Contents
What is mutual information analysis?
Mutual Information Analysis is a generic side-channel distinguisher that. has been introduced at CHES 2008. It aims to allow successful attacks requiring min- imum assumptions and knowledge of the target device by the adversary.
What does point wise mutual information measure?
Pointwise mutual information (PMI), or point mutual information, is a measure of association used in information theory and statistics. In contrast to mutual information (MI) which builds upon PMI, it refers to single events, whereas MI refers to the average of all possible events.
Why is positive pointwise mutual information?
The Positive Pointwise Mutual Information, which works well for measuring semantic similarity in the Term- Sentence-Matrix, is used in our method to assign weights for each entry in the Term-Sentence-Matrix. The Sentence-Rank-Matrix generated from this weighted TSM, is then used to extract a summary from the document.
Why pointwise mutual information is important?
The pointwise mutual information represents a quantified measure for how much more- or less likely we are to see the two events co-occur, given their individual probabilities, and relative to the case where the two are completely independent.
How is mutual information used in signal processing?
Mutual information is also used in the area of signal processing as a measure of similarity between two signals. For example, FMI metric [17] is an image fusion performance measure that makes use of mutual information in order to measure the amount of information that the fused image contains about the source images.
Is there such a thing as mutual information?
Mutual Information is just one way among many of measuring how related two random variables are. However, it is a measure ideally suited for analyzing communication channels.
How does mutual information quantize the amount of information?
More specifically, it quantifies the ” amount of information ” (in units such as shannons ( bits ), nats or hartleys) obtained about one random variable through observing the other random variable.
How is mutual information measured in probability theory?
In probability theoryand information theory, the mutual information(MI) of two random variablesis a measure of the mutual dependencebetween the two variables. More specifically, it quantifies the “amount of information” (in unitssuch as shannons, commonly called bits) obtained about one random variable through observing the other random variable.