• <tr id="yyy80"></tr>
  • <sup id="yyy80"></sup>
  • <tfoot id="yyy80"><noscript id="yyy80"></noscript></tfoot>
  • 99热精品在线国产_美女午夜性视频免费_国产精品国产高清国产av_av欧美777_自拍偷自拍亚洲精品老妇_亚洲熟女精品中文字幕_www日本黄色视频网_国产精品野战在线观看 ?

    Building a Trust Model for Secure Data Sharing(TM-SDS)in Edge Computing Using HMAC Techniques

    2022-08-23 02:15:02KarthikeyanandMadhavan
    Computers Materials&Continua 2022年6期

    K.Karthikeyanand P.Madhavan

    School of Computing,SRM Institute of Technology,Kattankulathur,Chennai,603203,India

    Abstract:With the rapid growth of Internet of Things(IoT)based models,and the lack amount of data makes cloud computing resources insufficient.Hence,edge computing-based techniques are becoming more popular in present research domains that makes data storage, and processing effective at the network edges.There are several advanced features like parallel processing and data perception are available in edge computing.Still, there are some challenges in providing privacy and data security over networks.To solve the security issues in Edge Computing,Hash-based Message Authentication Code(HMAC)algorithm is used to provide solutions for preserving data from various attacks that happens with the distributed network nature.This paper proposed a Trust Model for Secure Data Sharing (TM-SDS) with HMAC algorithm.Here,data security is ensured with local and global trust levels with the centralized processing of cloud and by conserving resources effectively.Further,the proposed model achieved 84.25%of packet delivery ratio which is better compared to existing models in the resulting phase.The data packets are securely transmitted between entities in the proposed model and results showed that proposed TM-SDS model outperforms the existing models in an efficient manner.

    Keywords: Secure data sharing; edge computing; global trust levels; parallel processing

    1 Introduction

    Internet of Things(IoT)is the recent advancement in communication,in which data is the valuable resource,providing several intelligent services to the people[1].However,the IoT data contain private data and can disclose the user identities,if it is not efficiently secured[2].For instance,the malicious user can utilize the user’s private data like date of birth,bank details and so on.The authorized person identification is considered that influences the adverse effects, when there are responsible for user actions.So,an effective privacy preserving models and protocols are necessary in edge computing.In recent times, edge computing is a distributed computation model with many trust models in which the coexistence of multiple operational entities,authentication models require the attribute validation for every unit in single trust model [3,4].Hence, the entities are mutually authenticated each other with varied secure models.For some resource-limited entities, it is unfeasible to store or process big data or to run a highly complex trust model.Edge computing model comprises big data processing,parallel computation aspects,distributed data transmission processing,location-aware,mobility and dynamicity,and so on.The conventional privacy and security models in edge computing are ineffective for securing the massive data processing[5].Specifically,secure data processing and privacy preserving problems are effectively important.Major concerns that are faced in edge computing related to data security and privacy-preserving issues are lightweight and fine-grained, distributed access control,limited resources and efficient privacy preservation.

    The above-stated data security and privacy preserving issues of edge computing model are stimulated to develop a security model in edge computing.The edge computing model can solve the problems that are related with the centralized system by approaching data pipeline operations over the edge of models with resource accessibility and application needs[6,7].Moreover,the framework deployment is more advanced in developing model with content providers,network entity,and third party element.Thereby, it is essential to enhance the end-user experience, because of the energy computing strategies[8–10].Nevertheless,edge computing cannot secure the user data privacy,since new set of attacks with multiple attack models are associated with the heterogeneity of element resources, network measurement and user accessibility [11,12].So, a Trust Model for Secure Data Sharing(TM-SDS)with HMAC algorithm is proposed in this research paper.The technology utilizes data blocks that are connected with one another with a cryptographic hash key[13,14].However,the Homomorphic Encryption incorporating in edge computing is a challenging process,because of the resource constraints and the scalability problems.The contributions of the proposed model are listed below,

    · Developing enhanced privacy with efficient HMAC Algorithm.

    · Local and global trust levels are developed with the centralized processing of cloud and conserving resources effectively.

    · For data and communication security,HMAC algorithm is used with hashing concept.

    · Providing compatibility with the efficient trust chain process that makes effective decision making without depending on the central admin of each node.

    · Interoperability between the trust blocks for efficient data security over communication.

    · Evaluation of results based on factors such as processing delay,rate of security,packet delivery ratio,communication overhead and packet drop.

    The structure of this paper is organized as follows: Section 2 provides the concepts of security management in edge computing that are applied for data security so far.Section 3 presents the preliminaries that support the proposed idea.Section 4 discussed the working procedure of the proposed Trust Model.The results and evaluations are presented in Section 5 for evidencing the model efficiency.Finally,Section 6 concludes the paper with some motivations for enhancement.

    2 Related Works

    Each merchant in IoT based communications are used for developing smart entities based on requirements that acts effectively in dynamic platforms [15].In addition, the framed data are to be secured in such a way that no one can access or misuse data.A valuable review work that described the security issues in several computation platforms.Tao et al.[16] developed a new multi-layered cloud architectural framework in which the services are given with the IoT based smart devices.Additionally,an ontology-based knowledge representation model has been presented in this literature.Lee et al.[17]used semantic web rule language for an effective interoperability of heterogeneous devices.

    An Intrusion Detection model(IDM)is developed based on SDN framework by Nobakht et al.[18].The developed model is used to solve the issues of host-based attack.In addition,the communicational,and computational overhead is significantly reduced by designing the traffic flow based on the target nodes.In this literature,IoT-IDM involved in monitoring the attack-based network activities,and tried to derive the attributes based on data flow of networks.The machine learning techniques are used for the classification of malicious traffics accurately.Gheisari et al.[19] and Madhavan et al.[20] implemented Support Vector Machine (SVM) technique with homomorphic encryption and friendly algorithm to detect the normal and abnormal node activities.The classification operations are performed based on the selected features of the attacks.Mohammadi et al.[21]and Mamolar et al.[22]has tried to resolve the attacks with defined traffic protocols with proper switching and hubs.

    Yu et al.[23] has presented a four image encryption algorithm based on chaos and computer generated hologram and quaternion Fresnel transform technique.The developed algorithm improved the security and weaken the correlation, where the extensive experiment showed the effectiveness of four image encryption algorithm.Esposito et al.[24]developed a novel model to authorize and find the policies by leveraging on the block-chain technology for holding a global view of the security policies with-in the system.Further,Li et al.[25]implemented a new algorithm based on synergetic neural networks.Firstly, the developed algorithm embeds the gray watermark signals into discrete cosine transform components.Additionally,the companion algorithm along with co-operative neural network is used for the extraction of watermark.Lastly,the suspected watermark signal is considered as the input,and the output image is considered as the outcome of recognition mechanism.

    Stergiou et al.[26] developed an innovative architecture that operates in a wireless mobile 6G network to manage big data on smart buildings.Al-Qerem et al.[27]developed a new variant optimistic con-currency control protocol that decreases the computation, and communication at the cloud.Hence, the developed protocol supports transactional and scalability of the services.The author analyzed the validation process under three con-currency protocols based on the numerical studies.The validation results represent that the developed protocol is more beneficial for the IoT users.Tewari et al.[28] developed a new ultra-light weighted mutual authentication protocol that utilizes bit-wise operations.This protocol is effective by means of communication cost,and storage.Zheng,et al.[29]implemented a light-weighted authenticated encryption approach on the basis of discrete chaotic s box coupled map lattice that superiorly improves the security in IoT environment.Further,Yu et al.[30]developed a new single bit public key encryption approach on the basis of learning parity with noise for an effective encryption.The extensive experiment showed that the developed approach achieved better plaintext attack security.

    Gupta et al.[31] developed an attribute based searchable encryption algorithm that provides better flexibility and usability by means of effective search.The developed attribute based searchable encryption algorithm delivers better performance in medical field by preserving privacy of the health data by keeping the data in an encryption form.Tewari et al.[32]performed a mutual authentication process between server and the IoT devices on the basis of elliptic curve cryptography that provides better solution by means of attack resistance and communication over-head.Further,Alsmirat et al.[33] determines the optimal ratio of the finger-print image compression to improve the recognition accuracy of finger-print identification system.In this study,the experiment was performed on large in house dataset and the obtained results showed that the developed approach accurately determines the compression ratio.

    The major drawback noticed in the existing works is that the feature selection has been carried out with the static mode.Then,the malicious activities that are not detected in dynamic process,and also the existing models can secure only the target host and not the complete network.To address these issues,a new model is proposed in this research paper.

    3 Preliminaries

    This section describes the background research about the trust model.In this paper,the concepts of Homomorphic Encryption technique are incorporated to resolve the security issues and efficient resource utilization in Edge Computing.The basic edge computing model is depicted in Fig.1.

    Figure 1:General edge computing framework

    The Trust model estimates the security strength and computes the trust esteem value.A trust esteem value comprises of various parameters along with the security of edge computing.The sub parameters and functions also be evaluated in the Trust model[34,35].Fig.2 measure the conceptual view of the trust model with their parameter,sub parameter and functions[36].

    In Fig.2,‘A’addresses the Identity Management(IDM),which is the vital components of security frameworks in the cloud, where the cycle analyzed the sign strength with in it.The authentication process represented as ‘B’that increase the end user security access at the time of the login and verification process.The verified end user is determined by the strength of the authentication, and it is processed by the segments of trust models.The authorization process represented as ‘C’, which is measured by authorization strength.The cloud computing provides the authorization services by the various model using Access Control Strength (ACL) and all the activities need authorization permission in this stage.

    Figure 2:Conceptual view of trust model

    The data protection,confidentiality,communication,isolation and virtualization security process are represented from‘D’to‘I’,where the trust model security covers all aspects of parameters[37].The above boundaries are estimated independently and it is joined to calculate the distributed computing strength and application.

    4 Proposed Model

    In this section,the novel techniques for privacy preserving and utilization of effective computational resources are presented with the proposed model named Trust Model for Secure Data Sharing(TM-SDS) that includes HMAC algorithm for security in edge computing.The proposed model provides enhanced scalability with the secure and distributed storage mechanism, where the high security is achieved with the homomorphic encryption and HMAC algorithm with the trusted model.This process makes the distributed decision making effective without relying on the central admin,who has the control over each node in the network.Furthermore, the interoperability among the multiple blocks is effectively managed.Additionally,the local and the global trust levels are designed for efficient resource usage,which is graphically presented in Fig.3.

    Figure 3:Overall design of the proposed TM-SDS model

    In this research paper, the proposed trust model is implemented with the trust service levels called global and local trust levels.The home or the industrial routers are defined as the trust agent.Based on the demands of security platform,trust services are employed in both the local trust levels.Moreover,in this framework,the homomorphic encryption based trust model technology is enabled for communicating with each other without the requirement of central admin in the pattern of peerto-peer model.Additionally,the distributive characteristic of edge computing makes both parallel and serial levels based on the application requirements.For computing the authority,there are several trust ranges are defined based on entities,data trust,and user privacy related trust.

    Further, the proposed work comprises of three phases such as, (i) initialization phase, (ii) data encryption with homomorphic encryption,and(iii)secure data processing with HMAC.The functions performed in each phase are clearly depicted in Fig.4, which is executed in bottom-up manner,comprises lower,middle and upper layers.

    Figure 4:Layers and function in proposed TM-SDS model

    4.1 Initialization Phase

    In this phase,initial setups are processed by preparing the networks based on security demands.The system comprises of edge devices and aggregation point(Ap)for receiving the collected data from edge devices.The data are secured before sending toApfor data aggregation.Steps involved in the initialization phase are given as,

    · Each host of end device (D) in the edge computing network is provided with an identity asDi∈{1,...,n}.

    · Aggregation points are also provided for some device set,which are also given with identities.

    · The base station broadcasts a distinctive key-pair for all devices with similarApto produce HMAC for data security.

    4.2 Data Encryption with HE

    4.2.1 Process of Data Split

    Let it be in two months, answered Don Giovanni, for the time was nearly up that the devil had fixed13, and he wanted a whole month to himself to wash off the dirt of the past three years

    For enhancing the security process, the data split method is used here and the divided data are switched in pair-wise process.Here, it is taken that theApis connected with multiple devices, which are termed as,Di= {1,...,n}.For specific timestamp, the end devices in edge computing receive dataM={m1,m2,...,mn},respectively.The initial phase,each device‘D’,‘M’splits the acquired data into‘n’number of sections as,Sij(i∈1,2,...,n),(j∈1,2,...,n)considerably,in which‘n’points the number of devices presented in the network.The equation for data split is given as Eq.(1),

    Following the data split operation,the sections are interchanged with themselves.The section,‘S11’is protected by the device‘D1’,where the other devices are in effective distribution.Based on the device,D1is transmitting(n-1)sections of data,whereSij(ji)to others.Next to the process of swapping,the encryption process is performed,where the model HE derives fast encryption and decryption.The algorithm works on the basis of probabilistic asymmetric method for securing the scalar parameter of shared data.The process of key generation is demonstrated below.

    i.Key Generation Process

    1.Two random numbers ‘a(chǎn)’and ‘b’are selected, which are mutually independent and provides that is mathematically indicated in Eq.(2).

    It is assumed that the numbers are with equal length.

    2.Computen-abandβ=1,which is the parameter constant,for(x-1,y-1).

    3.Random integer‘L’is selected,whereL∈

    In which,functionFis given as,F(A)=(a-1)/n

    5.Here,the public key is derived as,(n,L)

    6.And,private key is stated as,(β,?)

    ii.Process of Encryption

    The obtained dataDi, in which 0 ≤Di≤n, a random number ‘v’is selected, that relies in between(0,n).The encrypted text(ET)is derived as Eq.(4),

    iii.Process of Decryption

    The‘ET’is decrypted using Eq.(5).

    4.2.2 HMAC Operations in the Proposed Model

    In this model, HMAC is produced for the ‘ET’, which effectively controls the impacts of node capture attacks and compromised node attacks in edge computing.Here, the HMAC for ET is generated with the identical keys that are used in theAps.The pseudocode for HMAC generation is given below;

    Algorithm 1: Process of HMAC Generation for ET 1.Begin 2.Network Setup Initialization//Key Generation:Select p1 and p2 ∈Z*n2,then P=p1,p2//HMAC Generation,Do Derive U ←F(p1)∈Z*n2 V ←G(p2(ID,i)))∈Z*n2 HMACET ←(U.V)+S)∈Z*n2 Call Data-Aggregation()Call homomorphic security()End

    4.2.3 Operations in Aggregation Point

    The data aggregation process is performed in secure manner and the process is explained below,which is run when the pseudocode calls Data-Aggregation().Moreover,the additive operations are performed as given as follows,

    The final results(FD)are derived using Eq.(7),

    The private keys are used for device-to-device communications that are to be updated frequently.In addition,the hashing operations are performed for one instant pad with the assumption that the initial private-key is taken as,‘q1’and the set ends with‘qn’for‘n’number of devices.

    The resultant data obtained for each device is portrayed in Tab.1 where,di(i∈(1,2,...,n))are the shared data to the edge devicesDi(i∈(1,2,...,n)).The respective encrypted data isdi0(i∈(1,2,...,n)).In this way, the real time data are acquired by end devices from the edge computing, which are by secured data storage and transmission between the servers.The data aggregation converts theHence, the data cannot be disclosed or accessed atApand the real shared data are more secure.

    Table 1: Results of secure data aggregation process

    When the edge devices share the obtained data,the real data is encrypted with the above operations and the Homomorphic_security()is executed at the upper layer for securing the keys from unknown access.The encrypted datadi0(i∈(1,2,...,n))is concealed with the public key of the cloud server before it is shared,which is given as Eq.(9),

    The hash rate is produced by each device with their unique identities(ID),time-stamp and ET.Here,the hash rate is given as,HS(ID‖tp‖ETi),and it helpsApto verify that the shared private data of the users are confidential and not accessed by anywhere between the transmission process.

    5 Results and Discussions

    The proposed model is simulated utilizing Network Simulator NS2 device.The results and discussions are presented in this section.Furthermore,the proposed model is accessed the evaluation metrics such as rate of model security,packet delivery rate,transmission delay,packet drop,communication overhead.For evidencing the model efficiency,the results are compared with Support Vector Machine for attack detection and IoT-Intrusion Detection Model(IDM).The initial parameter setting for the simulation tool is provided in the Tab.2.

    Table 2: Initial simulation settings

    The significant factor for determining the performance of the proposed model is the communication complexity.During the process of data accumulation,there are some possibilities for attackers to access the data, and the communication complexity is measured asO(d*y), where, d represents devices and y indicates number of third-party attackers possibly to attack the communication,which is to be less in an efficient model for communication.The evaluation results based on the factor called communication complexity is given in Fig.5.It is obvious from the results that the proposed model produces minimal complexity than other,since the risks of attacks are minimal in the model with the effectively defined trust model.

    Figure 5:Communication overhead-comparisons

    The Packet Delivery Ratio (PDR) is derived with respect to the simulation time and the results are portrayed in Fig.6.The proposed model achieves 84.25% of PDR in average, which is higher compared to other models such as SVM and IoT-IDM.The data packets are securely transmitted between entities in the proposed model.

    Figure 6:Packet delivery ratio vs.simulation time

    The transmission delay occurs in a communication model for various reasons and the major issue is the troubles caused by the attackers.In the proposed model,the security of data is effectively handled with the trust model and the homomorphic encryption based security implementations, the overall transmission delay is effectively reduced in the proposed model and the evidences are provided in the graph in Fig.7.Another factor,packer drop also should be minimal in efficient edge computing model.The evaluations are carried out against the simulation time and the results are depicted in Fig.8.It is shown that the proposed model achieves minimal packet drop than the comparative models.

    Figure 7:Transmission delay vs.packet size

    Figure 8:Packet drop vs.simulation time

    As mentioned earlier,the main motivation of the proposed model is to be derived an efficient data security mechanism for shared data between entities in edge computing.Hence, the security rate of the proposed model is evaluated against a particular attack called compromised node attack and the results are given in Fig.9.When the compromised attacks are happened in the proposed work, the model effectively detects the attack and showed that there is the attack possibility with minimal rate of security than others.The evaluations are performed against the simulation time.

    Figure 9:Security rate analysis

    6 Conclusion and Future Work

    This paper presented a secure communication model in edge computing called Trust Model for Secure Data Sharing (TM-SDS) with homomorphic encryption based Techniques.The model used Homomorphic Encryption and the cross verification is implemented with trust model.Moreover,the security of the shared data is provided with local and global trust levels to be considered with the centralized processing of cloud and conserving resources in efficient manner.HMAC is also utilized for enhancing the rate of data security at the aggregator point in the process of data transmission.The outcomes are assessed based on significant factors such as packet drop, model efficiency and PDR.The comparative analysis showed that the proposed model obtained better results and outperforms the results of the existing works with the effective integration of cryptography and trust model.In future,the proposed work is enhanced by deriving novel mechanisms for integrity verification and seamless communication between entities.In addition, the proposed work is also improved by implementing and evaluating in a real-time environment.

    Funding Statement:The authors received no specific funding for this study.

    Conflicts of Interest:The authors declare that they have no conflicts of interest to report regarding the present study.

    内射极品少妇av片p| 国产精品久久久久久av不卡| 少妇 在线观看| 精品一区二区三卡| 欧美日韩一区二区视频在线观看视频在线 | 久久久久精品久久久久真实原创| 国产精品爽爽va在线观看网站| 日本一二三区视频观看| av线在线观看网站| 欧美区成人在线视频| 欧美日韩在线观看h| 亚洲精品国产成人久久av| 老司机影院成人| 国产精品久久久久久精品古装| 亚洲av中文字字幕乱码综合| 午夜福利高清视频| 国产亚洲最大av| 在线免费十八禁| 精品人妻一区二区三区麻豆| 欧美日韩综合久久久久久| 国产一区二区在线观看日韩| 色播亚洲综合网| 特大巨黑吊av在线直播| 黄色一级大片看看| 国产精品av视频在线免费观看| 天美传媒精品一区二区| 欧美日韩亚洲高清精品| 精品酒店卫生间| 国产 一区精品| 国产精品精品国产色婷婷| 最近2019中文字幕mv第一页| 欧美日本视频| 亚洲熟女精品中文字幕| 亚洲欧美日韩卡通动漫| 久久久久久久久久久丰满| 亚洲最大成人中文| 国产精品av视频在线免费观看| 久久6这里有精品| 亚洲精品456在线播放app| 欧美+日韩+精品| 2021天堂中文幕一二区在线观| 久久久精品欧美日韩精品| 少妇人妻精品综合一区二区| 久久亚洲国产成人精品v| 国产欧美另类精品又又久久亚洲欧美| 一本一本综合久久| 精品久久久久久久人妻蜜臀av| 国产女主播在线喷水免费视频网站| 免费不卡的大黄色大毛片视频在线观看| 美女内射精品一级片tv| 国产亚洲av片在线观看秒播厂| 看十八女毛片水多多多| 26uuu在线亚洲综合色| 精品少妇久久久久久888优播| 欧美3d第一页| 日韩国内少妇激情av| 国产精品偷伦视频观看了| 在线观看国产h片| 亚洲精品成人av观看孕妇| 午夜视频国产福利| 国产精品成人在线| 69av精品久久久久久| 在线亚洲精品国产二区图片欧美 | 丰满少妇做爰视频| 又黄又爽又刺激的免费视频.| 成人亚洲欧美一区二区av| 亚洲国产av新网站| 欧美成人a在线观看| 亚洲精品乱码久久久v下载方式| 国产毛片a区久久久久| 精品久久久久久久久亚洲| 69人妻影院| 嘟嘟电影网在线观看| 搞女人的毛片| 搡女人真爽免费视频火全软件| 嫩草影院入口| 精品久久久噜噜| 寂寞人妻少妇视频99o| 国产精品人妻久久久影院| 亚洲av免费高清在线观看| 亚洲在线观看片| 我的老师免费观看完整版| 啦啦啦在线观看免费高清www| 大香蕉97超碰在线| 精品久久久噜噜| 欧美精品一区二区大全| 18禁在线播放成人免费| 亚洲图色成人| 91久久精品电影网| 青青草视频在线视频观看| 国产精品久久久久久精品古装| 亚洲在久久综合| 97人妻精品一区二区三区麻豆| 69人妻影院| 亚洲不卡免费看| 欧美最新免费一区二区三区| 国产黄a三级三级三级人| 人妻少妇偷人精品九色| 日韩成人伦理影院| 国产成人91sexporn| 午夜老司机福利剧场| tube8黄色片| 在线看a的网站| 国产黄a三级三级三级人| 99热6这里只有精品| 亚洲精品一二三| 国产午夜精品久久久久久一区二区三区| 一级毛片久久久久久久久女| 亚洲图色成人| 91午夜精品亚洲一区二区三区| 激情五月婷婷亚洲| 午夜精品国产一区二区电影 | 久久久久久久精品精品| 欧美高清性xxxxhd video| 波野结衣二区三区在线| 亚洲欧洲日产国产| 又爽又黄无遮挡网站| 久久久久国产网址| 成人国产av品久久久| 大话2 男鬼变身卡| 国产综合精华液| 女的被弄到高潮叫床怎么办| 在线看a的网站| 国产亚洲最大av| 超碰97精品在线观看| 黄色配什么色好看| 七月丁香在线播放| 一级黄片播放器| 亚洲,欧美,日韩| 26uuu在线亚洲综合色| 丰满少妇做爰视频| 日韩成人伦理影院| 美女国产视频在线观看| 少妇人妻精品综合一区二区| 欧美激情久久久久久爽电影| 亚洲av福利一区| 少妇 在线观看| 日本熟妇午夜| 久久久久久久久大av| 日韩亚洲欧美综合| 伊人久久精品亚洲午夜| 亚洲欧美成人综合另类久久久| 国语对白做爰xxxⅹ性视频网站| 久久精品熟女亚洲av麻豆精品| 亚洲精品日韩在线中文字幕| 一区二区三区免费毛片| 日韩视频在线欧美| eeuss影院久久| 国语对白做爰xxxⅹ性视频网站| 秋霞伦理黄片| 一区二区av电影网| 51国产日韩欧美| 搞女人的毛片| 高清av免费在线| 啦啦啦啦在线视频资源| 亚洲第一区二区三区不卡| 亚洲国产欧美人成| 日日啪夜夜爽| 午夜福利高清视频| 欧美xxxx黑人xx丫x性爽| 国产免费又黄又爽又色| 亚洲成人中文字幕在线播放| 下体分泌物呈黄色| 日韩国内少妇激情av| 久久久久久久久大av| 午夜爱爱视频在线播放| 国产成人freesex在线| 精品一区二区免费观看| 天堂俺去俺来也www色官网| 一个人看的www免费观看视频| 国产成年人精品一区二区| 免费黄色在线免费观看| 三级男女做爰猛烈吃奶摸视频| 国产黄a三级三级三级人| 婷婷色av中文字幕| 1000部很黄的大片| 国产黄片视频在线免费观看| 日韩电影二区| 搡女人真爽免费视频火全软件| 热99国产精品久久久久久7| 午夜免费男女啪啪视频观看| 免费不卡的大黄色大毛片视频在线观看| 亚洲精品成人av观看孕妇| 久久精品综合一区二区三区| 国产日韩欧美亚洲二区| 精品人妻视频免费看| 国语对白做爰xxxⅹ性视频网站| 赤兔流量卡办理| 婷婷色综合大香蕉| 亚洲成人久久爱视频| 亚洲国产日韩一区二区| 久久久精品94久久精品| 99热这里只有精品一区| 91久久精品电影网| 18禁裸乳无遮挡免费网站照片| 久热这里只有精品99| 亚洲熟女精品中文字幕| 久久久色成人| 欧美最新免费一区二区三区| 国产综合精华液| 丝袜喷水一区| 26uuu在线亚洲综合色| 在线 av 中文字幕| 一个人看的www免费观看视频| 精品久久国产蜜桃| 国产 一区 欧美 日韩| 亚洲精品视频女| 在线观看免费高清a一片| 国产欧美日韩精品一区二区| 99热网站在线观看| 韩国av在线不卡| 免费av不卡在线播放| 欧美另类一区| av在线老鸭窝| 在线观看一区二区三区| 美女高潮的动态| 美女脱内裤让男人舔精品视频| 久久ye,这里只有精品| 又爽又黄a免费视频| 国产极品天堂在线| 99久久精品国产国产毛片| 久久久久久久久久成人| 精品久久国产蜜桃| 国产一区有黄有色的免费视频| 国产精品成人在线| 国产美女午夜福利| 亚洲电影在线观看av| 偷拍熟女少妇极品色| 日本一本二区三区精品| 成人国产麻豆网| 久久精品夜色国产| 麻豆久久精品国产亚洲av| 一区二区三区四区激情视频| 亚洲人成网站在线观看播放| 国产精品人妻久久久影院| 欧美成人精品欧美一级黄| 交换朋友夫妻互换小说| 97热精品久久久久久| 国产精品人妻久久久久久| 精品一区二区免费观看| 女的被弄到高潮叫床怎么办| 国产精品偷伦视频观看了| 亚洲最大成人手机在线| 国产精品一区二区三区四区免费观看| 久久久久久久午夜电影| 亚洲在线观看片| 99热国产这里只有精品6| 午夜爱爱视频在线播放| 亚洲成人av在线免费| 亚洲最大成人av| 丝袜喷水一区| 99热网站在线观看| 男人狂女人下面高潮的视频| 亚洲精品视频女| 最近手机中文字幕大全| 人妻制服诱惑在线中文字幕| 一级毛片久久久久久久久女| 久久这里有精品视频免费| 日韩制服骚丝袜av| 女的被弄到高潮叫床怎么办| av播播在线观看一区| 大香蕉97超碰在线| 国产av码专区亚洲av| 精品少妇久久久久久888优播| 成人欧美大片| 啦啦啦在线观看免费高清www| 熟妇人妻不卡中文字幕| 亚洲熟女精品中文字幕| 国产亚洲一区二区精品| 男女边摸边吃奶| 精品久久久精品久久久| 国产精品.久久久| 噜噜噜噜噜久久久久久91| 国产精品麻豆人妻色哟哟久久| 精品久久久久久久久亚洲| 亚洲精品第二区| 九九在线视频观看精品| 嫩草影院入口| 网址你懂的国产日韩在线| 我要看日韩黄色一级片| 亚洲三级黄色毛片| 爱豆传媒免费全集在线观看| 国产乱人偷精品视频| 国产午夜精品久久久久久一区二区三区| 男人爽女人下面视频在线观看| 成人免费观看视频高清| 亚洲色图综合在线观看| 伊人久久精品亚洲午夜| 午夜亚洲福利在线播放| 日韩电影二区| 一级片'在线观看视频| 尤物成人国产欧美一区二区三区| 国产精品无大码| 狂野欧美白嫩少妇大欣赏| 国产午夜福利久久久久久| 六月丁香七月| 色综合色国产| 青青草视频在线视频观看| 80岁老熟妇乱子伦牲交| 亚洲内射少妇av| 中文在线观看免费www的网站| 日韩伦理黄色片| 久久精品国产亚洲网站| 亚洲av国产av综合av卡| 最近2019中文字幕mv第一页| 国产乱人视频| 99久国产av精品国产电影| 国产毛片a区久久久久| 免费大片18禁| 色5月婷婷丁香| a级毛片免费高清观看在线播放| 又黄又爽又刺激的免费视频.| 99久久精品热视频| 欧美成人午夜免费资源| 日韩不卡一区二区三区视频在线| 99热这里只有精品一区| 免费观看a级毛片全部| 亚洲精品成人av观看孕妇| 亚洲精品aⅴ在线观看| 国语对白做爰xxxⅹ性视频网站| 色综合色国产| av卡一久久| 日韩,欧美,国产一区二区三区| 听说在线观看完整版免费高清| 久久久精品免费免费高清| 一本—道久久a久久精品蜜桃钙片 精品乱码久久久久久99久播 | 国产女主播在线喷水免费视频网站| 亚洲综合精品二区| 精品国产露脸久久av麻豆| 男男h啪啪无遮挡| 伊人久久精品亚洲午夜| 亚洲欧美日韩卡通动漫| 女人久久www免费人成看片| 69人妻影院| 国产精品99久久久久久久久| 少妇裸体淫交视频免费看高清| 看黄色毛片网站| 亚洲国产欧美人成| 亚洲人成网站在线观看播放| 有码 亚洲区| 免费少妇av软件| 99久久中文字幕三级久久日本| 内地一区二区视频在线| 精品国产三级普通话版| 熟妇人妻不卡中文字幕| 日韩伦理黄色片| 亚洲av不卡在线观看| 日本与韩国留学比较| 99热全是精品| 婷婷色麻豆天堂久久| 国产美女午夜福利| 国产永久视频网站| 午夜激情福利司机影院| 只有这里有精品99| 婷婷色av中文字幕| 少妇丰满av| 亚洲精品国产av蜜桃| 黄片wwwwww| 极品教师在线视频| 99热国产这里只有精品6| 欧美日韩亚洲高清精品| 亚洲欧美成人综合另类久久久| 亚洲成人久久爱视频| 欧美精品一区二区大全| 午夜激情福利司机影院| 国产精品成人在线| 亚洲av不卡在线观看| 黄片wwwwww| 成人亚洲精品av一区二区| 26uuu在线亚洲综合色| 中文字幕制服av| 日本午夜av视频| 晚上一个人看的免费电影| 哪个播放器可以免费观看大片| 美女视频免费永久观看网站| 免费播放大片免费观看视频在线观看| 精品亚洲乱码少妇综合久久| 爱豆传媒免费全集在线观看| 成人一区二区视频在线观看| 一级毛片电影观看| 国产毛片在线视频| 一二三四中文在线观看免费高清| 欧美最新免费一区二区三区| 午夜老司机福利剧场| 熟女电影av网| 在线 av 中文字幕| 亚洲精品乱码久久久久久按摩| 国产中年淑女户外野战色| 亚洲激情五月婷婷啪啪| 99热这里只有是精品在线观看| 久久99蜜桃精品久久| 欧美丝袜亚洲另类| 免费观看a级毛片全部| 亚洲国产成人一精品久久久| 一区二区av电影网| tube8黄色片| 午夜激情久久久久久久| 人妻 亚洲 视频| 夫妻午夜视频| 成人午夜精彩视频在线观看| 一级毛片久久久久久久久女| 色综合色国产| 婷婷色综合www| 在线看a的网站| 乱系列少妇在线播放| 亚洲精品视频女| 建设人人有责人人尽责人人享有的 | 成人亚洲欧美一区二区av| 一本久久精品| 永久免费av网站大全| 水蜜桃什么品种好| 欧美日韩在线观看h| 晚上一个人看的免费电影| 久久久久精品久久久久真实原创| 老师上课跳d突然被开到最大视频| 免费不卡的大黄色大毛片视频在线观看| 精品久久久噜噜| 国产精品三级大全| 日韩在线高清观看一区二区三区| 最近中文字幕高清免费大全6| 久久久久国产网址| 插阴视频在线观看视频| 两个人的视频大全免费| 麻豆乱淫一区二区| 欧美日韩精品成人综合77777| 午夜精品国产一区二区电影 | 国产精品久久久久久久久免| 国产伦精品一区二区三区视频9| 国产大屁股一区二区在线视频| 亚洲av福利一区| 赤兔流量卡办理| 久久综合国产亚洲精品| 久久女婷五月综合色啪小说 | 成年版毛片免费区| 日本一二三区视频观看| 91午夜精品亚洲一区二区三区| 韩国高清视频一区二区三区| 黄片wwwwww| 中文字幕人妻熟人妻熟丝袜美| 欧美精品国产亚洲| 中国美白少妇内射xxxbb| 日本爱情动作片www.在线观看| 久久女婷五月综合色啪小说 | 成人亚洲精品一区在线观看 | 人妻系列 视频| av国产免费在线观看| 伊人久久国产一区二区| 啦啦啦在线观看免费高清www| 少妇的逼水好多| 精品少妇久久久久久888优播| 亚洲av二区三区四区| 婷婷色综合www| 久久热精品热| 亚洲精品456在线播放app| 亚洲国产av新网站| 精品视频人人做人人爽| 亚洲国产欧美人成| 亚洲国产日韩一区二区| 亚洲欧美清纯卡通| 午夜福利在线在线| 蜜桃久久精品国产亚洲av| 99久久中文字幕三级久久日本| 一级毛片aaaaaa免费看小| 欧美一区二区亚洲| 欧美日韩综合久久久久久| av女优亚洲男人天堂| 国产精品伦人一区二区| 亚洲欧洲国产日韩| 国产免费又黄又爽又色| 久久综合国产亚洲精品| 色网站视频免费| 久久久色成人| 亚洲欧美精品专区久久| 久久精品国产亚洲av天美| 各种免费的搞黄视频| 亚洲人成网站在线观看播放| 91久久精品国产一区二区成人| 国产老妇女一区| 麻豆成人午夜福利视频| 久久国产乱子免费精品| videos熟女内射| 精品久久国产蜜桃| 免费大片黄手机在线观看| 精品久久久久久久末码| 亚洲精品aⅴ在线观看| 欧美3d第一页| 色吧在线观看| 小蜜桃在线观看免费完整版高清| 亚洲精品久久午夜乱码| 免费观看在线日韩| 韩国高清视频一区二区三区| 免费av毛片视频| 80岁老熟妇乱子伦牲交| 色播亚洲综合网| 我的老师免费观看完整版| 欧美丝袜亚洲另类| 99热网站在线观看| 免费看不卡的av| 免费观看无遮挡的男女| 人妻夜夜爽99麻豆av| 成人鲁丝片一二三区免费| 少妇人妻久久综合中文| 80岁老熟妇乱子伦牲交| 91精品伊人久久大香线蕉| 我的老师免费观看完整版| 亚洲成人一二三区av| 一级毛片 在线播放| 国产成人午夜福利电影在线观看| 性插视频无遮挡在线免费观看| 我的老师免费观看完整版| 女人被狂操c到高潮| av免费在线看不卡| 人人妻人人看人人澡| 一个人观看的视频www高清免费观看| 欧美xxⅹ黑人| 免费看日本二区| 亚洲精品色激情综合| 国产毛片在线视频| 午夜福利视频1000在线观看| 国产精品福利在线免费观看| 亚洲天堂国产精品一区在线| 国产视频首页在线观看| 欧美最新免费一区二区三区| 免费黄色在线免费观看| www.色视频.com| 午夜视频国产福利| 亚洲高清免费不卡视频| 亚洲av国产av综合av卡| 国产乱人偷精品视频| 狂野欧美激情性xxxx在线观看| 网址你懂的国产日韩在线| 亚洲成人久久爱视频| 成人国产麻豆网| 久热这里只有精品99| 午夜福利视频精品| 久久精品人妻少妇| 国产在线一区二区三区精| 亚洲精品国产成人久久av| 免费av不卡在线播放| 亚洲精品第二区| 国产精品久久久久久精品电影| 国产午夜精品一二区理论片| 欧美成人一区二区免费高清观看| 男女边摸边吃奶| 久久精品国产鲁丝片午夜精品| 国产亚洲最大av| 大陆偷拍与自拍| 久久99热6这里只有精品| 一本—道久久a久久精品蜜桃钙片 精品乱码久久久久久99久播 | 夜夜看夜夜爽夜夜摸| 欧美成人一区二区免费高清观看| 亚洲精品中文字幕在线视频 | 亚洲欧美清纯卡通| 国产爱豆传媒在线观看| 国产亚洲一区二区精品| 免费观看在线日韩| 亚洲人与动物交配视频| 国产精品偷伦视频观看了| 欧美极品一区二区三区四区| 亚洲精品乱久久久久久| 精品一区二区三卡| 久久久精品欧美日韩精品| 成人高潮视频无遮挡免费网站| 国产成人免费无遮挡视频| 久久女婷五月综合色啪小说 | 免费看不卡的av| 色视频在线一区二区三区| 大陆偷拍与自拍| 91久久精品国产一区二区成人| 天堂中文最新版在线下载 | 97在线视频观看| 国产成人一区二区在线| 日日摸夜夜添夜夜爱| 精品国产一区二区三区久久久樱花 | 国产爽快片一区二区三区| 国产精品人妻久久久影院| 国产精品人妻久久久久久| 色视频在线一区二区三区| av天堂中文字幕网| 在现免费观看毛片| 午夜福利在线在线| 午夜精品国产一区二区电影 | 中文乱码字字幕精品一区二区三区| 神马国产精品三级电影在线观看| 久久久久久久大尺度免费视频| av国产免费在线观看| 中文在线观看免费www的网站| 久久久久久国产a免费观看| 国产探花极品一区二区| 男女边吃奶边做爰视频| 人人妻人人看人人澡| 校园人妻丝袜中文字幕| 内射极品少妇av片p| 插阴视频在线观看视频| 亚洲精品亚洲一区二区| 久久久久久久国产电影| 五月玫瑰六月丁香| 免费看不卡的av| 王馨瑶露胸无遮挡在线观看| 身体一侧抽搐| 麻豆精品久久久久久蜜桃| 亚洲欧美精品专区久久| 亚洲av在线观看美女高潮| 中文精品一卡2卡3卡4更新| 亚洲精华国产精华液的使用体验| 男男h啪啪无遮挡| 我的老师免费观看完整版| 亚洲精品中文字幕在线视频 | 热re99久久精品国产66热6| 久久久久精品久久久久真实原创| 精品久久久噜噜| 亚洲最大成人av| 免费大片黄手机在线观看| 毛片女人毛片| 亚洲精品乱码久久久久久按摩|