• <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| 人人澡人人妻人| 国内精品宾馆在线| 97在线人人人人妻| 波野结衣二区三区在线| 草草在线视频免费看| 国产精品欧美亚洲77777| 免费av中文字幕在线| 国产精品三级大全| 色吧在线观看| 日韩三级伦理在线观看| 我要看黄色一级片免费的| 成年av动漫网址| 十八禁网站网址无遮挡 | 99九九在线精品视频 | 免费不卡的大黄色大毛片视频在线观看| 国产综合精华液| 久久久久国产精品人妻一区二区| 国产午夜精品一二区理论片| 国产免费一级a男人的天堂| 日本vs欧美在线观看视频 | 亚洲国产日韩一区二区| 色网站视频免费| 夜夜看夜夜爽夜夜摸| 永久免费av网站大全| 亚洲精品久久久久久婷婷小说| 亚洲欧美精品专区久久| 搡女人真爽免费视频火全软件| 国产一区二区在线观看av| 国产伦精品一区二区三区视频9| 最新中文字幕久久久久| 日本vs欧美在线观看视频 | 午夜影院在线不卡| 赤兔流量卡办理| 亚洲国产精品999| 亚洲久久久国产精品| 一个人看视频在线观看www免费| 人妻制服诱惑在线中文字幕| 美女脱内裤让男人舔精品视频| 亚洲激情五月婷婷啪啪| 精华霜和精华液先用哪个| 国产精品女同一区二区软件| 国产精品蜜桃在线观看| 亚洲av二区三区四区| 69精品国产乱码久久久| 91精品伊人久久大香线蕉| 亚洲国产成人一精品久久久| 老司机影院毛片| 亚洲欧洲国产日韩| videossex国产| 内地一区二区视频在线| 色网站视频免费| 国产成人91sexporn| 美女内射精品一级片tv| 国产一区有黄有色的免费视频| 99视频精品全部免费 在线| 国产精品秋霞免费鲁丝片| 日日爽夜夜爽网站| 精品亚洲成国产av| 天天操日日干夜夜撸| 精品午夜福利在线看| 美女cb高潮喷水在线观看| tube8黄色片| 在线天堂最新版资源| 色吧在线观看| 久久久久精品性色| 亚洲丝袜综合中文字幕| 日日啪夜夜撸| 免费大片18禁| 女的被弄到高潮叫床怎么办| 欧美激情极品国产一区二区三区 | 精品久久久久久电影网| 夜夜骑夜夜射夜夜干| 乱码一卡2卡4卡精品| 国产精品一区二区在线观看99| 日韩伦理黄色片| 国精品久久久久久国模美| 晚上一个人看的免费电影| 国产一区二区三区综合在线观看 | 蜜臀久久99精品久久宅男| 国产亚洲最大av| 亚洲欧美日韩另类电影网站| 在线精品无人区一区二区三| 国产伦精品一区二区三区视频9| 久久午夜福利片| 高清在线视频一区二区三区| 中文天堂在线官网| 丰满迷人的少妇在线观看| 国产精品一二三区在线看| a级片在线免费高清观看视频| 最新的欧美精品一区二区| 青春草亚洲视频在线观看| 人妻系列 视频| 亚洲国产精品999| 日本av免费视频播放| 亚洲情色 制服丝袜| 久久精品久久久久久久性| 亚洲,欧美,日韩| 日本色播在线视频| 嫩草影院入口| 亚洲第一av免费看| 91午夜精品亚洲一区二区三区| 多毛熟女@视频| 少妇人妻精品综合一区二区| 日本黄色日本黄色录像| 亚洲av男天堂| 最近2019中文字幕mv第一页| 欧美激情极品国产一区二区三区 | 日韩中字成人| 精品少妇内射三级| 涩涩av久久男人的天堂| 人妻夜夜爽99麻豆av| 国产亚洲午夜精品一区二区久久| 欧美3d第一页| 欧美最新免费一区二区三区| 午夜久久久在线观看| 麻豆乱淫一区二区| 国产在线视频一区二区| 一本色道久久久久久精品综合| 最近手机中文字幕大全| 日韩在线高清观看一区二区三区| 免费播放大片免费观看视频在线观看| 国产淫片久久久久久久久| 国产欧美日韩精品一区二区| 日韩伦理黄色片| 精品久久久精品久久久| 蜜桃在线观看..| 国产精品无大码| 高清不卡的av网站| 久久久国产欧美日韩av| av.在线天堂| 日韩精品有码人妻一区| 有码 亚洲区| 国产精品一区二区在线不卡| av国产精品久久久久影院| 久久国内精品自在自线图片| 午夜视频国产福利| 成人国产麻豆网| 亚洲欧美清纯卡通| 色5月婷婷丁香| 国产一区二区在线观看日韩| 国产精品嫩草影院av在线观看| 在线观看免费视频网站a站| 天天躁夜夜躁狠狠久久av| 亚洲欧洲精品一区二区精品久久久 | av卡一久久| 中文在线观看免费www的网站| 天天操日日干夜夜撸| 男女边吃奶边做爰视频| 国产精品熟女久久久久浪| 中文字幕免费在线视频6| a级一级毛片免费在线观看| 大陆偷拍与自拍| 国产精品偷伦视频观看了| av又黄又爽大尺度在线免费看| 校园人妻丝袜中文字幕| 少妇熟女欧美另类| 国产成人精品一,二区| 岛国毛片在线播放| 2022亚洲国产成人精品| 国产亚洲午夜精品一区二区久久| 国产老妇伦熟女老妇高清| 熟妇人妻不卡中文字幕| 国产在线男女| 亚洲欧美一区二区三区黑人 | 久久人人爽av亚洲精品天堂| 亚洲精品日本国产第一区| 纯流量卡能插随身wifi吗| 国产伦精品一区二区三区四那| 国产av精品麻豆| 在线观看免费日韩欧美大片 | 在线亚洲精品国产二区图片欧美 | 美女国产视频在线观看| 一级黄片播放器| 亚洲中文av在线| 最近最新中文字幕免费大全7| 在线 av 中文字幕| 国产欧美亚洲国产| 日本猛色少妇xxxxx猛交久久| 婷婷色av中文字幕| av福利片在线观看| 丰满乱子伦码专区| 国产深夜福利视频在线观看| 蜜臀久久99精品久久宅男| 99久久综合免费| 大又大粗又爽又黄少妇毛片口| 国产精品成人在线| 午夜老司机福利剧场| 在线观看免费视频网站a站| 欧美日韩视频精品一区| 女性被躁到高潮视频| a级片在线免费高清观看视频| 亚洲欧美成人综合另类久久久| 中文字幕精品免费在线观看视频 | 欧美97在线视频| 日本与韩国留学比较| 亚洲国产最新在线播放| 国产毛片在线视频| 成年美女黄网站色视频大全免费 | 少妇人妻精品综合一区二区| 夜夜看夜夜爽夜夜摸| 成人18禁高潮啪啪吃奶动态图 | 午夜免费观看性视频| 3wmmmm亚洲av在线观看| 久久久久网色| 亚洲成色77777| 午夜久久久在线观看| 特大巨黑吊av在线直播| 我的老师免费观看完整版| 美女xxoo啪啪120秒动态图| 亚洲av在线观看美女高潮| 久久久亚洲精品成人影院| 91在线精品国自产拍蜜月| 一个人免费看片子| 婷婷色综合大香蕉| 国产美女午夜福利| 国产精品一区二区在线观看99| 欧美少妇被猛烈插入视频| 久久久久久久国产电影| 国产免费一级a男人的天堂| 久久精品久久精品一区二区三区| 日韩视频在线欧美| 色婷婷av一区二区三区视频| 欧美3d第一页| 久久久久久久久久久久大奶| 亚洲国产最新在线播放| 九草在线视频观看| 国国产精品蜜臀av免费| 老女人水多毛片| 蜜臀久久99精品久久宅男| 欧美日韩国产mv在线观看视频| 蜜桃在线观看..| 十分钟在线观看高清视频www | 男女免费视频国产| videossex国产| 国产精品人妻久久久久久| 日日撸夜夜添| 亚洲精品国产av蜜桃| 天天操日日干夜夜撸| 黄色毛片三级朝国网站 | 人人妻人人添人人爽欧美一区卜| 大又大粗又爽又黄少妇毛片口| 看非洲黑人一级黄片| 久久久久精品性色| 国产精品一区二区在线观看99| 亚洲精品国产色婷婷电影| videos熟女内射| 欧美日韩在线观看h| 男人爽女人下面视频在线观看| 日本黄色日本黄色录像| 18禁在线播放成人免费| 少妇被粗大的猛进出69影院 | 国产熟女欧美一区二区| 在线观看免费高清a一片| 久久毛片免费看一区二区三区| 久久久久久久久大av| 久久99热6这里只有精品| 99精国产麻豆久久婷婷| 亚洲色图综合在线观看| 伦精品一区二区三区| 午夜激情久久久久久久| 精品人妻一区二区三区麻豆| 免费播放大片免费观看视频在线观看| 男人狂女人下面高潮的视频| freevideosex欧美| 欧美精品亚洲一区二区| 亚洲第一区二区三区不卡| 色吧在线观看| 午夜福利影视在线免费观看| 嘟嘟电影网在线观看| 99热这里只有精品一区| 99久久人妻综合| 精品一区二区三卡| 国产精品不卡视频一区二区| 国产欧美亚洲国产| 三级国产精品欧美在线观看| 亚洲激情五月婷婷啪啪| 精品国产乱码久久久久久小说| 色婷婷av一区二区三区视频| 黑人猛操日本美女一级片| 久久 成人 亚洲| 下体分泌物呈黄色| 久久精品国产亚洲av天美| 熟女av电影| 少妇人妻一区二区三区视频| 国语对白做爰xxxⅹ性视频网站| 观看免费一级毛片| av网站免费在线观看视频| 王馨瑶露胸无遮挡在线观看| 成人亚洲精品一区在线观看| 少妇猛男粗大的猛烈进出视频| 人人妻人人看人人澡| 欧美精品国产亚洲| 欧美一级a爱片免费观看看| 精品一区二区免费观看| 精品99又大又爽又粗少妇毛片| 亚洲激情五月婷婷啪啪| 国产黄色视频一区二区在线观看| 亚洲国产精品一区二区三区在线| 春色校园在线视频观看| 黑丝袜美女国产一区| 黄色怎么调成土黄色| 久久久精品免费免费高清| 99久久中文字幕三级久久日本| 国产91av在线免费观看| 精华霜和精华液先用哪个| 青春草国产在线视频| 国产成人精品无人区| 午夜老司机福利剧场| 国产精品.久久久| 综合色丁香网| 久久精品国产亚洲av涩爱| 午夜久久久在线观看| 成人美女网站在线观看视频| 国产精品国产三级国产av玫瑰| 纯流量卡能插随身wifi吗| 欧美精品一区二区免费开放| 免费看av在线观看网站| 国产一区二区三区av在线| 久久人人爽人人片av| 国产精品一区二区性色av| 插阴视频在线观看视频| 夜夜看夜夜爽夜夜摸| 国模一区二区三区四区视频| 99视频精品全部免费 在线| 国产精品久久久久久av不卡| 五月开心婷婷网| 人人澡人人妻人| 午夜免费观看性视频| 精品午夜福利在线看| 精品亚洲成国产av| 爱豆传媒免费全集在线观看| 国产精品麻豆人妻色哟哟久久| 日本vs欧美在线观看视频 | a级毛片在线看网站| 亚洲一区二区三区欧美精品| 搡老乐熟女国产| 丝瓜视频免费看黄片| 国内少妇人妻偷人精品xxx网站| 一级毛片久久久久久久久女| 特大巨黑吊av在线直播| 中文天堂在线官网| 看非洲黑人一级黄片| 亚洲精品日本国产第一区| 欧美激情国产日韩精品一区| 色吧在线观看| 免费看日本二区| 日韩av不卡免费在线播放| 国模一区二区三区四区视频| 亚洲国产精品999| 午夜激情久久久久久久| 丝瓜视频免费看黄片| 中文天堂在线官网| 免费观看性生交大片5| 青春草视频在线免费观看| 一区二区av电影网| 熟女人妻精品中文字幕| 免费大片黄手机在线观看| 日韩中文字幕视频在线看片| 99热6这里只有精品| 国产精品一区二区三区四区免费观看| 成人特级av手机在线观看| 高清在线视频一区二区三区| 国产熟女午夜一区二区三区 | 麻豆成人午夜福利视频| 看免费成人av毛片| 九色成人免费人妻av| 亚洲精品456在线播放app| 国产有黄有色有爽视频| 国产亚洲最大av| 一个人免费看片子| 亚洲美女视频黄频| 啦啦啦啦在线视频资源| 精品国产一区二区三区久久久樱花| 激情五月婷婷亚洲| 少妇精品久久久久久久| 最新中文字幕久久久久| 一级黄片播放器| 夫妻性生交免费视频一级片| 一级二级三级毛片免费看| 成人午夜精彩视频在线观看| 免费人妻精品一区二区三区视频| 精品少妇内射三级| 亚洲人成网站在线观看播放| 极品人妻少妇av视频| 免费观看的影片在线观看| kizo精华| 国产精品免费大片| 亚洲国产毛片av蜜桃av| www.色视频.com| 亚洲av综合色区一区| 亚洲成色77777| 我要看日韩黄色一级片| 日本欧美视频一区| freevideosex欧美| 王馨瑶露胸无遮挡在线观看| 国产精品99久久久久久久久| 免费久久久久久久精品成人欧美视频 | 亚洲精品国产av蜜桃| 蜜臀久久99精品久久宅男| 乱系列少妇在线播放| 国产高清不卡午夜福利| 9色porny在线观看| 欧美97在线视频| 国产极品粉嫩免费观看在线 | 国产高清国产精品国产三级| 晚上一个人看的免费电影| 在线天堂最新版资源| 色视频在线一区二区三区| 国产色爽女视频免费观看| 街头女战士在线观看网站| 插阴视频在线观看视频| 免费看光身美女| 黑人猛操日本美女一级片| av黄色大香蕉| 国产精品福利在线免费观看| 日韩亚洲欧美综合| 亚洲国产日韩一区二区| 多毛熟女@视频| 精品亚洲成a人片在线观看| 欧美日韩视频精品一区| 欧美日韩av久久| 亚洲成人av在线免费| 久久久久久久精品精品| 成人亚洲精品一区在线观看| 热99国产精品久久久久久7| 在线观看av片永久免费下载| 亚洲av综合色区一区| 国产极品粉嫩免费观看在线 | 另类亚洲欧美激情| 9色porny在线观看| 人人妻人人澡人人爽人人夜夜| 亚洲综合精品二区| 日韩av不卡免费在线播放| 韩国高清视频一区二区三区| 精品久久久久久久久亚洲| 国产乱人偷精品视频| 国产精品国产三级国产av玫瑰| 男人添女人高潮全过程视频| 一级二级三级毛片免费看| 九草在线视频观看| 国产精品久久久久成人av| 国产精品一区二区性色av| 亚洲欧美日韩另类电影网站| 久久精品国产自在天天线| 久久97久久精品| 黄色配什么色好看| 亚洲综合精品二区| 亚洲精品自拍成人| 三上悠亚av全集在线观看 | 久久久欧美国产精品| 在线观看美女被高潮喷水网站| 女性生殖器流出的白浆| 热99国产精品久久久久久7| 亚洲精品自拍成人| 亚洲精品国产av蜜桃| 中国三级夫妇交换| 亚洲人成网站在线观看播放| 91在线精品国自产拍蜜月| 精品国产一区二区三区久久久樱花| 在线 av 中文字幕| 欧美精品一区二区免费开放| 亚洲国产精品国产精品| 国产亚洲午夜精品一区二区久久| 亚洲久久久国产精品| 国产成人免费无遮挡视频| 免费观看在线日韩| 最近2019中文字幕mv第一页| 精品久久久久久久久亚洲| 日本91视频免费播放| 欧美国产精品一级二级三级 | 一区二区三区乱码不卡18| 国产成人一区二区在线| 国产高清有码在线观看视频| 成人亚洲欧美一区二区av| 男人和女人高潮做爰伦理| 亚洲精品久久久久久婷婷小说| 午夜精品国产一区二区电影| 亚州av有码| 欧美老熟妇乱子伦牲交| 久久午夜福利片| 91久久精品电影网| 国产无遮挡羞羞视频在线观看| 看非洲黑人一级黄片| 涩涩av久久男人的天堂| 国产亚洲最大av| 国产精品一区二区三区四区免费观看| 女性被躁到高潮视频| 黄片无遮挡物在线观看| 在线观看人妻少妇| 亚洲国产精品一区三区| 大陆偷拍与自拍| 51国产日韩欧美| av福利片在线| 国产成人精品一,二区| 国产精品免费大片| 久久久欧美国产精品| 一级a做视频免费观看| 久久精品国产亚洲av涩爱| 亚洲色图综合在线观看| 国产有黄有色有爽视频| 国产美女午夜福利| 久久国产乱子免费精品| 日本欧美视频一区| 校园人妻丝袜中文字幕| 永久网站在线| 99热全是精品| 日日撸夜夜添| 在线播放无遮挡| av国产精品久久久久影院| 午夜福利在线观看免费完整高清在| a级毛色黄片| 日本vs欧美在线观看视频 | 亚洲欧美日韩卡通动漫| 亚洲欧美一区二区三区黑人 | 日韩精品有码人妻一区| h视频一区二区三区| 久久97久久精品| 国产精品一区二区性色av| 一级av片app| 日韩中文字幕视频在线看片| 国产伦在线观看视频一区| 亚洲va在线va天堂va国产| 国产精品国产三级专区第一集| 乱人伦中国视频| 一级毛片电影观看| 欧美最新免费一区二区三区| 99热6这里只有精品| www.色视频.com| 免费看不卡的av| av国产久精品久网站免费入址| 美女大奶头黄色视频| 晚上一个人看的免费电影| 又粗又硬又长又爽又黄的视频| 国产在线视频一区二区| 国产片特级美女逼逼视频| 婷婷色综合大香蕉| 一级毛片aaaaaa免费看小| 免费观看无遮挡的男女| 在线观看av片永久免费下载| 亚洲图色成人| 国产视频首页在线观看| 大陆偷拍与自拍| 青春草国产在线视频| 中国三级夫妇交换| 国产精品99久久久久久久久| 色婷婷久久久亚洲欧美| 欧美bdsm另类| av在线老鸭窝| 最近中文字幕高清免费大全6| 两个人的视频大全免费| 免费黄网站久久成人精品| 丰满乱子伦码专区| 人体艺术视频欧美日本| 热re99久久精品国产66热6| 久久久久久伊人网av| 人妻一区二区av| 国产精品熟女久久久久浪| 五月伊人婷婷丁香| 日本欧美视频一区| 黄色毛片三级朝国网站 | 免费黄网站久久成人精品| 成人特级av手机在线观看| 亚洲成人av在线免费| 日本黄色片子视频| 国产成人免费观看mmmm| 99re6热这里在线精品视频| 在线 av 中文字幕| 亚洲欧美成人综合另类久久久| 另类亚洲欧美激情| 春色校园在线视频观看| 亚洲天堂av无毛| 在线观看免费视频网站a站| 亚洲高清免费不卡视频| 亚洲av国产av综合av卡| 国产色爽女视频免费观看| 久久精品久久精品一区二区三区| 国产永久视频网站| 精品人妻一区二区三区麻豆| 日韩成人av中文字幕在线观看| 边亲边吃奶的免费视频| 亚洲精品一区蜜桃| 久久人人爽av亚洲精品天堂| 午夜福利网站1000一区二区三区| 高清毛片免费看| 伦理电影免费视频| 国产精品久久久久久久电影| 欧美 日韩 精品 国产| 一边亲一边摸免费视频| 欧美最新免费一区二区三区| 欧美丝袜亚洲另类| 国产男女内射视频| h日本视频在线播放| 亚洲精品第二区| 各种免费的搞黄视频| 亚洲在久久综合| 日韩 亚洲 欧美在线| 亚洲av.av天堂| 国产一区二区三区综合在线观看 | 一本一本综合久久| av福利片在线| 亚洲精品一二三| 高清欧美精品videossex| 日韩伦理黄色片| 欧美老熟妇乱子伦牲交| 国产老妇伦熟女老妇高清| 亚洲怡红院男人天堂| 亚洲久久久国产精品| 欧美精品亚洲一区二区| 丰满人妻一区二区三区视频av| 日本黄色日本黄色录像| 国产中年淑女户外野战色| 国产男人的电影天堂91| 久久国产精品大桥未久av | 一本色道久久久久久精品综合|