机械
发表于 2025-3-23 12:03:12
Ernst Hafterwell as not requiring a large number of TCP packets being captured and processed, and thus our proposed SSID algorithm is more efficient. Since the number of packet crossovers can be easily calculated, our proposed detection method is easy to use and implement. The effectiveness, correctness and eff
COMMA
发表于 2025-3-23 14:59:47
Ernst Hafterain..One result of these more general and improved methods includes a slight increase over the scalar multiplication speeds reported at PKC. Furthermore, by the straightforward removal of rules for unusual cases, some particularly concise yet efficient presentations can be given for algorithms in th
Esophagus
发表于 2025-3-23 19:06:48
arity of pairing (compatible with Tate pairing) without any branches in the program, and is as efficient as the original one. Therefore the proposed universal .. pairing is suitable for the implementation of various extension degrees . with higher security.
使声音降低
发表于 2025-3-24 01:15:46
Ernst Hafterformance on PIPO-64/128 basis than the simple ported version of RISC-V. In addition, our implementation showed 393.52% improvement over the encryption performance of the PIPO reference code, despite including the key scheduling process. As far as we know, this is the first optimal implementation of
英寸
发表于 2025-3-24 05:41:17
http://reply.papertrans.cn/87/8623/862233/862233_15.png
哄骗
发表于 2025-3-24 10:08:34
Ernst Haftercision and Recall (TaPR), which is suitable for anomaly detection evaluation in ICS. As a result of submission of test data, we were awarded 2nd place at HAICon2020. We have detected anomalies in ICS. As a follow-up work, we will do further research to identify the sensor and actuator that caused th
概观
发表于 2025-3-24 14:32:37
http://reply.papertrans.cn/87/8623/862233/862233_17.png
Patrimony
发表于 2025-3-24 16:37:01
http://reply.papertrans.cn/87/8623/862233/862233_18.png
ELUC
发表于 2025-3-24 22:53:41
ed feature vectors extracted from the opcode sequences of each method using an opcode list, we present a more thorough representation that encapsulates the complex traits of the malware samples. We employ state-of-the-art graph-based deep learning models to classify malware families, including Graph
阐释
发表于 2025-3-24 23:39:26
http://reply.papertrans.cn/87/8623/862233/862233_20.png