An Improved Dictionary Cracking Scheme Based on Multiple GPUs for Wi-Fi Network

The Internet has penetrated all aspects of human society and has promoted social progress.Cyber-crimes in many forms are commonplace and are dangerous to society and national security.Cybersecurity has become a major concern for citizens and governments.The Internet functions and software applications play a vital role in cybersecurity research and practice.Most of the cyber-attacks are based on exploits in system or application software.It is of utmost urgency to investigate software security problems.The demand for Wi-Fi applications is proliferating but the security problem is growing,requiring an optimal solution from researchers.To overcome the shortcomings of the wired equivalent privacy(WEP)algorithm,the existing literature proposed security schemes forWi-Fi protected access(WPA)/WPA2.However,in practical applications,the WPA/WPA2 scheme still has some weaknesses that attackers exploit.To destroy a WPA/WPA2 security,it is necessary to get a PSK pre-shared key in pre-shared key mode,or an MSK master session key in the authentication mode.Brute-force cracking attacks can get a phase-shift keying(PSK)or a minimum shift keying(MSK).In real-world applications,many wireless local area networks(LANs)use the pre-shared key mode.Therefore,brute-force cracking of WPA/WPA2-PSK is important in that context.This article proposes a new mechanism to crack theWi-Fi password using a graphical processing unit(GPU)and enhances the efficiency through parallel computing of multiple GPU chips.Experimental results show that the proposed algorithm is effective and provides a procedure to enhance the security of Wi-Fi networks.

WiMA:Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

Despite the planned installation and operations of the traditional IEEE 802.11 networks,they still experience degraded performance due to the number of inefficiencies.One of the main reasons is the received signal strength indicator(RSSI)association problem,in which the user remains connected to the access point(AP)unless the RSSI becomes too weak.In this paper,we propose a multi-criterion association(WiMA)scheme based on software defined networking(SDN)in Wi-Fi networks.An association solution based on multi-criterion such as AP load,RSSI,and channel occupancy is proposed to satisfy the quality of service(QoS).SDNhaving an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance.To implementWiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator.The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30%and enhances the throughput by 20%–50%,hence maintaining user fairness and accommodating more wireless devices and traffic load in the network,when compared to traditional client-driven(CD)approach and state of the art Wi-Balance approach.

Security Threat and Data Consumption as Mojor Nuisance of Social Media on Wi-Fi Network

This research is about the nuisances of social media applications on a Wi-Fi network at a university campus in Ghana. The aim was to access the security risk on the network, the speed of the network, and the data consumption of those platforms on the network. Network Mapper (Nmap Zenmap) Graphical User Interface 7.80 application was used to scan the various social media platforms to identify the protocols, ports, services, etc. to enable in accessing the vulnerability of the network. Data consumption of users’ mobile devices was collected and analyzed. Device Accounting (DA) based on the various social media applications was used. The results of the analysis revealed that the network is prone to attacks due to the nature of the protocols, ports, and services on social media applications. The numerous users with average monthly data consumption per user of 4 gigabytes, 300 megabytes on social media alone are a clear indication of high traffic as well as the cost of maintaining the network. A URL filtering of the social media websites was proposed on Rockus Outdoor AP to help curb the nuisance.

Application of virtual reality technology improves the functionality of brain networks in individuals experiencing pain

Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.

Unlocking the future:Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response

BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment responses.AIM To predict prognosis and immunotherapy response in patients diagnosed with OC using mitochondrial genes and neural networks.METHODS Prognosis,immunotherapy efficacy,and next-generation sequencing data of patients with OC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus.Mitochondrial genes were sourced from the MitoCarta3.0 database.The discovery cohort for model construction was created from 70% of the patients,whereas the remaining 30% constituted the validation cohort.Using the expression of mitochondrial genes as the predictor variable and based on neural network algorithm,the overall survival time and immunotherapy efficacy(complete or partial response)of patients were predicted.RESULTS In total,375 patients with OC were included to construct the prognostic model,and 26 patients were included to construct the immune efficacy model.The average area under the receiver operating characteristic curve of the prognostic model was 0.7268[95% confidence interval(CI):0.7258-0.7278]in the discovery cohort and 0.6475(95%CI:0.6466-0.6484)in the validation cohort.The average area under the receiver operating characteristic curve of the immunotherapy efficacy model was 0.9444(95%CI:0.8333-1.0000)in the discovery cohort and 0.9167(95%CI:0.6667-1.0000)in the validation cohort.CONCLUSION The application of mitochondrial genes and neural networks has the potential to predict prognosis and immunotherapy response in patients with OC,providing valuable insights into personalized treatment strategies.

Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.

一种Wi-Fi RTT/数据驱动惯性导航行人室内定位方法

为了研究基于智能手机的行人室内定位方法,并提高其精度,本文提出了一种基于Wi-Fi往返时间(RTT)、惯性测量单元(IMU)的定位系统。该方法主要包括3部分:(1)使用扩展卡尔曼滤波融合测距信息的Wi-Fi RTT室内定位方法;(2)适用于多手机使用模式的航位推算方法,该方法基于长短时记忆模型(LSTM)建立神经网络模型,预测行人运动速度及航向;(3)基于误差状态卡尔曼滤波的Wi-Fi RTT/数据驱动惯性导航融合定位方法,进一步提高定位精度。试验结果表明,与单一的基于Wi-Fi RTT方法和数据驱动惯性导航方法相比,本文方法的平均定位精度提升了10%~20%。

基于Wi-Fi感知的多用户身份识别研究

随着无线感知技术的发展,基于Wi-Fi的身份识别研究在人机交互和家居安防等领域备受关注。尽管基于Wi-Fi信号的身份识别已经取得了初步的成功,但是目前主要适用于用户独立行为场景,并发行为下的多用户身份识别仍然面临着一系列挑战,包括用户之间的相互干扰以及模型鲁棒性差等问题。因此,提出了一种并发行为下多用户身份识别系统Wiblack,其核心思想是训练一个多分支深度神经网络(Wiblack-Net)来提取每个单用户的独特特征。首先,利用主干网络提取多用户之间的共同特征;然后,为每个用户分配一个二分类器以此判断给定群体中是否存在目标用户,在此基础上基于并发行为实现多个用户身份识别。此外,将Wiblack与多个独立的二分类模型和单个多分类模型进行对比实验,对运行效率和系统性能进行分析。实验结果显示,在同时识别3个用户身份时,Wibalck平均准确率达到了92.97%,平均精确度为93.71%,平均召回率为93.24%,平均F1值为92.43%。

Convolutional Neural Networks Based Indoor Wi-Fi Localization with a Novel Kind of CSI Images

Indoor Wi-Fi localization of mobile devices plays a more and more important role along with the rapid growth of location-based services and Wi-Fi mobile devices.In this paper,a new method of constructing the channel state information(CSI)image is proposed to improve the localization accuracy.Compared with previous methods of constructing the CSI image,the new kind of CSI image proposed is able to contain more channel information such as the angle of arrival(AoA),the time of arrival(TOA)and the amplitude.We construct three gray images by using phase differences of different antennas and amplitudes of different subcarriers of one antenna,and then merge them to form one RGB image.The localization method has off-line stage and on-line stage.In the off-line stage,the composed three-channel RGB images at training locations are used to train a convolutional neural network(CNN)which has been proved to be efficient in image recognition.In the on-line stage,images at test locations are fed to the well-trained CNN model and the localization result is the weighted mean value with highest output values.The performance of the proposed method is verified with extensive experiments in the representative indoor environment.

基于Wi-Fi指纹且计算外包的室内定位隐私保护方案

为了解决室内定位中用户和服务器双方的隐私保护问题,提出了一种在使用Paillier加密的过程中将部分计算外包给云服务器的方案,这不仅保护了用户和定位服务器的隐私,而且避免了产生过大的计算和通信开销。该方案的主要思想是服务器先在离线阶段建立指纹数据库,在线阶段用户将k匿名算法和Paillier加密结合,将加密后的Wi-Fi指纹发送给定位服务器,服务器对接收到的Wi-Fi指纹和数据库指纹进行聚合处理,然后外包给云服务器进行解密和距离计算,最终得到定位结果。理论分析和实验结果表明了所提方案的安全性、有效性和实用性。

基于Wi-Fi信号感知技术的图书馆特殊群体服务研究

特殊群体是图书馆用户的重要组成部分,采用数字技术帮助特殊群体享受均等化的公共文化服务,是无障碍图书馆建设的重要部分。文章在介绍面向人机物融合的Wi-Fi信号感知技术的基础上,梳理了其在图书馆特殊群体服务中的具体应用场景。Wi-Fi信号感知技术在图书馆特殊群体服务中具有很好的应用价值,但也存在一些弊端和问题需要进一步优化和解决,在多种技术的加持下突破服务壁垒,提高服务质量。

融合安全的广电5G公共Wi-Fi技术探索

本文针对公共场所Wi-Fi网络接入方式存在的安全及法律风险,提出利用广电5G CPE,结合Wi-Fi Portal认证、5G专网和VXLAN隧道等技术,构造一种融合安全的广电5G公共Wi-Fi接入网络,旨在探索出一种较低成本的安全的5G公共Wi-Fi接入解决方案。

基于通感一体化的Wi-Fi卸载匹配算法

针对目前移动数据流量激增所导致的通感一体化无线通信网络系统中的拥塞和过载问题,提出一种基于通感一体化的Wi-Fi卸载匹配算法。首先,基于信息论综合考虑系统的通信吞吐量和感知互信息量,定义系统的效用函数,在满足用户QoS的同时最大化系统的总效用;其次,基于图论的思想建立Wi-Fi信道分配算法为每个Wi-Fi接入点分配信道,并将用户的接入选择问题建立为具有外部性的多对一匹配博弈模型。仿真结果表明,所设计的卸载策略能够提高系统的总效用,缓解基站处的数据压力。

WiFace:A Secure GeoSocial Networking System Using Wi-Fi Based Multihop MANET

A number of mobile Online Social Networking （OSN） services have appeared in the market in recent times. While most mobile systems benefit greatly from cloud services, centralized servers and communications infrastructure is not always available. Nor are location-based services offered to mobile devices without GPS. To take advantage of cloud and to address these problems, a Wi-Fi based multihop networking system called MoNet is proposed. On top of MONET we propose a privacy-aware geosocial networking service called WiFace. Where there is no infrastructure, a distributed content sharing protocol significantly shortens the relay path, reduces conflicts, and improves data availability. Furthermore, a security mechanism is developed to protect privacy. Comprehensive experiments performed on MoNet show that the system is more than sufficient to support social networking and even audio and video applications.

Wi-Fi RTT/RSS混合定位CRLB推导与最优节点布局设计

基于精细时间测量协议(FTM)的Wi-Fi RTT定位是目前领域内的研究热点,但其定位算法性能的评估手段较为单一且缺乏理论基础,Wi-Fi接入点(AP)布局对于定位精度的影响也尚未深入研究。本文以智能手机Wi-Fi FTM为研究对象,推导了基于Wi-Fi RTT/RSS混合定位方法的克拉美罗下界(CRLB),阐明了单一定位与混合定位方法CRLB的理论关系,为算法性能评估确立了理论依据;研究了Wi-Fi AP布局对RTT/RSS混合定位精度的影响,以增强遗传算法(EGA)和CRLB为基础,设计了Wi-Fi RTT/RSS混合定位的最优节点布局方案。研究表明,Wi-Fi RSS/RTT混合定位可作为高效的FTM定位方法,提出的基于EGA和CRLB的最优节点布局方法能快速给出定位区域内的最优AP布局方案。试验结果表明,在最优节点布局下(7个Wi-Fi节点),Wi-Fi RSS、RTT和RSS/RTT混合定位在本文试验环境的理论精度分别为0.92、1.07和0.61 m。研究结果可为Wi-Fi FTM定位算法性能评估提供理论支持,也能为合理布设Wi-Fi节点、减少定位成本投入提供可行方案。

不依赖位置坐标的室内Wi-Fi网络覆盖度量方法

3GPP在版本16(R16,Release 16)中升级了最小化路测(MDT,minimization of drive test)技术,提出移动终端可利用4G/5G网络自主上报Wi-Fi信号的接收信号强度指示(RSSI,received signal strength indicator),为运营商度量Wi-Fi网络的覆盖率带来了可能性。然而,现有基于MDT技术的网络覆盖度量方法严重依赖GPS提供的位置坐标,但全球定位系统(GPS,global positioning system)不能提供室内精准定位,无法用于室内Wi-Fi网络的覆盖度量。为此,提出了一种不依赖位置坐标的RSSI聚类方法,充分利用室内相近位置RSSI的统计相似性,区分不同位置的RSSI测量差异,在无位置坐标条件下准确估计出室内Wi-Fi网络的覆盖率。实验结果表明,所提方法估计的覆盖率与基于真实位置坐标测量的覆盖率相近,度量准确度明显优于现有的其他方法。

Pluggable multitask diffractive neural networks based on cascaded metasurfaces

Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).

Social-ecological perspective on the suicidal behaviour factors of early adolescents in China:a network analysis

Background In early adolescence,youth are highly prone to suicidal behaviours.Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To explore the risk and protective factors of suicidal behaviours(ie,suicidal ideation,plans and attempts)in early adolescence in China using a social-ecological perspective.Methods Using data from the cross-sectional project‘Healthy and Risky Behaviours Among Middle School Students in Anhui Province,China',stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020.Network analysis was employed to examine the correlates of suicidal ideation,plans and attempts at four levels,namely individual(sex,academic performance,serious physical llness/disability,history of self-harm,depression,impulsivity,sleep problems,resilience),family(family economic status,relationship with mother,relationship with father,family violence,childhood abuse,parental mental illness),school(relationship with teachers,relationship with classmates,school-bullying victimisation and perpetration)and social(social support,satisfaction with society).Results In total,37.9%,19.0%and 5.5%of the students reported suicidal ideation,plans and attempts in the past 6 months,respectively.The estimated network revealed that suicidal ideation,plans and attempts were collectively associated with a history of self-harm,sleep problems,childhood abuse,school bullying and victimisation.Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse.Notably,the network also showed unique correlates of suicidal ideation(sex,weight=0.60;impulsivity,weight=0.24;family violence,weight=0.17;relationship with teachers,weight=-0.03;school-bullying perpetration,weight=0.22),suicidal plans(social support,weight=-0.15)and suicidal attempts(relationship with mother,weight=-0.10;parental mental llness,weight=0.61).Conclusions This study identified the correlates of suicidal ideation,plans and attempts,and provided practical implications for suicide prevention for young adolescents in China.Firstly,this study highlighted the importance of joint interventions across multiple departments.Secondly,the common risk factors of suicidal ideation,plans and attempts were elucidated.Thirdly,this study proposed target interventions to address the unique influencing factors of suicidal ideation,plans and attempts.

A Framework for Multi-Hop Ad-Hoc Networking over Wi-Fi Direct with Android Smart Devices

The wide diffusion of mobile devices that natively support ad hoc communication technologies has led to several protocols for enabling and optimizing Mobile Ad Hoc Networks (MANETs). Nevertheless, the actual utilization of MANETs in real life seems limited due to the lack of protocols for the automatic creation and evolution of ad hoc networks. Recently, a novel P2P protocol named Wi-Fi Direct has been proposed and standardized by the Wi-Fi Alliance to facilitate nearby devices’ interconnection. Wi-Fi Direct provides high-performance direct communication among devices, includes different energy management mechanisms, and is now available in most Android mobile devices. However, the current implementation of Wi-Fi Direct on Android has several limitations, making the Wi-Fi Direct network only be a one-hop ad-hoc network. This paper aims to develop a new framework for multi-hop ad hoc networking using Wi-Fi Direct in Android smart devices. The framework includes a connection establishment protocol and a group management protocol. Simulations validate the proposed framework on the OMNeT++ simulator. We analyzed the framework by varying transmission range, number of hops, and buffer size. The results indicate that the framework provides an eventual 100% packet delivery for different transmission ranges and hop count values. The buffer size has enough space for all packets. However, as buffer size decreases, the packet delivery decreases proportionally.