TY - CHAP
T1 - Robustness
AU - Alvim, Mário S.
AU - Chatzikokolakis, Konstantinos
AU - McIver, Annabelle
AU - Morgan, Carroll
AU - Palamidessi, Catuscia
AU - Smith, Geoffrey
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Given a channel with input X, we have now seen that g-leakage provides us with a rich variety of ways to measure the information leakage of X that the channel causes. The prior models the adversary’s prior knowledge about X; the gain function g models the operational scenario, which encompasses both the set of actions that the adversary can take and also the worth to the adversary of each such action, for each possible value of X; and the choice of multiplicative- or additive leakage allows us to measure either the relative or the absolute increase in g-vulnerability.
AB - Given a channel with input X, we have now seen that g-leakage provides us with a rich variety of ways to measure the information leakage of X that the channel causes. The prior models the adversary’s prior knowledge about X; the gain function g models the operational scenario, which encompasses both the set of actions that the adversary can take and also the worth to the adversary of each such action, for each possible value of X; and the choice of multiplicative- or additive leakage allows us to measure either the relative or the absolute increase in g-vulnerability.
UR - https://www.scopus.com/pages/publications/85091592048
U2 - 10.1007/978-3-319-96131-6_6
DO - 10.1007/978-3-319-96131-6_6
M3 - Chapter
AN - SCOPUS:85091592048
T3 - Information Security and Cryptography
SP - 101
EP - 105
BT - Information Security and Cryptography
PB - Springer Science and Business Media Deutschland GmbH
ER -