

AbstractQuantum channels underlie the dynamics of quantum systems, but in many practical settings it is the channels themselves that require processing. We establish universal limitations on the processing of both quantum states and channels, expressed in the form of no-go theorems and quantitative bounds for the manipulation of general quantum channel resources under the most general transformation protocols. Focusing on the class of distillation tasks — which can be understood either as the purification of noisy channels into unitary ones, or the extraction of state-based resources from channels — we develop fundamental restrictions on the error incurred in such transformations, and comprehensive lower bounds for the overhead of any distillation protocol. In the asymptotic setting, our results yield broadly applicable bounds for rates of distillation. We demonstrate our results through applications to fault-tolerant quantum computation, where we obtain state-of-the-art lower bounds for the overhead cost of magic state distillation, as well as to quantum communication, where we recover a number of strong converse bounds for quantum channel capacity.

Constrained VQ codebook design for noisy channels

2001 ◽  
Vol 37 (10) ◽  
pp. 662 ◽  
Author(s):  
Wen-Whei Chang ◽  
Heng-Iang Hsu
Keyword(s):  
Noisy Channels ◽  
Codebook Design

A STATISTICAL APPROACH TOWARDS SECURE LOCATION VERIFICATION IN NOISY WIRELESS CHANNELS

2014 ◽  
Vol 25 (05) ◽  
pp. 563-584 ◽  
Author(s):  
PARTHA SARATHI MANDAL ◽  
ANIL K. GHOSH
Keyword(s):  
Statistical Approach ◽  
Probability Model ◽  
Distance Estimation ◽  
Sensor Nodes ◽  
Noisy Channel ◽  
Malicious Nodes ◽  
Noisy Channels ◽  
Location Verification ◽  
Limited Precision ◽  
Very High

Location verification in wireless sensor networks (WSNs) is quite challenging in the presence of malicious sensor nodes, which are called attackers. These attackers try to break the verification protocol by reporting their incorrect locations during the verification stage. In the literature of WSNs, most of the existing methods of location verification use a set of trusted verifiers, which are vulnerable to attacks by malicious nodes. These existing methods also use some distance estimation techniques, which are not accurate in noisy channels. In this article, we adopt a statistical approach for secure location verification to overcome these limitations. Our proposed method does not rely on any trusted entities and it takes care of the limited precision in distance estimation by using a suitable probability model for the noise. The resulting verification scheme detects and filters out all malicious nodes from the network with a very high probability even when it is in a noisy channel.

scholarly journals Analyzing anonymity attacks through noisy channels

2015 ◽  
Vol 244 ◽  
pp. 76-112 ◽  
Author(s):  
Sami Zhioua
Keyword(s):  
Noisy Channels

Joint Source-Channel Coding in Dictionary Methods of Lossless Data Compression

2010 ◽  
Vol 56 (4) ◽  
pp. 351-355
Author(s):  
Marcin Rodziewicz
Keyword(s):  
Data Compression ◽  
Channel Coding ◽  
Data Stream ◽  
Noisy Channels ◽  
Error Resiliency ◽  
Joint Source Channel Coding ◽  
Lossless Data Compression ◽  
Compressed Data ◽  
Source Channel Coding

Joint Source-Channel Coding in Dictionary Methods of Lossless Data Compression Limitations on memory and resources of communications systems require powerful data compression methods. Decompression of compressed data stream is very sensitive to errors which arise during transmission over noisy channels, therefore error correction coding is also required. One of the solutions to this problem is the application of joint source and channel coding. This paper contains a description of methods of joint source-channel coding based on the popular data compression algorithms LZ'77 and LZSS. These methods are capable of introducing some error resiliency into compressed stream of data without degradation of the compression ratio. We analyze joint source and channel coding algorithms based on these compression methods and present their novel extensions. We also present some simulation results showing usefulness and achievable quality of the analyzed algorithms.

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