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The radiation mechanism of fast radio bursts (FRBs) has been extensively studied but still remains elusive. Coherent radiation is identified as a crucial component in the FRB mechanism, with charged bunches also playing a significant role under specific circumstances. In the present research, we propose a phenomenological model that draws upon the coherent curvature radiation framework and the magnetized neutron star, taking into account the kinetic energy losses of outflow particles due to inverse Compton scattering (ICS) induced by soft photons within the magnetosphere. By integrating the ICS deceleration mechanism for particles, we hypothesize a potential compression effect on the particle number density within a magnetic tube/family, which could facilitate achieving the necessary size for coherent radiation in the radial direction. This mechanism might potentially enable the dynamic formation of bunches capable of emitting coherent curvature radiation along the curved magnetic field. Moreover, we examine the formation of bunches from an energy perspective. Our discussion suggests that within the given parameter space the formation of bunches is feasible. Finally, we apply this model to FRB 20190520B, one of the most active repeating FRBs discovered and monitored by FAST. Several observed phenomena are explained, including basic characteristics, frequency downward drifting, and bright spots within certain dynamic spectral ranges., Comment: 16 pages, 9 figures, and 1 table. Accepted for publication in ApJ

In this paper, we focus on multiple sampling problems for the estimation of the fractional Brownian motion when the maximum number of samples is limited, extending existing results in the literature in a non-Markovian framework. Two classes of sampling schemes are proposed: a deterministic scheme and a level-triggered scheme. For the deterministic sampling scheme, the sampling times are selected beforehand and do not depend on the process trajectory. For the level-triggered sampling scheme, the sampling times are the times when the process crosses predetermined thresholds. The sampling times are selected sequentially in time and depend on the process trajectory. For each of the schemes, we derive the optimal sampling times by minimizing the aggregate squared error distortion. We then show that the optimal sampling strategies heavily depend on the dependence structure of the process.

The evolutions of a neutron star's rotation and magnetic field (B-field) have remained unsolved puzzles for over half a century. We ascribe the rotational braking torques of pulsar to both components, the standard magnetic dipole radiation (MDR) and particle wind flow ( MDR + Wind, hereafter named MDRW), which we apply to the Crab pulsar (B0531 + 21), the only source with a known age and long-term continuous monitoring by radio telescope. Based on the above presumed simple spin-down torques, we obtain the exact analytic solution on the rotation evolution of the Crab pulsar, together with the related outcomes as described below: (1) unlike the constant characteristic B-field suggested by the MDR model, this value for the Crab pulsar increases by a hundred times in 50~kyr while its real B-field has no change; (2) the rotational braking index evolves from $\sim$3 to 1 in the long-term, however, it drops from 2.51 to 2.50 in $\sim$45 years at the present stage, while the particle flow contributes approximately 25% of the total rotational energy loss rate; (3) strikingly, the characteristic age has the maximum limit of $\sim$10 kyr, meaning that it is not always a good indicator of real age. Furthermore, we discussed the evolutionary path of the Crab pulsar from the MDR to the wind domination by comparing it with the possible wind braking candidate pulsar PSR J1734-3333., Comment: 21pages, 3 figures, 2 tables, and 5 appendices, published in Universe

Fast radio bursts (FRBs) are extremely strong radio flares lasting several micro- to milliseconds and come from unidentified objects at cosmological distances, most of which are only seen once. Based on recently published data in the CHIME/FRB Catalog 1 in the frequency bands 400-800 MHz, we analyze 125 apparently singular FRBs with low dispersion measure (DM) and find that the distribution of their luminosity follows a lognormal form according to statistical tests. In our luminosity measurement, the FRB distance is estimated by using the Macquart relation which was obtained for 8 localized FRBs, and we find it still applicable for 18 sources after adding the latest 10 new localized FRBs. In addition, we test the validity of the luminosity distribution up to the Macquart relation and find that the lognormal form feature decreases as the uncertainty increases. Moreover, we compare the luminosity of these apparent non-repeaters with that of the previously observed 10 repeating FRBs also at low DM, noting that they belong to different lognormal distributions with the mean luminosity of non-repeaters being two times greater than that of repeaters. Therefore, from the two different lognormal distributions, different mechanisms for FRBs can be implied., Comment: 25 pages, 6 figures, 5 tables, published in Astrophysics and Space Science (ApSS) in July 2022

The properties of the young pulsars and their relations to the supernova remnants (SNRs) have been the interesting topics. At present, 383 SNRs in the Milky Way galaxy have been published, which are associated with 64 radio pulsars and 46 pulsars with high energy emissions. However, we noticed that 630 young radio pulsars with spin periods of less than half a second have been not yet observed the SNRs surrounding or nearby them, which arises a question of that could the two types of young radio pulsars with/without SNRs hold distinctive characteristics? Here, we employ the statistical tests on the two groups of young radio pulsars with (52) and without (630) SNRs to reveal if they share different origins. Kolmogorov-Smirnov (K-S) and Mann-Whitney-Wilcoxon (M-W-W) tests indicate that the two samples have the different distributions with parameters of spin period ($P$), derivative of spin period ($\dot P$), surface magnetic field strength ($B$), and energy loss rate ($\dot E$). Meanwhile, the cumulative number ratio between the pulsars with and without SNRs at the different spindown ages decreases significantly after $\rm10-20\,Kyr$. So we propose that the existence of the two types of supernovae (SNe), corresponding to their SNR lifetimes, which can be roughly ascribed to the low-energy and high-energy SNe. Furthermore, the low-energy SNe may be formed from the $\rm8-12\,M_{\odot}$ progenitor, e.g., possibly experiencing the electron capture, while the main sequence stars of $\rm12-25\,M_{\odot}$ may produce the high-energy SNe probably by the iron core collapse., Comment: 8 pages, 10 figures, 3 tables. Published in MNRAS

Security issues have gradually emerged with the continuous development of artificial intelligence (AI). Earlier work verified the possibility of converting neural network models into stegomalware, embedding malware into a model with limited impact on the model's performance. However, existing methods are not applicable in real-world attack scenarios and do not attract enough attention from the security community due to performance degradation and additional workload. Therefore, we propose an improved stegomalware EvilModel. By analyzing the composition of the neural network model, three new methods for embedding malware into the model are proposed: MSB reservation, fast substitution, and half substitution, which can embed malware that accounts for half of the model's volume without affecting the model's performance. We built 550 EvilModels using ten mainstream neural network models and 19 malware samples. The experiment shows that EvilModel achieved an embedding rate of 48.52\%. A quantitative algorithm is proposed to evaluate the existing embedding methods. We also design a trigger and propose a threat scenario for the targeted attack. The practicality and effectiveness of the proposed methods were demonstrated by experiments and analyses of the embedding capacity, performance impact, and detection evasion., Comment: A newer version of this paper has been accepted at Computers & Security. Free access to the final version at https://authors.elsevier.com/c/1fJhFc43uylbS before August 16, 2022. This paper is an extended version of work that was first presented at the 26th IEEE Symposium on Computers and Communications (ISCC 2021)

Delivering malware covertly and evasively is critical to advanced malware campaigns. In this paper, we present a new method to covertly and evasively deliver malware through a neural network model. Neural network models are poorly explainable and have a good generalization ability. By embedding malware in neurons, the malware can be delivered covertly, with minor or no impact on the performance of neural network. Meanwhile, because the structure of the neural network model remains unchanged, it can pass the security scan of antivirus engines. Experiments show that 36.9MB of malware can be embedded in a 178MB-AlexNet model within 1% accuracy loss, and no suspicion is raised by anti-virus engines in VirusTotal, which verifies the feasibility of this method. With the widespread application of artificial intelligence, utilizing neural networks for attacks becomes a forwarding trend. We hope this work can provide a reference scenario for the defense on neural network-assisted attacks., Comment: To be appear at 26th IEEE Symposium on Computers and Communications (ISCC 2021)

Fast radio bursts (FRBs) are extremely strong radio flares lasting several milliseconds, most of which come from unidentified objects at a cosmological distance. They can be apparently repeating or not. In this paper, we analyzed 18 repeaters and 12 non-repeating FRBs observed in the frequency bands of 400-800 MHz from CHIME. We investigated the distributions of FRB isotropic-equivalent radio luminosity, considering the K correction. Statistically, the luminosity distribution can be better fitted by Gaussian form than by power-law. Based on the above results, together with the observed FRB event rate, pulse duration, and radio luminosity, FRB origin models are evaluated and constrained such that the gamma-ray bursts (GRBs) may be excluded for the non-repeaters while magnetars or neutron stars (NSs) emitting the supergiant pulses are preferred for the repeaters. We also found the necessity of a small FRB emission beaming solid angle (about 0.1 sr) from magnetars that should be considered, and/or the FRB association with soft gamma-ray repeaters (SGRs) may lie at a low probability of about 10%. Finally, we discussed the uncertainty of FRB luminosity caused by the estimation of the distance that is inferred by the simple relation between the redshift and dispersion measure (DM)., Comment: 12 pages, 2 figures, 2 tables. Accepted in Research in Astronomy and Astrophysics (RAA)

Volatility asymmetry is a hot topic in high-frequency financial market. In this paper, we propose a new econometric model, which could describe volatility asymmetry based on high-frequency historical data and low-frequency historical data. After providing the quasi-maximum likelihood estimators for the parameters, we establish their asymptotic properties. We also conduct a series of simulation studies to check the finite sample performance and volatility forecasting performance of the proposed methodologies. And an empirical application is demonstrated that the new model has stronger volatility prediction power than GARCH-It\^{o} model in the literature., Comment: 25 pages, 1 figures, 4 tables

Fast Radio Bursts (FRBs) are the short, strong radio pulses lasting several milliseconds. They are subsequently identified, for the most part, as emanating from unknown objects at cosmological distances. At present, over one hundred FRBs have been verified, classified into two groups: repeating bursts (20 samples) and apparently non-repeating bursts (91 samples). Their origins, however, are still hotly debated. Here,we investigate the statistical classifications for the two groups of samples to see if the non-repeating and repeating FRBs have different origins by employing Anderson-Darling (A-D) test and Mann-Whitney-Wilcoxon (M-W-W) test. Firstly, by taking the pulse width as a statistical variant, we found that the repeating samples do not follow the Gaussian statistics (may belong to a chi-square distribution), although the overall data and non-repeating group do follow the Gaussian. Meanwhile, to investigate the statistical differences between the two groups, we turn to M-W-W test and notice that the two distributions have different origins. Secondly, we consider the FRB radio luminosity as a statistical variant, and find that both groups of samples can be regarded as the Gaussian distributions under the A-D test, although they have different origins according to M-W-W tests. Therefore, statistically, we can conclude that our classifications of both repeaters and non-repeaters are plausible, that the two FRB classes have different origins, or each has experienced distinctive phases or been subject to its own physical processes., Comment: 7 pages, 5 figures, 3 tables. Accepted for publication in MNRAS

Command and control (C&C) is important in an attack. It transfers commands from the attacker to the malware in the compromised hosts. Currently, some attackers use online social networks (OSNs) in C&C tasks. There are two main problems in the C&C on OSNs. First, the process for the malware to find the attacker is reversible. If the malware sample is analyzed by the defender, the attacker would be exposed before publishing the commands. Second, the commands in plain or encrypted form are regarded as abnormal contents by OSNs, which would raise anomalies and trigger restrictions on the attacker. The defender can limit the attacker once it is exposed. In this work, we propose DeepC2, an AI-powered C&C on OSNs, to solve these problems. For the reversible hard-coding, the malware finds the attacker using a neural network model. The attacker's avatars are converted into a batch of feature vectors, and the defender cannot recover the avatars in advance using the model and the feature vectors. To solve the abnormal contents on OSNs, hash collision and text data augmentation are used to embed commands into normal contents. The experiment on Twitter shows that command-embedded tweets can be generated efficiently. The malware can find the attacker covertly on OSNs. Security analysis shows it is hard to recover the attacker's identifiers in advance., Comment: A later version of this paper is accepted at the 24th International Conference on Information and Communications Security (ICICS 2022)

Constructing stealthy malware has gained increasing popularity among cyber attackers to conceal their malicious intent. Nevertheless, the constructed stealthy malware still fails to survive the reverse engineering by security experts. Therefore, this paper modeled a type of malware with an "unbreakable" security attribute-unbreakable malware (UBM), and made a systematical probe into this new type of threat through modeling, method analysis, experiments, evaluation and anti-defense capacity tests. Specifically, we first formalized the definition of UBM and analyzed its security attributes, put forward two core features that are essential for realizing the "unbreakable" security attribute, and their relevant tetrad for evaluation. Then, we worked out and implemented four algorithms for constructing UBM, and verified the "unbreakable" security attribute based on our evaluation of the abovementioned two core features. After that, the four verified algorithms were employed to construct UBM instances, and by analyzing their volume increment and anti-defense capacity, we confirmed real-world applicability of UBM. Finally, to address the new threats incurred by UBM to the cyberspace, this paper explored some possible defense measures, with a view to establishing defense systems against UBM attacks., Comment: 13 pages, 11 figures, 4 tables