• <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.

    av线在线观看网站| 热re99久久精品国产66热6| 99热网站在线观看| 肉色欧美久久久久久久蜜桃| 在线精品无人区一区二区三| 巨乳人妻的诱惑在线观看| 国产亚洲av片在线观看秒播厂| 老熟女久久久| 99国产极品粉嫩在线观看| 老汉色∧v一级毛片| 国产精品久久久久久精品电影小说| 欧美+亚洲+日韩+国产| av视频免费观看在线观看| 90打野战视频偷拍视频| 中文字幕人妻熟女乱码| 久久久久久久精品精品| 成人av一区二区三区在线看 | 一级片免费观看大全| 一级片免费观看大全| 纵有疾风起免费观看全集完整版| 免费在线观看完整版高清| 欧美日韩亚洲高清精品| 99re6热这里在线精品视频| 亚洲全国av大片| 一级黄色大片毛片| 在线 av 中文字幕| 亚洲欧美一区二区三区久久| 在线观看免费高清a一片| 精品国产乱子伦一区二区三区 | 亚洲男人天堂网一区| 啪啪无遮挡十八禁网站| 亚洲综合色网址| 国精品久久久久久国模美| av不卡在线播放| 狠狠精品人妻久久久久久综合| 久热这里只有精品99| 成在线人永久免费视频| 亚洲av男天堂| 日日爽夜夜爽网站| 欧美激情久久久久久爽电影 | 亚洲国产精品成人久久小说| 十分钟在线观看高清视频www| av福利片在线| 日本av免费视频播放| 中亚洲国语对白在线视频| 母亲3免费完整高清在线观看| 欧美日韩一级在线毛片| 大片电影免费在线观看免费| 老司机福利观看| 日韩大片免费观看网站| 国产成人精品久久二区二区91| 两个人免费观看高清视频| 国产在线观看jvid| 欧美精品高潮呻吟av久久| 99国产极品粉嫩在线观看| 久久久国产欧美日韩av| 久久中文字幕一级| 大码成人一级视频| 一本久久精品| av在线老鸭窝| 中文字幕另类日韩欧美亚洲嫩草| 别揉我奶头~嗯~啊~动态视频 | 五月天丁香电影| 啦啦啦在线免费观看视频4| 最新在线观看一区二区三区| 麻豆av在线久日| 黄频高清免费视频| 黄频高清免费视频| 两性夫妻黄色片| 国产日韩一区二区三区精品不卡| 啦啦啦啦在线视频资源| 精品一品国产午夜福利视频| 高清视频免费观看一区二区| 亚洲成av片中文字幕在线观看| 丝袜喷水一区| 亚洲国产欧美日韩在线播放| 777久久人妻少妇嫩草av网站| 欧美日韩国产mv在线观看视频| 看免费av毛片| 美女福利国产在线| 韩国精品一区二区三区| 一个人免费在线观看的高清视频 | 欧美乱码精品一区二区三区| 新久久久久国产一级毛片| 国产精品九九99| 亚洲五月婷婷丁香| 操出白浆在线播放| 国产精品偷伦视频观看了| 丁香六月天网| a 毛片基地| 午夜福利影视在线免费观看| 久久 成人 亚洲| 99国产精品99久久久久| 9191精品国产免费久久| 老司机深夜福利视频在线观看 | 韩国精品一区二区三区| 91成人精品电影| 国产欧美日韩一区二区三区在线| 国产日韩欧美视频二区| 两性午夜刺激爽爽歪歪视频在线观看 | 欧美 日韩 精品 国产| 高清视频免费观看一区二区| 精品国产一区二区久久| 两性午夜刺激爽爽歪歪视频在线观看 | 午夜福利在线观看吧| 少妇裸体淫交视频免费看高清 | 亚洲国产精品一区二区三区在线| 捣出白浆h1v1| 最新的欧美精品一区二区| 别揉我奶头~嗯~啊~动态视频 | a 毛片基地| 午夜91福利影院| 久久精品亚洲熟妇少妇任你| 两个人免费观看高清视频| 最近最新免费中文字幕在线| 一级毛片女人18水好多| 亚洲av成人不卡在线观看播放网 | 亚洲精品国产色婷婷电影| 可以免费在线观看a视频的电影网站| 亚洲美女黄色视频免费看| 啦啦啦 在线观看视频| 国产精品久久久人人做人人爽| h视频一区二区三区| 1024香蕉在线观看| 亚洲,欧美精品.| 免费观看av网站的网址| 99热网站在线观看| 少妇 在线观看| 国产野战对白在线观看| 人妻一区二区av| 午夜免费观看性视频| 飞空精品影院首页| 亚洲一区中文字幕在线| 又黄又粗又硬又大视频| 精品福利观看| 婷婷色av中文字幕| 极品少妇高潮喷水抽搐| 国内毛片毛片毛片毛片毛片| www.熟女人妻精品国产| 999久久久国产精品视频| 国产成人精品在线电影| 日韩一卡2卡3卡4卡2021年| 久久99热这里只频精品6学生| 两性午夜刺激爽爽歪歪视频在线观看 | 在线观看免费高清a一片| 王馨瑶露胸无遮挡在线观看| 不卡av一区二区三区| 欧美在线黄色| 亚洲一卡2卡3卡4卡5卡精品中文| 老司机亚洲免费影院| 国产主播在线观看一区二区| 免费在线观看黄色视频的| 精品久久久精品久久久| 精品乱码久久久久久99久播| 日韩人妻精品一区2区三区| 热99re8久久精品国产| 国产区一区二久久| 国产一区二区三区av在线| 人成视频在线观看免费观看| 亚洲欧美精品自产自拍| 欧美日韩成人在线一区二区| 在线观看免费午夜福利视频| 国产麻豆69| 国产人伦9x9x在线观看| 妹子高潮喷水视频| 成年美女黄网站色视频大全免费| 精品第一国产精品| videos熟女内射| 欧美日韩亚洲综合一区二区三区_| 最黄视频免费看| 日本猛色少妇xxxxx猛交久久| 性少妇av在线| 中亚洲国语对白在线视频| 大型av网站在线播放| 制服诱惑二区| 色综合欧美亚洲国产小说| 50天的宝宝边吃奶边哭怎么回事| 手机成人av网站| 亚洲av美国av| 爱豆传媒免费全集在线观看| 热99国产精品久久久久久7| 黑人巨大精品欧美一区二区蜜桃| 在线观看免费视频网站a站| 国产一区有黄有色的免费视频| 少妇粗大呻吟视频| 一二三四在线观看免费中文在| 国产无遮挡羞羞视频在线观看| 中文字幕制服av| 亚洲欧美色中文字幕在线| 美女脱内裤让男人舔精品视频| 高清av免费在线| 一区二区三区激情视频| 亚洲九九香蕉| 淫妇啪啪啪对白视频 | 亚洲欧美精品自产自拍| 伦理电影免费视频| 欧美激情久久久久久爽电影 | 国产又色又爽无遮挡免| 涩涩av久久男人的天堂| 精品人妻在线不人妻| 精品国产乱码久久久久久男人| 亚洲国产中文字幕在线视频| 老司机影院成人| av在线老鸭窝| 久久人妻熟女aⅴ| 国产精品亚洲av一区麻豆| 国产1区2区3区精品| 夜夜骑夜夜射夜夜干| 啦啦啦中文免费视频观看日本| 一级毛片女人18水好多| 国产男人的电影天堂91| 热99re8久久精品国产| 日韩大码丰满熟妇| 超碰成人久久| 日韩一区二区三区影片| 精品一区二区三卡| 俄罗斯特黄特色一大片| 久久精品久久久久久噜噜老黄| 国产精品免费大片| 久久国产亚洲av麻豆专区| 丰满饥渴人妻一区二区三| 美女午夜性视频免费| 国产精品香港三级国产av潘金莲| 深夜精品福利| 18在线观看网站| 久久久久精品国产欧美久久久 | 999久久久精品免费观看国产| 免费在线观看完整版高清| 久久九九热精品免费| 久久国产精品人妻蜜桃| 色婷婷久久久亚洲欧美| 欧美精品亚洲一区二区| 中文字幕制服av| 美女午夜性视频免费| 一个人免费在线观看的高清视频 | 青草久久国产| 制服人妻中文乱码| 国产亚洲一区二区精品| 黄片小视频在线播放| 男女之事视频高清在线观看| 女人久久www免费人成看片| 丝袜美腿诱惑在线| 老鸭窝网址在线观看| 亚洲人成电影免费在线| 成年女人毛片免费观看观看9 | 国产精品九九99| 免费观看a级毛片全部| 欧美另类一区| 青青草视频在线视频观看| 夫妻午夜视频| 久久久久国产一级毛片高清牌| 亚洲情色 制服丝袜| 精品国产国语对白av| 精品亚洲成a人片在线观看| 亚洲人成电影观看| 9191精品国产免费久久| 天天躁狠狠躁夜夜躁狠狠躁| 黑丝袜美女国产一区| 亚洲av国产av综合av卡| 久久精品人人爽人人爽视色| 女人久久www免费人成看片| 亚洲精品日韩在线中文字幕| 2018国产大陆天天弄谢| 国产成人免费无遮挡视频| 欧美av亚洲av综合av国产av| 满18在线观看网站| 国产精品亚洲av一区麻豆| 免费在线观看日本一区| 人人澡人人妻人| 咕卡用的链子| 亚洲精品成人av观看孕妇| 国产在线一区二区三区精| 国产欧美日韩一区二区三 | 欧美日韩视频精品一区| 国产精品99久久99久久久不卡| 亚洲精品粉嫩美女一区| 中国国产av一级| 国产日韩欧美在线精品| 日本撒尿小便嘘嘘汇集6| 国产精品国产三级国产专区5o| 日本精品一区二区三区蜜桃| av福利片在线| 热re99久久国产66热| 欧美日韩黄片免| 亚洲欧美激情在线| av在线老鸭窝| 久久久国产精品麻豆| 午夜精品久久久久久毛片777| 美女扒开内裤让男人捅视频| 国产日韩欧美视频二区| 老司机影院毛片| 一本—道久久a久久精品蜜桃钙片| 亚洲欧美清纯卡通| 老熟妇仑乱视频hdxx| 亚洲精品久久成人aⅴ小说| 女人久久www免费人成看片| 国产成人精品在线电影| 又大又爽又粗| 法律面前人人平等表现在哪些方面 | 狠狠精品人妻久久久久久综合| 国产欧美日韩精品亚洲av| 最新的欧美精品一区二区| 99久久精品国产亚洲精品| av网站在线播放免费| svipshipincom国产片| 欧美精品啪啪一区二区三区 | 天天躁狠狠躁夜夜躁狠狠躁| 男女免费视频国产| 精品一区二区三区av网在线观看 | 每晚都被弄得嗷嗷叫到高潮| 一二三四社区在线视频社区8| a级毛片在线看网站| 美女大奶头黄色视频| 亚洲国产av新网站| 啦啦啦视频在线资源免费观看| 纯流量卡能插随身wifi吗| 人人妻人人澡人人爽人人夜夜| 国产极品粉嫩免费观看在线| 亚洲精品国产av成人精品| 日韩欧美一区视频在线观看| 色精品久久人妻99蜜桃| 欧美一级毛片孕妇| 亚洲精品av麻豆狂野| 一二三四在线观看免费中文在| 国产av一区二区精品久久| 男女之事视频高清在线观看| 国产成人免费观看mmmm| 欧美精品啪啪一区二区三区 | 中文字幕高清在线视频| 久久久久久免费高清国产稀缺| 亚洲国产精品999| 日韩人妻精品一区2区三区| 法律面前人人平等表现在哪些方面 | 免费在线观看影片大全网站| 欧美精品高潮呻吟av久久| av视频免费观看在线观看| 最近中文字幕2019免费版| 欧美人与性动交α欧美精品济南到| 一级毛片精品| 另类精品久久| 欧美激情极品国产一区二区三区| 久久天躁狠狠躁夜夜2o2o| 一区二区三区四区激情视频| 男女床上黄色一级片免费看| av天堂久久9| 午夜免费观看性视频| 777米奇影视久久| 国产亚洲av片在线观看秒播厂| 精品熟女少妇八av免费久了| 欧美国产精品va在线观看不卡| 国产欧美日韩一区二区三 | 亚洲av国产av综合av卡| 一本—道久久a久久精品蜜桃钙片| 777米奇影视久久| 老熟妇乱子伦视频在线观看 | 他把我摸到了高潮在线观看 | 国产成人影院久久av| 色视频在线一区二区三区| 精品亚洲乱码少妇综合久久| 欧美精品一区二区大全| 亚洲人成电影观看| 国产国语露脸激情在线看| 菩萨蛮人人尽说江南好唐韦庄| 色播在线永久视频| 狠狠精品人妻久久久久久综合| 亚洲精品国产精品久久久不卡| 老司机福利观看| 在线观看一区二区三区激情| 老司机福利观看| 午夜影院在线不卡| 一本—道久久a久久精品蜜桃钙片| 精品人妻1区二区| 久久这里只有精品19| www.自偷自拍.com| 99久久精品国产亚洲精品| 久久精品国产a三级三级三级| 99热国产这里只有精品6| 蜜桃国产av成人99| 在线观看免费午夜福利视频| 亚洲av成人不卡在线观看播放网 | 丝瓜视频免费看黄片| 99久久国产精品久久久| 午夜视频精品福利| 久久这里只有精品19| 国产深夜福利视频在线观看| av片东京热男人的天堂| 男女午夜视频在线观看| 一区二区av电影网| 日韩欧美国产一区二区入口| 日本撒尿小便嘘嘘汇集6| 97在线人人人人妻| 日韩中文字幕视频在线看片| 亚洲伊人色综图| tocl精华| 国产老妇伦熟女老妇高清| 亚洲第一青青草原| 少妇人妻久久综合中文| 亚洲欧美日韩高清在线视频 | 大片免费播放器 马上看| 嫩草影视91久久| 久久久国产精品麻豆| 日本vs欧美在线观看视频| 欧美人与性动交α欧美软件| 欧美日韩亚洲综合一区二区三区_| 精品国产国语对白av| 国产av精品麻豆| 国产成人免费无遮挡视频| 亚洲av日韩精品久久久久久密| 久久 成人 亚洲| 国产一区二区激情短视频 | 在线观看免费视频网站a站| 99久久国产精品久久久| 欧美激情久久久久久爽电影 | 久久这里只有精品19| 亚洲av成人一区二区三| 免费黄频网站在线观看国产| 久久天躁狠狠躁夜夜2o2o| 欧美少妇被猛烈插入视频| av欧美777| 国产成人啪精品午夜网站| 另类亚洲欧美激情| 亚洲欧美日韩高清在线视频 | 19禁男女啪啪无遮挡网站| 一级片'在线观看视频| 18禁黄网站禁片午夜丰满| 国产成人欧美在线观看 | 国产成人精品久久二区二区91| 高清在线国产一区| 亚洲精品国产av蜜桃| 久久免费观看电影| 搡老乐熟女国产| 国产精品一二三区在线看| 亚洲欧美一区二区三区黑人| 亚洲国产精品一区三区| 97在线人人人人妻| 欧美日韩视频精品一区| 免费在线观看影片大全网站| 菩萨蛮人人尽说江南好唐韦庄| 国产亚洲av片在线观看秒播厂| 婷婷丁香在线五月| 国产精品国产av在线观看| 欧美日韩亚洲国产一区二区在线观看 | 精品国产国语对白av| 日韩电影二区| 中文字幕人妻熟女乱码| 国产精品熟女久久久久浪| 日本黄色日本黄色录像| 免费久久久久久久精品成人欧美视频| 婷婷色av中文字幕| 中亚洲国语对白在线视频| 国产精品一区二区免费欧美 | 日韩大片免费观看网站| 亚洲国产欧美日韩在线播放| a级毛片在线看网站| 国产免费视频播放在线视频| 91麻豆精品激情在线观看国产 | 国产精品影院久久| 欧美一级毛片孕妇| 亚洲精品一二三| 脱女人内裤的视频| 精品国产一区二区三区久久久樱花| 夜夜骑夜夜射夜夜干| 伊人亚洲综合成人网| 丰满饥渴人妻一区二区三| 久久天躁狠狠躁夜夜2o2o| 亚洲va日本ⅴa欧美va伊人久久 | 亚洲精品久久久久久婷婷小说| 美国免费a级毛片| 久久久欧美国产精品| 操美女的视频在线观看| 国产精品免费视频内射| 国产一区二区三区在线臀色熟女 | 午夜成年电影在线免费观看| 好男人电影高清在线观看| 一区二区三区精品91| 韩国高清视频一区二区三区| 日本wwww免费看| 啦啦啦免费观看视频1| 亚洲欧洲精品一区二区精品久久久| 99国产精品免费福利视频| 热re99久久国产66热| 国产一区二区激情短视频 | 久久中文看片网| 国产97色在线日韩免费| 午夜两性在线视频| 国产亚洲精品久久久久5区| 亚洲欧洲精品一区二区精品久久久| 国产深夜福利视频在线观看| 亚洲精华国产精华精| 国产1区2区3区精品| 久久精品熟女亚洲av麻豆精品| 亚洲国产av影院在线观看| 国产成人欧美| 国产极品粉嫩免费观看在线| 国产又爽黄色视频| 精品一区二区三区av网在线观看 | 国产在线视频一区二区| 青青草视频在线视频观看| 80岁老熟妇乱子伦牲交| 在线av久久热| 999久久久国产精品视频| 视频在线观看一区二区三区| 91精品伊人久久大香线蕉| 人妻 亚洲 视频| 日本vs欧美在线观看视频| 欧美激情久久久久久爽电影 | 男人爽女人下面视频在线观看| 亚洲av国产av综合av卡| 欧美+亚洲+日韩+国产| 色综合欧美亚洲国产小说| 亚洲av美国av| 日韩免费高清中文字幕av| 日韩人妻精品一区2区三区| 亚洲精品成人av观看孕妇| 亚洲av欧美aⅴ国产| 一边摸一边抽搐一进一出视频| 成人免费观看视频高清| 中国国产av一级| 青春草视频在线免费观看| 国产成人av教育| 国产无遮挡羞羞视频在线观看| 欧美精品一区二区大全| 午夜福利影视在线免费观看| 人人妻人人澡人人爽人人夜夜| 一区二区三区四区激情视频| 久久久欧美国产精品| 国产亚洲午夜精品一区二区久久| 亚洲欧美色中文字幕在线| 久久久国产一区二区| www.999成人在线观看| 亚洲欧美清纯卡通| 91国产中文字幕| 国产野战对白在线观看| 亚洲国产精品一区三区| 十八禁网站网址无遮挡| 亚洲 欧美一区二区三区| 美女高潮喷水抽搐中文字幕| 久久久久国产一级毛片高清牌| 午夜免费成人在线视频| 国产一区二区三区av在线| 97人妻天天添夜夜摸| 成年美女黄网站色视频大全免费| 国产免费一区二区三区四区乱码| 人人妻人人爽人人添夜夜欢视频| 黑人猛操日本美女一级片| 成年动漫av网址| 精品久久蜜臀av无| 丁香六月天网| 桃花免费在线播放| 精品一品国产午夜福利视频| 国产免费视频播放在线视频| 国产精品 国内视频| 纯流量卡能插随身wifi吗| 2018国产大陆天天弄谢| 在线天堂中文资源库| 一区二区三区乱码不卡18| 亚洲欧美一区二区三区黑人| 99国产精品一区二区三区| 肉色欧美久久久久久久蜜桃| 国精品久久久久久国模美| a级片在线免费高清观看视频| 可以免费在线观看a视频的电影网站| 国产深夜福利视频在线观看| av福利片在线| 999精品在线视频| 亚洲五月婷婷丁香| 日韩一区二区三区影片| 久久久久国内视频| 啦啦啦啦在线视频资源| 亚洲色图 男人天堂 中文字幕| 亚洲成人免费av在线播放| 青青草视频在线视频观看| 51午夜福利影视在线观看| 飞空精品影院首页| 国产精品免费大片| 一二三四社区在线视频社区8| 黄色毛片三级朝国网站| 精品久久久久久久毛片微露脸 | 人妻人人澡人人爽人人| 女性生殖器流出的白浆| 一区二区三区四区激情视频| 亚洲久久久国产精品| 高清在线国产一区| 久久亚洲精品不卡| 久久久久精品国产欧美久久久 | 欧美日韩亚洲综合一区二区三区_| 美国免费a级毛片| 最近最新中文字幕大全免费视频| 欧美日韩亚洲高清精品| 欧美国产精品一级二级三级| 国产av精品麻豆| 一区二区三区激情视频| 777米奇影视久久| 女人久久www免费人成看片| 侵犯人妻中文字幕一二三四区| 亚洲免费av在线视频| avwww免费| 青青草视频在线视频观看| 岛国毛片在线播放| 真人做人爱边吃奶动态| 成人亚洲精品一区在线观看| 丝袜美足系列| 久久国产精品大桥未久av| 欧美 亚洲 国产 日韩一| av网站免费在线观看视频| 久久久久网色| 一级,二级,三级黄色视频| 侵犯人妻中文字幕一二三四区| 午夜福利在线观看吧| 亚洲熟女毛片儿| 汤姆久久久久久久影院中文字幕| 成年人午夜在线观看视频| 日韩视频一区二区在线观看| 丁香六月欧美| 香蕉丝袜av|