Questions tagged [machine-learning]

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

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How to quantify privacy, when using homomorphic encryption?

How can you measure how secure or private the new variables are relative to the real (actual) variables. I want to compare homomorphic encryption and differential privacy in combination with machine ...
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Using ML to detect what classical cipher the ciphertext is encrypted with

I was considering creating an ML project where it is fed some ciphertext by any classical cipher and would return possible ciphers that encrypted the text. I would have to create a sizeable dataset ...
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Neural Network based on pseudorandom number

Recently, I read this paper NEURAL NETWORK BASED CRYPTOGRAPHY. Under the section 3.1 it said: The aim is to improve the randomness of the random numbers generated by any algorithm using an NN. In ...
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Adaptive security

I would like to know if there are any effective methods to choose a cryptographic algorithm from a pool of algorithms depending on a certain situation. Let's say we know the performances of these ...
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Extracting genome from a Ciphertext [closed]

Is it Probable to extract the ciphertext's genome and Visualizing it ? Converting this: ...
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security of different federated learning schemes

all, I am working on federated learning and here goes my question: Suppose there are two participants to do the federated learning. For some of the models (e.g. Logistic Regression models, assume one ...
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Can Big Data together with deep neural networks attack RSA by affording the vast calculation of prime multiplications in advance?

This is a spin-off from Can Big Data attack RSA by just calculating many prime multiplications in advance? [duplicate]. Intro I am somewhat new to cryptography. Repeating the basics of RSA from How ...
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Paillier scheme : Encoding floats into integers impact on computations

In Privacy Preserving Processing Over Encrypted Images, I could understand that appropriate encoding of floats into integers (required in Paillier) only incur negligible error in computations. Any ...
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How to adapt the equation of Gaussian mechanism noise based on number of executions

I'm trying to build a differentially private machine learning model. I'm using the Gaussian mechanism to calculate the required noise amount based on pre-defined privacy budget value 𝜖 The equation ...
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Selection of the noise application position in differential privacy

In DP-SGD proposed by M Abadi in 2016, noise is applied to the gradient, so every round of training needs to be applied. My questions are: Can I choose to apply noise that meets the DP requirements to ...
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2 votes
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Predicting with a machine learning model while preserving the privacy

Imagine Alice has trained a machine learning model. She wants to store her model in a blockchain so that everyone can use it; however, she wants her model to be private so that no one can steal her ...
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3 votes
1 answer
114 views

Zero knowledge proof for verifying a machine learning model

Imagine Alice has trained a machine learning model. Bob wants to verify that whether Alice actually trained the model or not, but Alice does not want to reveal her model (because the model is personal ...
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Machine Learning to improve Encryption algorithms [duplicate]

Can machine learning be used to improve encryption algorithms e.g.image encryption algorithms that use ECC ?
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Predict with a machine learning model without knowing the actual model values

Imagine Alice has trained a machine learning model. She wants other people like Bob to be able to use her model for prediction, but she doesn't want them to know the actual model. She wants the model ...
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The existing approaches based on machine learning for cryptography [closed]

i'm working on a paper about Machine learning and Deep Learning and i'm wondring about the uses of this domain in cryptography!! so what are these application of Ml that we use in cryptography and the ...
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Decrypting data on client side for use inside program

So I am developing a python program and encrypting the trained machine learning models which need to be decrypted when loading them on client side. My program will deployed on the client's machine ...
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Computing guessing entropy (average rank of the correct key) in attack using deep learning

I am looking for help with some issues that I have about the guessing entropy (GE) in side-channel attacks context. I have read some papers where GE is used as a metric to measure the attack's ...
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What machine learning accuracy is assumed to be predictable for TRNG/PUF application?

In regular machine learning (ML) applications, usually an accuracy of greater than 95% is desired. In an ideal TRNG/PUF applications, unpredictable behavior (50% accuracy with ML models) is desired. ...
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2 votes
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Applications of machine learning in classical ciphers?

Machine learning is definitely applicable in analyzing simple shift ciphers like Caesar and affine ciphers, as well as substitution ciphers like Vigenère, but is it possible for machine learning to ...
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how to measure/calculate guessing entropy for side channel attacks

I was going through the paper (https://link.springer.com/chapter/10.1007/978-3-319-66787-4_3), and I came across where authors says that accuracy alone is not enough as an evaluation metric and ...
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5 votes
5 answers
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Using AI to perform Cryptanalysis

If given a large set of examples of cyphertext and corresponding plaintext, could AI be trained to decrypt a cyphertext as the examples provided?, and if so, are there any examples online ...
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Can machine learning/AI lower the security existing cryptographic protocols similar to quantum computers? [duplicate]

Initial thinking would be not unless the protocol revealed sensitive local information that could then be analysed by an ML algorithm and applied globally. local meaning I see messages from Alice and ...
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2 votes
1 answer
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How can we compare an encrypted number with a normal number?

I am currently doing a project on privacy preserving encryption using a k-means system and the Paillier encryption algorithm (homomorphic algorithm). I have to send an image of a skin disease to the ...
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8 votes
1 answer
4k views

Deep Learning application in decryption?

If the output of an algorithm when interacting with the [encryption] protocol matches that of a simulator given some inputs, it ‘need not know’ anything more than those inputs. Can a machine learn to ...
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6 votes
1 answer
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Homomorphic Encryption for Deep Learning

I'm interested in the two following processes: Perform deep learning on homomorphic encrypted data Perform deep learning predictions with a homomorphic encrypted model on unencrypted data. By this, ...
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