A Framework for Enhancing Privacy and Anonymity in Blockchain-Enabled IoT Devices

With the increase in IoT(Internet of Things)devices comes an inherent challenge of security.In the world today,privacy is the prime concern of every individual.Preserving one’s privacy and keeping anonymity throughout the system is a desired functionality that does not come without inevitable trade-offs like scalability and increased complexity and is always exceedingly difficult to manage.The challenge is keeping confidentiality and continuing to make the person innominate throughout the system.To address this,we present our proposed architecture where we manage IoT devices using blockchain technology.Our proposed architecture works on and off blockchain integrated with the closed-circuit television(CCTV)security camera fixed at the rental property.In this framework,the CCTV security camera feed is redirected towards the owner and renter based on the smart contract conditions.One entity(owner or renter)can see the CCTV security camera feed at one time.There is no third-party dependence except for the CCTV security camera deployment phase.Our contributions include the proposition of framework architecture,a novel smart contract algorithm,and the modification to the ring signatures leveraging an existing cryptographic technique.Analyses are made based on different systems’security and key management areas.In an empirical study,our proposed algorithm performed better in key generation,proof generation,and verification times.By comparing similar existing schemes,we have shown the proposed architectures’advantages.Until now,we have developed this system for a specific area in the real world.However,this system is scalable and applicable to other areas like healthcare monitoring systems,which is part of our future work.

An Efficient Three-Party Authenticated Key Exchange Procedure Using Chebyshev Chaotic Maps with Client Anonymity

Internet of Things(IoT)applications can be found in various industry areas,including critical infrastructure and healthcare,and IoT is one of several technological developments.As a result,tens of billions or possibly hundreds of billions of devices will be linked together.These smart devices will be able to gather data,process it,and even come to decisions on their own.Security is the most essential thing in these situations.In IoT infrastructure,authenticated key exchange systems are crucial for preserving client and data privacy and guaranteeing the security of data-in-transit(e.g.,via client identification and provision of secure communication).It is still challenging to create secure,authenticated key exchange techniques.The majority of the early authenticated key agreement procedure depended on computationally expensive and resource-intensive pairing,hashing,or modular exponentiation processes.The focus of this paper is to propose an efficient three-party authenticated key exchange procedure(AKEP)using Chebyshev chaotic maps with client anonymity that solves all the problems mentioned above.The proposed three-party AKEP is protected from several attacks.The proposed three-party AKEP can be used in practice for mobile communications and pervasive computing applications,according to statistical experiments and low processing costs.To protect client identification when transferring data over an insecure public network,our three-party AKEP may also offer client anonymity.Finally,the presented procedure offers better security features than the procedures currently available in the literature.

Novel Block Chain Technique for Data Privacy and Access Anonymity in Smart Healthcare

The Internet of Things (IoT) and Cloud computing are gaining popularity due to their numerous advantages, including the efficient utilization of internetand computing resources. In recent years, many more IoT applications have beenextensively used. For instance, Healthcare applications execute computations utilizing the user’s private data stored on cloud servers. However, the main obstaclesfaced by the extensive acceptance and usage of these emerging technologies aresecurity and privacy. Moreover, many healthcare data management system applications have emerged, offering solutions for distinct circumstances. But still, theexisting system has issues with specific security issues, privacy-preserving rate,information loss, etc. Hence, the overall system performance is reduced significantly. A unique blockchain-based technique is proposed to improve anonymityin terms of data access and data privacy to overcome the above-mentioned issues.Initially, the registration phase is done for the device and the user. After that, theGeo-Location and IP Address values collected during registration are convertedinto Hash values using Adler 32 hashing algorithm, and the private and publickeys are generated using the key generation centre. Then the authentication is performed through login. The user then submits a request to the blockchain server,which redirects the request to the associated IoT device in order to obtain thesensed IoT data. The detected data is anonymized in the device and stored inthe cloud server using the Linear Scaling based Rider Optimization algorithmwith integrated KL Anonymity (LSR-KLA) approach. After that, the Time-stamp-based Public and Private Key Schnorr Signature (TSPP-SS) mechanismis used to permit the authorized user to access the data, and the blockchain servertracks the entire transaction. The experimental findings showed that the proposedLSR-KLA and TSPP-SS technique provides better performance in terms of higherprivacy-preserving rate, lower information loss, execution time, and Central Processing Unit (CPU) usage than the existing techniques. Thus, the proposed method allows for better data privacy in the smart healthcare network.

The Effect of Perceived Anonymity on Online Transgressions:The Moderating Role of Moral Excuses

With the development of science and technology,the use of the Internet is becoming more and more widespread.However,with the popularity of the Internet,some problems have gradually surfaced.The anonymity of Internet use has become a breeding ground for many acts that are contrary to public decency,and this study is conducted against this background.This study explored the impact of perceived anonymity on online transgressions and investigated the moderating effect of moral excuses.A total of 414 subjects,210 males and 204 females,participated in this experimental survey.The SPSS data analysis concluded that perceived anonymity played a significant positive predictive role on online deviance(p<0.01),and the moderating role of moral excuses was not significant.This study will be conducive to the better implementation of the action of clearing cyberspace and to the regulation of public behaviour in cyberspace.

Clustered trajectories anonymity in wireless sensor networks

This paper proposes a clustered trajectories anonymity scheme （CTA） that enhances the kano nymity scheme to provide the intended level of source location privacy in mobile event monitoring when a global attacker is assumed. CTA applies isomorphic property of rotation to create traces of the fake sources distributions which are similar to those of the real sources. Thus anonymity of each trajectory and that of the clustered is achieved. In addition, location kdiversity is achieved by dis tributing fake sources around the base station. To reduce the time delay, tree rooted at the base sta tion is constructed to overlap part of the beacon interval of the nodes in the hierarchy. Both the ana lytical analysis and the simulation results prove that proved energy overhead and time delay. our scheme provides perfect anonymity with improved energy overhead and time delay.

Achieve Personalized Anonymity Through Query Blocks Exchanging

In cyberspace security,the privacy in location-based services(LBSs) becomes more critical. In previous solutions,a trusted third party(TTP) was usually employed to provide disturbance or obfuscation,but it may become the single point of failure or service bottleneck. In order to cope with this drawback,we focus on another important class,establishing anonymous group through short-range communication to achieve k-anonymity with collaborative users. Along with the analysis of existing algorithms,we found users in the group must share the same maximum anonymity degree,and they could not ease the process of preservation in a lower one. To cope with this problem,we proposed a random-QBE algorithm to put up with personalized anonymity in user collaboration algorithms,and this algorithm could preserve both query privacy and location privacy. Then we studied the attacks from passive and active adversaries and used entropy to measure user's privacy level. Finally,experimental evaluations further verify its effectiveness and efficiency.

To name or not to name？ An overview of the social and ethical issues raised by removing anonymity from sperm donors

The aim of this paper is to focus on the ethical issues raised by the removal of anonymity from sperm donors. The increasing currency of a ＇right to genetic truth＇ is clearly visible in the drive to revise the legislation on donor anonymity in Western and European countries. The ethical debate is polarized between the ＇right to privacy＇ of the donor or parent and the ＇right to know＇ of the prospective child. However, it is evident that religious, social and cultural attitudes have an overarching impact on attitudes towards sperm donation generally and anonymity specifically. In Asian countries, the social and cultural heritage is hugely diverse and different from those of the West. This review considers the research exploring the complexity of ethical issues informing this debate, and argues that parent＇s decisions to reveal donor insemination origins to their children are highly complex and relate to a range of social and cultural attitudes that have not been addressed within the policy to remove anonymity from sperm donors.

A New Anonymity Model for Privacy-Preserving Data Publishing

Privacy-preserving data publishing （PPDP） is one of the hot issues in the field of the network security. The existing PPDP technique cannot deal with generality attacks, which explicitly contain the sensitivity attack and the similarity attack. This paper proposes a novel model, （w,γ, k）-anonymity, to avoid generality attacks on both cases of numeric and categorical attributes. We show that the optimal （w, γ, k）-anonymity problem is NP-hard and conduct the Top-down Local recoding （TDL） algorithm to implement the model. Our experiments validate the improvement of our model with real data.

AABN: Anonymity Assessment Model Based on Bayesian Network With Application to Blockchain

Blockchain is a technology that uses community validation to keep synchronized the content of ledgers replicated across multiple users,which is the underlying technology of digital currency like bitcoin.The anonymity of blockchain has caused widespread concern.In this paper,we put forward AABN,an Anonymity Assessment model based on Bayesian Network.Firstly,we investigate and analyze the anonymity assessment techniques,and focus on typical anonymity assessment schemes.Then the related concepts involved in the assessment model are introduced and the model construction process is described in detail.Finally,the anonymity in the MIX anonymous network is quantitatively evaluated using the methods of accurate reasoning and approximate reasoning respectively,and the anonymity assessment experiments under different output strategies of the MIX anonymous network are analyzed.

A Sensor Anonymity Enhancement Scheme Based on Pseudonym for Clustered Wireless Sensor Network

Security problem is an important issue for Wireless Sensor Network.The paper focuses on the privacy protection of WSN applications.An anonymity enhancement tactic based on pseudonym mechanism is presented for clustered Wireless Sensor Network,which provides anonymity for both the sensors within a cluster and the cluster head nodes.Simulation experiments are launched through NS2 platform to validate the anonymity performance.The theoretical analysis and empirical study imply that the proposed scheme based on pseudonym can protect the privacies of both the sensor nodes and the cluster head nodes.The work is valuable and the experimental results are convincible.

Trajectory Rotation Privacy Protection Algorithm Based on <i>k</i>Anonymity

The frequent use of location query services in location-based services will come out a large amount of space-time data related to users. Attackers infer information of location or track based on these rich background knowledge. Therefore, aiming at the problem of trajectory privacy, the context adds instant traffic monitoring based on user behavior patterns, trajectory similarity and other background information. According to the idea of k anonymity, proposed a method combined with traffic condition to protect the trajectory privacy. First, the user randomly selects a time point of the real trajectory to rotate to generate dummy trajectory, and then repeat the above process on the real trajectory and dummy trajectory. Up to the generation of k &minus;1 dummy trajectory, and according to the actual road conditions and trajectory leakage probability, traversing dummy trajectory to adjust. Finally, it is further proved through experiments that the method will be more efficient and protect privacy well.

An Improved User Authentication and Key Agreement Scheme Providing User Anonymity

When accessing remote services over public networks, a user authentication mechanism is required because these activities are executed in an insecure communication environment. Recently, Wang et al. proposed an authentication and key agreement scheme preserving the privacy of secret keys and providing user anonymity. Later, Chang et al. indicated that their scheme suffers from two security flaws. First, it cannot resist DoS （denial-of-service） attack because the indicators for the next session are not consistent. Second, the user password may be modified by a malicious attacker because no authentication mechanism is applied before the user password is updated. To eliminate the security flaws and preserve the advantages of Wang et aL＇s scheme, we propose an improvement in this paper.

An Anonymity Scheme Based on Pseudonym in P2P Networks

In this paper, we proposed an anonymity scheme based on pseudonym where peers are motivated not to share their identity. Compared with precious scheme such as RuP （Reputation using Pseudonyms）, our scheme can reduce its overhead and minimize the trusted center＇s involvement.

A NEW ANONYMITY CONTROLLED E-CASH SCHEME

E-cash is a type of very important electronic payment systems. The complete anonymity of E-cash can be used for criminal activities, so E-cash should be anonymity controlled.Moreover, Elliptic Curve Cryptography(ECC) has been regard as the mainstream of current public cryptography . In this paper, a new anonymity controlled E-cash scheme based on ECC for the first time and using a new technology-one-time key pairs digital signature is designed, and its security and efficiency are analyzed. In our scheme, the coin tracing and owner tracing can be implemented.

(r,QI)-Transform：Reversible Data Anonymity Based on Numeric Type of Data in Outsourced Database

An outsource database is a database service provided by cloud computing companies.Using the outsource database can reduce the hardware and software＇s cost and also get more efficient and reliable data processing capacity.However,the outsource database still has some challenges.If the service provider does not have sufficient confidence,there is the possibility of data leakage.The data may has user＇s privacy,so data leakage may cause data privacy leak.Based on this factor,to protect the privacy of data in the outsource database becomes very important.In the past,scholars have proposed k-anonymity to protect data privacy in the database.It lets data become anonymous to avoid data privacy leak.But k-anonymity has some problems,it is irreversible,and easier to be attacked by homogeneity attack and background knowledge attack.Later on,scholars have proposed some studies to solve homogeneity attack and background knowledge attack.But their studies still cannot recover back to the original data.In this paper,we propose a data anonymity method.It can be reversible and also prevent those two attacks.Our study is based on the proposed r-transform.It can be used on the numeric type of attributes in the outsource database.In the experiment,we discussed the time required to anonymize and recover data.Furthermore,we investigated the defense against homogeneous attack and background knowledge attack.At the end,we summarized the proposed method and future researches.

Anonymity control in electronic check systems

Electronic check systems, as one of electronic payment systems, are more desirable than other electronic cash systems. In the system, only a single cheek is used to pay any price that is not more than the face value. The main problem in check systems is to design an efficient refund mechanism that makes refired cheeks undistinguished from initial checks during payment and deposit. The problem of anonymity control also called fairmess is also an important issue in check systelns. All check systems yet are unconditional anonymity that opens the door to misuse for crime such as laundering and blackmailing. In this paper, the notion of anonylnity revocation is introduced to electronic check system for the fitst thne, and a model of fair electronic check system is proposed. An effieient fair online electronic check system with reusable refund is presented. In the system, a passive trustee is elnployed to revoke the anonymity of unhonest users. Moreover, the system solves the reusability problem of refunds thanks to the RSA-based partially signature. The system is efficient and meets all basic security requirements.

Anonymity Effects and Implications in the Virtual Environment: From Crowd to Computer-Mediated Communication

Anonymity, an important feature of computer-mediated communication (CMC), is embedded in this new technology. With the penetration of the Internet in society, many daily activities involve online interactions. Anonymity affects both the task and social aspects of online communication including information exchange, decision making, and relationship development. This review examines the effects of anonymity on human behavior. It outlines how the prior literature has attempted to address this issue and how the Social Identity Deindividuation (SIDE) model has developed as an attempt to tackle this question. More importantly, it discusses a framework describing the multidimensions of anonymity in CMC [1], and subsequently raised five propositions inspired by this framework. Furthermore, using McLeod’s framework, this review evaluates SIDE studies with regard to their anonymity manipulations. This critique reveals possible future research directions for refining the SIDE model and better studying the effect of anonymity in virtual environment.

Dark Web and Its Impact in Online Anonymity and Privacy: A Critical Analysis and Review

The Internet as the whole is a network of multiple computer networks and their massive infrastructure. The web is made up of accessible websites through search engines such as Google, Firefox, etc. and it is known as the Surface Web. The Internet is segmented further in the Deep Web—the content that it is not indexed and cannot access by traditional search engines. Dark Web considers a segment of the Deep Web. It accesses through TOR. Actors within Dark Web websites are anonymous and hidden. Anonymity, privacy and the possibility of non-detection are three factors that are provided by special browser such as TOR and I2P. In this paper, we are going to discuss and provide results about the influence of the Dark Web in different spheres of society. It is given the number of daily anonymous users of the Dark Web (using TOR) in Kosovo as well as in the whole world for a period of time. The influence of hidden services websites is shown and results are gathered from Ahimia and Onion City Dark Web’s search engines. The anonymity is not completely verified on the Dark Web. TOR dedicates to it and has intended to provide anonymous activities. Here are given results about reporting the number of users and in which place(s) they are. The calculation is based on IP addresses according to country codes from where comes the access to them and report numbers in aggregate form. In this way, indirect are represented the Dark Web users. The number of users in anonymous networks on the Dark Web is another key element that is resulted. In such networks, users are calculated through the client requests of directories (by TOR metrics) and the relay list is updated. Indirectly, the number of users is calculated for the anonymous networks.

Tor network anonymity evaluation based on node anonymity

In order to address the shortcomings of traditional anonymity network anonymity evaluation methods,which only analyze from the perspective of the overall network and ignore the attributes of individual nodes,we proposes a dynamic anonymity model based on a self-built anonymous system that combines node attributes,network behavior,and program security monitoring.The anonymity of evaluation nodes is assessed based on stable intervals and behavior baselines defined according to their normal operating status.The anonymity of the network is evaluated using an improved normalized information entropy method that refines anonymity evaluation to the anonymity of each node and expands the dimensionality of evaluation features.This paper compares the effectiveness of our proposed method with static framework information entropy and single indicator methods by evaluating the degree of anonymity provided by a self-built Tor anonymous network under multiple operating scenarios including normal and under attack.Our approach utilizes dynamically changing network anonymity based on multiple anonymous attributes and better reflects the degree of anonymity in anonymous systems.

MLDA:a multi-level k-degree anonymity scheme on directed social network graphs

With the emergence of network-centric data,social network graph publishing is conducive to data analysts to mine the value of social networks,analyze the social behavior of individuals or groups,implement personalized recommendations,and so on.However,published social network graphs are often subject to re-identification attacks from adversaries,which results in the leakage of users’privacy.The-anonymity technology is widely used in the field of graph publishing,which is quite effective to resist re-identification attacks.However,the current researches still exist some issues to be solved:the protection of directed graphs is less concerned than that of undirected graphs;the protection of graph structure is often ignored while achieving the protection of nodes’identities;the same protection is performed for different users,which doesn’t meet the different privacy requirements of users.Therefore,to address the above issues,a multi-level-degree anonymity(MLDA)scheme on directed social network graphs is proposed in this paper.First,node sets with different importance are divided by the firefly algorithm and constrained connectedness upper approximation,and they are performed different-degree anonymity protection to meet the different privacy requirements of users.Second,a new graph anonymity method is proposed,which achieves the addition and removal of edges with the help of fake nodes.In addition,to improve the utility of the anonymized graph,a new edge cost criterion is proposed,which is used to select the most appropriate edge to be removed.Third,to protect the community structure of the original graph as much as possible,fake nodes contained in a same community are merged prior to fake nodes contained in different communities.Experimental results on real datasets show that the newly proposed MLDA scheme is effective to balance the privacy and utility of the anonymized graph.