查看更多>>摘要：Deep neural network(DNN)is applied widely in many applications and achieves state-of-the-art performance.However,DNN lacks transparency and in-terpretability for users in structure.Attackers can use this feature to embed trojan horses in the DNN structure,such as inserting a backdoor into the DNN,so that DNN can learn both the normal main task and additional mali-cious tasks at the same time.Besides,DNN relies on data set for training.Attackers can tamper with training data to interfere with DNN training process,such as attaching a trigger on input data.Because of defects in DNN struc-ture and data,the backdoor attack can be a serious threat to the security of DNN.The DNN attacked by backdoor performs well on benign inputs while it outputs an attack-er-specified label on trigger attached inputs.Backdoor at-tack can be conducted in almost every stage of the ma-chine learning pipeline.Although there are a few re-searches in the backdoor attack on image classification,a systematic review is still rare in this field.This paper is a comprehensive review of backdoor attacks.According to whether attackers have access to the training data,we di-vide various backdoor attacks into two types:poisoning-based attacks and non-poisoning-based attacks.We go through the details of each work in the timeline,discuss-ing its contribution and deficiencies.We propose a de-tailed mathematical backdoor model to summary all kinds of backdoor attacks.In the end,we provide some insights about future studies.
查看更多>>摘要：Orthogonal frequency-division multiplex-ing(OFDM)has been developed into a popular modula-tion scheme for wireless communication systems,used in applications such as LTE and 5G.In wireless communica-tion systems,nonlinearity caused by radio frequency(RF)amplifiers will generate distortions to both passband and adjacent channels such that the transmission quality is degraded.The study of this article aims to predict the power spectrum for OFDM based signals at the output of an RF amplifier due to the nonlinearity.In this article,based on Taylor polynomial coefficients,a power spec-trum expression for amplified OFDM signals in terms of intercept points(up to nth-order)is derived.This model is useful to RF engineers in choosing and testing RF amp-lifiers with appropriate specifications,such as intercept points and gain,to meet the requirements of wireless standards.Measurements are carried out to confirm the results of the proposed model.
查看更多>>摘要：Pseudolites(PLs)are ground-based satellites,providing users with navigation solutions.However,implementation of the PL system leads to the near-far problem.In this paper,we proposed an im-proved navigation PL signal structure of combing Kasami sequences and the pulsing scheme to mitigate the near-far effect.The pulse modulation method is adopted to ensure that the PLs transmit signals at different timeslots and reduce the PL signals'mutual interference.Additionally,we employ the small set of Kasami sequences with good cross-correlation properties to improve the anti-interfer-ence ability.A simulation test based on software is car-ried out to evaluate the performance of the proposed sig-nal.The simulation proves that the improved PL signal has an impulsive power spectral density,makes it a feas-ible solution to mitigate the near-far effect,and performs better in the capture.
查看更多>>摘要：Aiming at the problem that the existing labeled multi-Bernoulli(LMB)method has a single and fixed model set,an LMB maneuvering target tracking al-gorithm via Takagi-Sugeno-Kang(TSK)iterative regres-sion multiple model is proposed.In the TSK iterative re-gression modeling,the feature information of the targets is analyzed and represented by multiple semantic fuzzy sets.Then the state is expanded to introduce model in-formation,thereby the adaptive multi-model idea is incor-porated into the framework of the LMB method to solve the uncertain maneuverability of moving targets.Finally,the simulation results show that the proposed algorithm can effectively achieve maneuvering target tracking in the nonlinear system.
查看更多>>摘要：Multiple secondary users(SUs)perform collaborative spectrum sensing(CSS)in cognitive radio networks to improve the sensing performance.However,this system severely degrades with spectrum sensing data falsification(SSDF)attacks from a large number of mali-cious secondary users,i.e.,massive SSDF attacks.To mit-igate such attacks,we propose a joint spectrum sensing and spectrum access framework.During spectrum sensing,each SU compares the decisions of CSS and independent spectrum sensing(IndSS),and then the reliable decisions are adopted as its final decisions.Since the transmission slot is divided into several tiny slots,at the stage of spec-trum access,each SU is assigned with a specific tiny time slot.In accordance with its independent final spectrum decisions,each node separately accesses the tiny time slot.Simulation results verify effectiveness of the proposed al-gorithm.
查看更多>>摘要：This paper deals with the 3-D moving source localization using time difference of arrival(TDOA),frequency difference of arrival(FDOA),angle of arrival(AOA)and AOA rate measurements,gathered from a set of spatially distributed receivers.The TDOA,FDOA,AOA and AOA rate measurement equations were firstly established according to the space geometric rela-tionship of the source relative to the receivers.Then an efficient closed-form algorithm for source position and ve-locity estimation from the quadruple hybrid measure-ments was proposed.The proposed algorithm converts the nonlinear measurement equations into a linear set of equations,which can then be used to estimate the source position and velocity applying weighted least square(WLS)minimization.In contrast to existing two-stage WLS algorithms,the proposed algorithm does not intro-duce any nuisance parameters and requires merely one-stage,which enables for source localization with the few-est receivers necessary.Theoretical accuracy analysis shows that the proposed algorithm reaches the Cramer-Rao lower bound,and simulation studies corroborate the efficiency and superiority of the proposed algorithm over other algorithms.
YANG HonghongSHANG JunchaoLI JingjingZHANG Yumei...
266-276页
查看更多>>摘要：Vehicles or pedestrians tracking is an im-portant task in intelligent transportation system.In this paper,we propose an online multi-object tracking for in-telligent traffic platform that employs improved sparse representation and structural constraint.We first build the spatial-temporal constraint via the geometric rela-tions and appearance of tracked objects,then we con-struct a robust appearance model by incorporating the discriminative sparse representation with weight con-straint and local sparse appearance with occlusion analys-is.Finally,we complete data association by using maxim-um a posteriori in a Bayesian framework in the pursuit for the optimal detection estimation.Experimental res-ults in two challenging vehicle tracking benchmark data-sets show that the proposed method has a good tracking performance.
查看更多>>摘要：Hilbert curve describes a one-to-one mapping between multidimensional space and 1D space.Most traditional 3D Hilbert encoding and decoding al-gorithms work on order-wise manner and are not aware of the difference between different input data and spend equivalent computing costs on them,thus resulting in a low efficiency.To solve this problem,in this paper we design efficient 3D state views for fast encoding and de-coding.Based on the state views designed,a new encod-ing algorithm(JFK-3HE)and a new decoding algorithm(JFK-3HD)are proposed.JFK-3HE and JFK-3HD can avoid executing iteratively encoding or decoding each or-der by skipping the first 0s in input data,thus decreasing the complexity and improving the efficiency.Experiment-al results show that JFK-3HE and JFK-3HD outperform the state-of-the-arts algorithms for both uniform and skew-distributed data.
查看更多>>摘要：AEGIS,an authenticated encryption(AE)algorithm designed by H.J.Wu and B.Preneel,is one of the six winners of the Competition for Authentic-ated Encryption:Security,Applicability,and Robustness,which was launched by the National Institute of Stand-ards and Technology.In this paper,we comprehensively investigate the existence of collision in the initialization of AEGIS-128 and evaluate the number of advanced encryp-tion standard(AES)round functions involved in initializ-ation,which reflects the resistance to differential attack.As a result,we find that there are 40 AES round func-tions,which is less than 50 ones claimed in the design document.We also prove that AEGIS-128 is strong enough to resist adversary who has access to partial state.In particular,we present a collision-based distinguisher and exploit it to recover the key of 4-step and 5-step(out of the full 10)AEGIS-128.The time and memory com-plexities are about 229.7 and 226 respectively.Specifically,we quantize the attack of 4-step AEGIS-128,in which we solve the technical issue of dealing with the function that does not fulfill Simon's promise.It is noted that the nonce is not reused in our work.Although we present some res-ults of AEGIS-128 that exceed the existed analysis,the security margin of AEGIS-128 remains large.
查看更多>>摘要：Identifying and determining behaviors of attack gangs is not only an advanced stage of the net-work security event tracing and analysis,but also a core step of large-scale combat and punishment of cyber at-tacks.Most of the work in the field of distributed denial of service(DDoS)attack analysis has focused on DDoS attack detection,and a part of the work involves the re-search of DDoS attack sourcing.We find that very little work has been done on the mining and analysis of DDoS attack gangs.DDoS attack gangs naturally have the at-tributes of human community relations.We propose a framework named HiAtGang,in which we define the concept of the gang detection in DDoS attacks and intro-duce the community analysis technology into DDoS at-tack gang analysis.Different attacker clustering al-gorithms are compared and analyzed.Based on analysis results of massive DDoS attack events that recorded by CNCERT/CC(The National Computer Network Emer-gency Response Technical Team/Coordination Center of China),the effective gang mining and attribute calibra-tion have been achieved.More than 250 DDoS attack gangs have been successfully tracked.Our research fills the gaps in the field of the DDoS attack gang detection and has supported CNCERT/CC in publishing"Analysis Report on DDoS Attack Resources"for three consecutive years and achieved a good practical effect on combating DDoS attack crimes.
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