A lossless covert communication method was proposed.Secret information was hidden in some imperceptible parts of host multimedia information and transmitted in open channels.Host data could be lossless restored when secret information was extracted from receiving host data which hidden secret information.The improved integer transform and new type judgement conditions were given.The algorithm has lower time complexity compared with Alattar's algorithm.The method was simulated by computers which got expectant results.Finally,the algorithm was applied to covert communication of speech signal hidden secret Chinese characters.Speech signal was transmitted in local area networks and host data could be lossless restored after embedded Chinese characters were extracted.
Pattern lock is a general technique used to realize identity authentication and access authorization on mobile terminal devices such as Android platform devices, but it is vulnerable to the attack proposed by recent researches that exploit information leaked by users while drawing patterns. However, the existing attacks on pattern lock are environmentally sensitive, and rely heavily on manual work, which constrains the practicability of these attack approaches. To attain a more practical attack, this paper designs the PatternMonitor, a whole pipeline with a much higher level of automation system againsts pattern lock, which extracts the guessed candidate patterns from a video containing pattern drawing: instead of manually cutting the target video and setting thresholds, it first employs recognition models to locate the target phone and keypoints of pattern drawing hand, which enables the gesture can be recognized even when the fingertips are shaded. Then, we extract the frames from the video where the drawing starts and ends. These pre-processed frames are inputs of target tracking model to generate trajectories, and further transformed into possible candidate patterns by performing our designed algorithm. To the best of our knowledge, our work is the first attack system to generate candidate patterns by only relying on hand movement instead of accurate fingertips capture. The experimental results demonstrates that our work is as accurate as previous work, which gives more than 90\% success rate within 20 attempts.
Rainfall predicting is closely related to people's lives, and improving the accuracy of rainfall prediction is of great importance for people's life and scientific researches. In this paper we attempt to use several machine learning algorithms to analyse and predict rainfall from over 140,000 data recorded at 49 weather stations in Australia. The specific research in this paper is as follows.(1) Explain the limitations of using traditional empirical/physical statistical methods in rainfall predicting through reviewing, and explain the advantages and remaining limitations of current machine learning algorithms applied to rainfall predicting over traditional methods.(2) Different methods are applied to pre-process the data set for both typed and continuous variables to ensure the integrity of the information and to avoid the loss of excessive information in the data.(3)The K-nearest neighbour algorithm, random forest algorithm and support vector machine algorithm are used to model the data for prediction. By comparing the prediction results of each model, summarize the advantages and disadvantages of each model.The prediction results show that the prediction accuracy of the above three algorithms are 82.4464%, 85.6416% and 81.3915% respectively, and the F1-score values are 52.2388%, 61.8736% and 65.1689% respectively. Results of each algorithm are similar in accuracy, and all shows good performance in both accuracy and F1-score.
To reach the demands of the real-time covert communication, the hardware implementation of a new kind of the high efficient information hiding algorithm is proposed. The proposed scheme can embed [log_2(n+1)] bits of the changed covert data under the condition of one bit in the coverwords of n bit. The embedding algorithm successfully applies to information hiding in speech. It is pointed out that the hardware solution based on two levels encryption, guarantees a very high level of security. The speed of the hardware can reach 85.7 MHz and the hardware 530 Mb/s of data by using 8 channel parallel processing. The design can generally reach the demands of the high speed and real-time covert communication.
Turbo-code has been applied in many fields except for the field of secret communication since its appearance. This paper presents a method on designing soft encrypting wireless channel based on turbo-code. The method utilizes existing wireless transmitting channel to realize secret communication based on turbo-code en-decoders. This paper also presents the encrypting method, which has the compositive elements of turbo-code en-decoders as secret key to realize encryption. The structures of encrypting system and decrypting system and the idea of encryption are also discussed in the paper. This paper simulates on the method with audio and image signal to check the effect of encryption and the validity of the method according to the designed program. This paper shows that the encrypting method can be extended into the design of channel codecs for wireless data transmission.
Nowadays, the cell phone users are increasing very rapid, but the wireless resource is limited. In this paper, we present a new approach of designing turbo en-decoders in which interleaver maps are orthogonal and the turbo en-decoders can be used to increase the capacity of CDMA systems. The orthogonal interleavers are selected by computer. In this paper, we simulate the performance of turbo en-decoders with orthogonal interleavers to check the validity of our approach.
The increasing complexity of computer systems necessitates innovative approaches to fault and error management, going beyond traditional manual log analysis. While existing solutions using large language models (LLMs) show promise, they are limited by a gap between natural and domain-specific languages, which restricts their effectiveness in real-world applications. Our approach addresses these limitations by integrating interpretable domain knowledge into open-source LLMs through continual pre-training (CPT), enhancing performance on log tasks while retaining natural language processing capabilities. We created a comprehensive dataset, NLPLog, with over 250,000 question-answer pairs to facilitate this integration. Our model, SuperLog, trained with this dataset, achieves the best performance across four log analysis tasks, surpassing the second-best model by an average of 12.01%. Our contributions include a novel CPT paradigm that significantly improves model performance, the development of SuperLog with state-of-the-art results, and the release of a large-scale dataset to support further research in this domain.
Endoplasmic reticulum-associated degradation (ERAD) maintains protein homeostasis by retrieving misfolded proteins from the endoplasmic reticulum (ER) lumen into the cytosol for degradation. The retrotranslocation of misfolded proteins across the ER membrane is an energy-consuming process, with the detailed transportation mechanism still needing clarification. We determined the cryo-EM structures of the hetero-decameric complex formed by the Derlin-1 tetramer and the p97 hexamer. It showed an intriguing asymmetric complex and a putative coordinated squeezing movement in Derlin-1 and p97 parts. With the conformational changes of p97 induced by its ATP hydrolysis activities, the Derlin-1 channel could be torn into a "U" shape with a large opening to the lipidic environment, thereby forming an entry for the substrates in the ER membrane. The EM analysis showed that p97 formed a functional protein complex with Derlin-1, revealing the coupling mechanism between the ERAD retrotranslocation and the ATP hydrolysis activities.
Endoplasmic-reticulum-associated protein degradation
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