@conference {633638,
	title = {Unifying computational entropies via Kullback-Leibler divergence},
	booktitle = {Advances in Cryptology: CRYPTO 2019, A. Boldyreva and D. Micciancio, (Eds)},
	volume = {11693},
	number = {1902.11202 [cs.CR]},
	year = {2019},
	pages = {831-858},
	publisher = {Springer Verlag, Lecture Notes in Computer Science},
	organization = {Springer Verlag, Lecture Notes in Computer Science},
	abstract = {
	Version History:\&nbsp;



	arXiv, first posted Feb 2019, most recently updated Aug 2019:\&nbsp;https://arxiv.org/abs/1902.11202



	Publisher{\textquoteright}s Version:\&nbsp;https://link.springer.com/chapter/10.1007\%2F978-3-030-26951-7_28



	\&nbsp;



	We introduce\&nbsp;hardness in relative entropy, a new notion of hardness for search problems which on the one hand is satisfied by all one-way functions and on the other hand implies both\&nbsp;next-block pseudoentropy\&nbsp;and\&nbsp;inaccessible entropy, two forms of computational entropy used in recent constructions of pseudorandom generators and statistically hiding commitment schemes, respectively. Thus, hardness in relative entropy unifies the latter two notions of computational entropy and sheds light on the apparent {\textquotedblleft}duality{\textquotedblright} between them. Additionally, it yields a more modular and illuminating proof that one-way functions imply next-block inaccessible entropy, similar in structure to the proof that one-way functions imply next-block pseudoentropy (Vadhan and Zheng, STOC {\textquoteleft}12).

},
	url = {https://link.springer.com/chapter/10.1007\%2F978-3-030-26951-7_28},
	author = {Rohit Agrawal and Yi-Hsiu Chen and Thibaut Horel and Salil Vadhan}
}
