방법 비교

	AES (Rijndael)	HMAC	선형 암호 해독
분야	암호학	암호학	암호학
계열	Machine learning	Machine learning	Machine learning
기원 연도	2001	1997	1993
창시자	Joan Daemen	Hugo Krawczyk	Mitsuru Matsui
유형	symmetric encryption algorithm	cryptographic authentication mechanism	linear approximation attack
원전	Daemen, J., & Rijmen, V. (2002). The Design of Rijndael: AES - The Advanced Encryption Standard. Springer-Verlag. ISBN: 978-3540425809	Krawczyk, H., Bellare, M., & Crechanko, R. (1997). HMAC: Keyed-Hashing for Message Authentication. RFC 2104.	Matsui, M. (1993). Linear cryptanalysis method for DES cipher. In Advances in Cryptology - EUROCRYPT 1993, LNCS 765, pp. 386-397.
별칭	Rijndael, AES encryption, FIPS 197	HMAC, keyed hash function	linear attack, linear approximation, piling-up lemma
관련	4	3	3
요약	The Advanced Encryption Standard (AES), also known as Rijndael, is a symmetric block cipher adopted as the official encryption standard by the U.S. government in 2001. It processes data in 128-bit blocks using 128, 192, or 256-bit keys and performs multiple rounds of substitution, permutation, and mixing operations. AES is the most widely used symmetric encryption algorithm today, securing everything from government communications to everyday internet traffic.	HMAC (Hash-Based Message Authentication Code) is a cryptographic algorithm for authenticating messages using a secret key and a hash function. Standardized in RFC 2104 (1997), HMAC can be combined with any cryptographic hash function (SHA-256, SHA-3, etc.) to create a message authentication code (MAC). HMAC provides both data integrity and authentication, detecting both accidental corruption and deliberate tampering, and is widely used in web security (TLS/SSL), API authentication, and network protocols.	Linear cryptanalysis is a known-plaintext attack that exploits linear approximations of a cipher's non-linear transformations to recover secret key bits. Introduced by Mitsuru Matsui in 1993, linear cryptanalysis provides practical attacks on ciphers like DES with computational complexity less than brute force. The technique analyzes statistical biases in how linear combinations of plaintext and ciphertext bits relate to key bits, enabling key recovery with reduced data requirements.