scholarly journals A Lightweight Modulation Classification Network Resisting White Box Gradient Attacks

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Sicheng Zhang ◽  
Yun Lin ◽  
Zhida Bao ◽  
Jiangzhi Fu
Keyword(s):  
Signal Sequence ◽  
Classification Model ◽  
Modulation Classification ◽  
Signal Recognition ◽  
Fast Calculation ◽  
Scale Reduction ◽  
Important Means ◽  
Modulation Signal ◽  
Small Model ◽  
The Internet Of Things

Improving the attack resistance of the modulation classification model is an important means to improve the security of the physical layer of the Internet of Things (IoT). In this paper, a binary modulation classification defense network (BMCDN) was proposed, which has the advantages of small model scale and strong immunity to white box gradient attacks. Specifically, an end-to-end modulation signal recognition network that directly recognizes the form of the signal sequence is constructed, and its parameters are quantized to 1 bit to obtain the advantages of low memory usage and fast calculation speed. The gradient of the quantized parameter is directly transferred to the original parameter to realize the gradient concealment and achieve the effect of effectively defending against the white box gradient attack. Experimental results show that BMCDN obtains significant immune performance against white box gradient attacks while achieving a scale reduction of 6 times.

scholarly journals Real-time observation of signal recognition particle binding to actively translating ribosomes

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Thomas R Noriega ◽  
Jin Chen ◽  
Peter Walter ◽  
Joseph D Puglisi
Keyword(s):  
Real Time ◽  
Single Molecule ◽  
Protein Translocation ◽  
Signal Sequence ◽  
Signal Recognition Particle ◽  
Initial Step ◽  
Signal Recognition ◽  
Fluorescence Measurements ◽  
Nascent Chain ◽  
Time Observation

The signal recognition particle (SRP) directs translating ribosome-nascent chain complexes (RNCs) that display a signal sequence to protein translocation channels in target membranes. All previous work on the initial step of the targeting reaction, when SRP binds to RNCs, used stalled and non-translating RNCs. This meant that an important dimension of the co-translational process remained unstudied. We apply single-molecule fluorescence measurements to observe directly and in real-time E. coli SRP binding to actively translating RNCs. We show at physiologically relevant SRP concentrations that SRP-RNC association and dissociation rates depend on nascent chain length and the exposure of a functional signal sequence outside the ribosome. Our results resolve a long-standing question: how can a limited, sub-stoichiometric pool of cellular SRP effectively distinguish RNCs displaying a signal sequence from those that are not? The answer is strikingly simple: as originally proposed, SRP only stably engages translating RNCs exposing a functional signal sequence.

scholarly journals Mechanisms of membrane protein biogenesis

2014 ◽  
Vol 70 (a1) ◽  
pp. C1161-C1161
Author(s):  
Irmgard Sinning
Keyword(s):  
Membrane Proteins ◽  
Signal Sequence ◽  
Signal Recognition Particle ◽  
Signal Recognition ◽  
Protein Biogenesis ◽  
Cargo Proteins ◽  
Target Membrane ◽  
Hydrophobic Nature ◽  
Correct Target ◽  
Srp Rna

More than 25% of the cellular proteome comprise membrane proteins that have to be inserted into the correct target membrane. Most membrane proteins are delivered to the membrane by the signal recognition particle (SRP) pathway which relies on the recognition of an N-terminal signal sequence. In contrast to this co-translational mechanism, which avoids problems due to the hydrophobic nature of the cargo proteins, tail-anchored (TA) membrane proteins utilize a post-translational mechanism for membrane insertion – the GET pathway (guided entry of tail-anchored membrane proteins). The SRP and GET pathways are both regulated by GTP and ATP binding proteins of the SIMIBI family. However, in the SRP pathway the SRP RNA plays a unique regulatory role. Recent insights into eukaryotic SRP will be discussed.

The Algorithm of Modulation Classification Based on Eigenface and Support Vector Machine in Low SNR

2014 ◽  
Vol 701-702 ◽  
pp. 442-448
Author(s):  
Xiang Ke Guo ◽  
Rong Ke Liu ◽  
Chang Yun Liu ◽  
Shao Hua Yue
Keyword(s):  
Support Vector Machine ◽  
Signal To Noise Ratio ◽  
Spectral Feature ◽  
Support Vector ◽  
Modulation Classification ◽  
Modulation Recognition ◽  
Low Snr ◽  
Feature Extract ◽  
Modulation Signal ◽  
Novel Algorithms

To improve the accuracy and reliability of modulation recognition at low signal to noise ratio (SNR) and few knowledge of signal parameter, the novel method based on the cyclic spectral feature and support vector machine(SVM) is presented. In the process of novel algorithms, the cyclic spectral analysis is used to realize the feature extract of the modulated signals, and the Eigenface method is used to reduce the amount of spectral coherence feature. Then, a new scheme of classification based on support vector machine is presented to classify the modulation signal. The experiment shows that the modulation classification accuracy of presented method is significantly improved at low SNR environment.

scholarly journals GTPase domain of the 54-kD subunit of the mammalian signal recognition particle is required for protein translocation but not for signal sequence binding.

1993 ◽  
Vol 120 (5) ◽  
pp. 1113-1121 ◽  
Author(s):  
D Zopf ◽  
H D Bernstein ◽  
P Walter
Keyword(s):  
Protein Translocation ◽  
Signal Sequence ◽  
Signal Recognition Particle ◽  
Intact Protein ◽  
Signal Recognition ◽  
Signal Sequences ◽  
Amino Terminal ◽  
Terminal Domain ◽  
Sequence Recognition ◽  
Amino Terminal Domain

The 54-kD subunit of the signal recognition particle (SRP54) binds to signal sequences of nascent secretory and transmembrane proteins. SRP54 consists of two separable domains, a 33-kD amino-terminal domain that contains a GTP-binding site (SRP54G) and a 22-kD carboxy-terminal domain (SRP54M) containing binding sites for both the signal sequence and SRP RNA. To examine the function of the two domains in more detail, we have purified SRP54M and used it to assemble a partial SRP that lacks the amino-terminal domain of SRP54 [SRP(-54G)]. This particle recognized signal sequences in two independent assays, albeit less efficiently than intact SRP. Analysis of the signal sequence binding activity of free SRP54 and SRP54M supports the conclusion that SRP54M binds signal sequences with lower affinity than the intact protein. In contrast, when SRP(-54G) was assayed for its ability to promote the translocation of preprolactin across microsomal membranes, it was completely inactive, apparently because it was unable to interact normally with the SRP receptor. These results imply that SRP54G plays an essential role in SRP-mediated targeting of nascent chain-ribosome complexes to the ER membrane and also influences signal sequence recognition, possibly by promoting a tighter association between signal sequences and SRP54M.

Structural basis of signal-sequence recognition by the signal recognition particle

2011 ◽  
Vol 18 (3) ◽  
pp. 389-391 ◽  
Author(s):  
Tobias Hainzl ◽  
Shenghua Huang ◽  
Gitte Meriläinen ◽  
Kristoffer Brännström ◽  
A Elisabeth Sauer-Eriksson
Keyword(s):  
Signal Sequence ◽  
Signal Recognition Particle ◽  
Structural Basis ◽  
Signal Recognition ◽  
Sequence Recognition

scholarly journals Signal recognition particle mediates a transient elongation arrest of preprolactin in reticulocyte lysate.

1989 ◽  
Vol 109 (6) ◽  
pp. 2617-2622 ◽  
Author(s):  
S L Wolin ◽  
P Walter
Keyword(s):  
Wheat Germ ◽  
Signal Sequence ◽  
Signal Recognition Particle ◽  
Secretory Proteins ◽  
Signal Recognition ◽  
Translation Arrest ◽  
Microsomal Membranes ◽  
Reticulocyte Lysate ◽  
Reticulocyte Lysates ◽  
Ribosome Pausing

Signal recognition particle (SRP) is a ribonucleoprotein that functions in the targeting of ribosomes synthesizing presecretory proteins to the ER. SRP binds to the signal sequence as it emerges from the ribosome, and in wheat germ extracts, arrests further elongation. The translation arrest is released when SRP interacts with its receptor on the ER membrane. We show that the delay of elongation mediated by SRP is not unique to wheat germ translation extracts. Addition of mammalian SRP to reticulocyte lysates resulted in a delay of preprolactin synthesis due to increased ribosome pausing at specific sites on preprolactin mRNA. Addition of canine pancreatic microsomal membranes to reticulocyte lysates resulted in an acceleration of preprolactin synthesis, suggesting that the endogenous SRP present in the reticulocyte lysate also delays synthesis of secretory proteins.

scholarly journals The DsbA Signal Sequence Directs Efficient, Cotranslational Export of Passenger Proteins to the Escherichia coli Periplasm via the Signal Recognition Particle Pathway

2003 ◽  
Vol 185 (19) ◽  
pp. 5706-5713 ◽  
Author(s):  
Clark F. Schierle ◽  
Mehmet Berkmen ◽  
Damon Huber ◽  
Carol Kumamoto ◽  
Dana Boyd ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Gene Fusion ◽  
Signal Sequence ◽  
Signal Recognition Particle ◽  
Signal Recognition ◽  
Sensitive Assay ◽  
Thioredoxin 1 ◽  
Passenger Proteins ◽  
Native Signal Sequence ◽  
Slight Inhibition

ABSTRACT The Escherichia coli cytoplasmic protein thioredoxin 1 can be efficiently exported to the periplasmic space by the signal sequence of the DsbA protein (DsbAss) but not by the signal sequence of alkaline phosphatase (PhoA) or maltose binding protein (MBP). Using mutations of the signal recognition particle (SRP) pathway, we found that DsbAss directs thioredoxin 1 to the SRP export pathway. When DsbAss is fused to MBP, MBP also is directed to the SRP pathway. We show directly that the DsbAss-promoted export of MBP is largely cotranslational, in contrast to the mode of MBP export when the native signal sequence is utilized. However, both the export of thioredoxin 1 by DsbAss and the export of DsbA itself are quite sensitive to even the slight inhibition of SecA. These results suggest that SecA may be essential for both the slow posttranslational pathway and the SRP-dependent cotranslational pathway. Finally, probably because of its rapid folding in the cytoplasm, thioredoxin provides, along with gene fusion approaches, a sensitive assay system for signal sequences that utilize the SRP pathway.

IoT with Cloud Based End to End Secured Disease Diagnosis Model using Light Weight Cryptography and Gradient Boosting Tree

2020 ◽  
Vol 13 ◽  
Author(s):  
K. Shankar
Keyword(s):  
Internet Of Things ◽  
Disease Diagnosis ◽  
Classification Model ◽  
Gradient Boosting ◽  
The Internet ◽  
Pima Indians ◽  
Healthcare Applications ◽  
Diagnosis Model ◽  
Consistent Performance ◽  
The Internet Of Things

Background: With the evolution of the Internet of Things (IoT) technology and connected devices employed in the medicinal domain, the different characteristics of the online healthcare applications become advantageous. Aim: The objective of this paper is to present an IoT and cloud-based secured disease diagnosis model. At present, various e-healthcare applications with the use of the Internet of Things (IoT) offers diverse dimensions and services online. Method: In this paper, an efficient IoT and cloud-based secured classification model are proposed for disease diagnosis. It is used to avail efficient and secured services to the people globally over online healthcare applications. The presented model includes an effective gradient boosting tree (GBT) based data classification and lightweight cryptographic technique named rectangle. The presented GBT–R model offers a better diagnosis in a secure way. Results: It is validated using the Pima Indians diabetes data, and extensive simulation takes place to verify the consistent performance of the employed GBT-R model. Conclusion: The experimental outcome strongly suggested that the presented model shows maximum performance with an accuracy of 94.92.

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