IoT malware is often generated in large quantities through source code modifications and widely used in cyberattacks. For fine-grained functional analysis, it is crucial to extract and utilize relevant behavioral information from the executables of malware samples. In this study, our primary objective is to improve the clustering accuracy of IoT malware based on phylogenetic trees, and from the results, we investigate which components are useful for analyzing functional characteristics at a level more fine-grained than the family.Executable code can generally be classified into statically linked library functions and user-written code, the latter presumed to reflect attacker-specific functionality. Based on this fact, we hypothesized that meaningful functional distinctions among samples are primarily captured in the user code regions. To test this hypothesis, we constructed multiple datasets with and without user code and library functions, and evaluated clustering quality with respect to two functional label sets: disabling information and exploit information.The experimental results showed that, as hypothesized, excluding library functions and retaining only the opcodes of user code improves clustering accuracy for disabling information, whereas for exploit labels, accuracy improves even when only the library function regions are used. These results demonstrate that eliminating irrelevant information is effective for functional label classification, and that functional analysis does not necessarily rely solely on user code; rather, it was revealed that vulnerability-related information is also contained in the library parts.
We present a CKKS native homomorphic transciphering framework that converts existing LEA-128 ciphertexts into LEA-256 ciphertexts without exposing plaintext. Motivated by the post-quantum reduction in symmetric key security, our design shows that, by using homomorphic encryption, especially CKKS, it is possible to transition to post-quantum cryptography without revealing sensitive information. Furthermore, we propose a method that optimizes ARX operations by leveraging the SIMD structure of CKKS. Our approach combines: (i) bitwise packing that maps LEA’s ARX to CKKS primitive operations; (ii) a CKKS adapted Kogge–Stone adder that implements modular addition with logarithmic carry depth using masked rotations; and (iii) a low degree noise attenuation polynomial that preserves binary fixed points and suppresses near binary perturbations at a modest depth overhead. With 2^15 CKKS slots and 32 CPU threads, the pipeline that converts LEA-128 to LEA-256 completes with an amortized time of 6.61 s, and the results decrypt correctly under our parameters. Compared with TFHE style Boolean gate baselines, our circuit formulation and 1-bit encoding deliver over 3 × speedups for bootstrapped modular addition and subtraction, while XOR and rotation are substantially faster due to SIMD packing. These results indicate that CKKS based transciphering is practical for ARX ciphers like LEA and provides a confidential migration path from 128-bit to 256-bit keys without plaintext exposure in the post-quantum era.
At ACISP 2017, Naito proposed a double-block-length (DBL) hash function with the following features: (i) without the costly feed-forward operations; (ii) of rate 1/2, and every pair of blockcipher-calls is parallelizable; (iii) achieving n-bit indifferentiability security using a blockcipher with n-bit blocks and κ -bit keys. This is one of the state-of-the-art DBL hash constructions. The only shortage is the use of a finalization function by two blockcipher-calls, which is unfriendly to short messages. We consider , which is obtained by injecting Naito’s feed-forward-free compression function into the Merkle-Damgård with permutation construction (JoC 2008), and prove n - log _2 n indifferentiability for it. To our knowledge, this is the first time to achieve the three aforementioned properties of plus finalization-freeness simultaneously. We also investigate the (second) preimage security of and . When κ≥ 2n+1 and a strengthened Merkle-Damgård message padding is used, for any challenge message with at least n+2 blocks, we show an attack finding a second preimage on with the same number of blocks, using O(n 2^n) time and O( 2^n ) memory. Our idea also yields a preimage attack against with the same complexities.
LINE is the most widely used messaging application worldwide, with 196 million monthly active users as of March 2025. Given its broad adoption, ensuring the security of its communication protocol is of significant importance. However, its end-to-end encryption protocol, Letter Sealing, has not undergone comprehensive formal verification. Although Letter Sealing Version 2—introduced after vulnerabilities were identified in Version 1—is now widely deployed, its security guarantees remain insufficiently scrutinized. In this work, we formally model the one-to-one communication protocol in both Letter Sealing versions using the symbolic verification tool Tamarin-Prover and analyze key security properties, including confidentiality, authentication, and integrity. For Letter Sealing Version 1, we reproduce previously reported vulnerabilities, such as impersonation and replay attacks, and additionally conduct an exhaustive verification of a broad range of security properties. For Letter Sealing Version 2, we represent the first comprehensive formal analysis. We confirm that several vulnerabilities have been mitigated through changes in cryptographic algorithms; however, our analysis also reveals several previously unidentified weaknesses that persist in the protocol. This work provides a foundational step toward a rigorous evaluation of the security guarantees offered by LINE’s encryption mechanisms and underscores the ongoing need for formal verification in widely deployed communication systems.
ChaCha is an ARX-based stream cipher and has been widely used in practice. In this paper, we propose a new derivation rule for linear approximations of ARX-based ciphers and then apply it to ChaCha. Compared with the previous derivation rules for linear approximations, it can reduce the number of active bits when deriving linear approximations. By combining this new derivation rule with the previous derivation rules in a mixed pattern, we improve the 3.5- and 4-round linear approximations for ChaCha. The original 3.5-round linear approximation presented at EUROCRYPT 2021 has a correlation of 2^-47 , which was improved to be -2^-41 recently. This paper further improves it with a better correlation of -2^-40 . Besides, we enhance the 4-round linear approximation for ChaCha with correlation 2^ - 48 , improving the previous result (i.e., -2^-50 ) by a factor of -2^2 . The new derivation rule for linear approximations is general and can be applied to other ARX-based ciphers.
