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Li, Kemeng, Zheng, Dong, Guo, Rui.  2021.  An Anonymous Editable Blockchain Scheme Based on Certificateless Aggregate Signature. 2021 3rd International Conference on Natural Language Processing (ICNLP). :57–67.
Blockchain technology has gradually replaced traditional centralized data storage methods, and provided people reliable data storage services with its decentralized and non-tamperable features. However, the current blockchain data supervision is insufficient and the data cannot be modified once it is on the blockchain, which will cause the blockchain system to face various problems such as illegal information cannot be deleted and breach of smart contract cannot be fixed in time. To address these issues, we propose an anonymous editable blockchain scheme based on the reconstruction of the blockchain structure of the SpaceMint combining with the certificateless aggregate signature algorithm. Users register with their real identities and use pseudonyms in the system to achieve their anonymity. If the number of users who agree to edit meets the threshold, the data on the blockchain can be modified or deleted, and our scheme has the function of accountability for malicious behavior. The security analysis show that the proposed certificateless aggregate signature algorithm enjoys the unforgeability under the adaptive selected message attack. Moreover, the method of setting the threshold of related users is adopted to guarantee the effectiveness and security of editing blockchain data. At last, we evaluate the performance of our certificateless aggregate signature algorithm and related schemes in theoretical analysis and experimental simulation, which demonstrates our scheme is feasible and efficient in storage, bandwidth and computational cost.
Hamouid, Khaled, Omar, Mawloud, Adi, Kamel.  2021.  A Privacy-Preserving Authentication Model Based on Anonymous Certificates in IoT. 2021 Wireless Days (WD). :1–6.
This paper proposes an anonymity based mechanism for providing privacy in IoT environment. Proposed scheme allows IoT entities to anonymously interacting and authenticating with each other, or even proving that they have trustworthy relationship without disclosing their identities. Authentication is based on an anonymous certificates mechanism where interacting IoT entities could unlinkably prove possession of a valid certificate without revealing any incorporated identity-related information, thereby preserving their privacy and thwarting tracking and profiling attacks. Through a security analysis, we demonstrate the reliability of our solution.
Abi Sen, Adnan Ahmed, M Alawfi, Ibrahim Moeed, Aloufi, Hazim Faisal, Bahbouh, Nour Mahmoud, Alsaawy, Yazed.  2021.  Comparison among Cooperation, Anonymity and Cloak Area Approaches for Preserving Privacy of IoT. 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom). :413–416.
As a result of the importance of privacy at present, especially with the modern applications and technologies that have spread in the last decade, many techniques and methods have appeared to preserve privacy and protect users' data from tracking, profiling, or identification. The most popular of these technologies are those which rely on peer-to-peer or third-party cooperation. But, by reviewing a significant portion of existing research articles related to privacy, we find considerable confusion amongst several concepts and ways of protection, such as the concept of cloak area, Anonymizer, cooperation, and Third Party Peers (TTP). In this research, we revisit and review these approaches, which contain an overlap between them to distinguish each one clearly with the help of graphs and to remove their ambiguity. In this way, we shall be able provide a ready-reckoner to those interested in this field to easily differentiate between them and thus work to develop them and provide new methods. In other words, this research seeks to enhance the privacy and security in smart applications and technologies in the IoT and smart city environments.
Buccafurri, Francesco, De Angelis, Vincenzo, Idone, Maria Francesca, Labrini, Cecilia.  2021.  Extending Routes in Tor to Achieve Recipient Anonymity against the Global Adversary. 2021 International Conference on Cyberworlds (CW). :238–245.
Tor is a famous routing overlay network based on the Onion multi-layered encryption to support communication anonymity in a threat model in which some network nodes are malicious. However, Tor does not provide any protection against the global passive adversary. In this threat model, an idea to obtain recipient anonymity, which is enough to have relationship anonymity, is to hide the recipient among a sufficiently large anonymity set. However, this would lead to high latency both in the set-up phase (which has a quadratic cost in the number of involved nodes) and in the successive communication. In this paper, we propose a way to arrange a Tor circuit with a tree-like topology, in which the anonymity set consists of all its nodes, whereas set-up and communication latency depends on the number of the sole branch nodes (which is a small fraction of all the nodes). Basically, the cost goes down from quadratic to linear. Anonymity is obtained by applying a broadcast-based technique for the forward message, and cover traffic (generated by the terminal-chain nodes) plus mixing over branch nodes, for the response.
Mygdalis, Vasileios, Tefas, Anastasios, Pitas, Ioannis.  2021.  Introducing K-Anonymity Principles to Adversarial Attacks for Privacy Protection in Image Classification Problems. 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP). :1–6.
The network output activation values for a given input can be employed to produce a sorted ranking. Adversarial attacks typically generate the least amount of perturbation required to change the classifier label. In that sense, generated adversarial attack perturbation only affects the output in the 1st sorted ranking position. We argue that meaningful information about the adversarial examples i.e., their original labels, is still encoded in the network output ranking and could potentially be extracted, using rule-based reasoning. To this end, we introduce a novel adversarial attack methodology inspired by the K-anonymity principles, that generates adversarial examples that are not only misclassified, but their output sorted ranking spreads uniformly along K different positions. Any additional perturbation arising from the strength of the proposed objectives, is regularized by a visual similarity-based term. Experimental results denote that the proposed approach achieves the optimization goals inspired by K-anonymity with reduced perturbation as well.
Zheng, Shiyuan, Xie, Hong, Lui, John C.S..  2021.  Social Visibility Optimization in OSNs with Anonymity Guarantees: Modeling, Algorithms and Applications. 2021 IEEE 37th International Conference on Data Engineering (ICDE). :2063–2068.
Online social network (OSN) is an ideal venue to enhance one's visibility. This paper considers how a user (called requester) in an OSN selects a small number of available users and invites them as new friends/followers so as to maximize his "social visibility". More importantly, the requester has to do this under the anonymity setting, which means he is not allowed to know the neighborhood information of these available users in the OSN. In this paper, we first develop a mathematical model to quantify the social visibility and formulate the problem of visibility maximization with anonymity guarantee, abbreviated as "VisMAX-A". Then we design an algorithmic framework named as "AdaExp", which adaptively expands the requester's visibility in multiple rounds. In each round of the expansion, AdaExp uses a query oracle with anonymity guarantee to select only one available user. By using probabilistic data structures like the k-minimum values (KMV) sketch, we design an efficient query oracle with anonymity guarantees. We also conduct experiments on real-world social networks and validate the effectiveness of our algorithms.
Deng, Han, Wang, Zhechon, Zhang, Yazhen.  2021.  Overview of Privacy Protection Data Release Anonymity Technology. 2021 7th IEEE Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS). :151–156.
The collection of digital information by governments, companies and individuals creates tremendous opportunities for knowledge and information-based decision-making. Driven by mutual benefit and laws and regulations, there is a need for data exchange and publication between all parties. However, data in its original form usually contains sensitive information about individuals and publishing such data would violate personal privacy. Privacy Protection Data Distribution (PPDP) provides methods and tools to release useful information while protecting data privacy. In recent years, PPDP has received extensive attention from the research community, and many solutions have been proposed for different data release scenarios. How to ensure the availability of data under the premise of protecting user privacy is the core problem to be solved in this field. This paper studies the existing achievements of privacy protection data release anonymity technology, focusing on the existing anonymity technology in three aspects of high-dimensional, high-deficiency, and complex relational data, and analyzes and summarizes them.
Kohlweiss, Markulf, Madathil, Varun, Nayak, Kartik, Scafuro, Alessandra.  2021.  On the Anonymity Guarantees of Anonymous Proof-of-Stake Protocols. 2021 IEEE Symposium on Security and Privacy (SP). :1818–1833.
In proof-of-stake (PoS) blockchains, stakeholders that extend the chain are selected according to the amount of stake they own. In S&P 2019 the "Ouroboros Crypsinous" system of Kerber et al. (and concurrently Ganesh et al. in EUROCRYPT 2019) presented a mechanism that hides the identity of the stakeholder when adding blocks, hence preserving anonymity of stakeholders both during payment and mining in the Ouroboros blockchain. They focus on anonymizing the messages of the blockchain protocol, but suggest that potential identity leaks from the network-layer can be removed as well by employing anonymous broadcast channels.In this work we show that this intuition is flawed. Even ideal anonymous broadcast channels do not suffice to protect the identity of the stakeholder who proposes a block.We make the following contributions. First, we show a formal network-attack against Ouroboros Crypsinous, where the adversary can leverage network delays to distinguish who is the stakeholder that added a block on the blockchain. Second, we abstract the above attack and show that whenever the adversary has control over the network delay – within the synchrony bound – loss of anonymity is inherent for any protocol that provides liveness guarantees. We do so, by first proving that it is impossible to devise a (deterministic) state-machine replication protocol that achieves basic liveness guarantees and better than (1-2f) anonymity at the same time (where f is the fraction of corrupted parties). We then connect this result to the PoS setting by presenting the tagging and reverse tagging attack that allows an adversary, across several executions of the PoS protocol, to learn the stake of a target node, by simply delaying messages for the target. We demonstrate that our assumption on the delaying power of the adversary is realistic by describing how our attack could be mounted over the Zcash blockchain network (even when Tor is used). We conclude by suggesting approaches that can mitigate such attacks.
Zhou, Yitao, Wu, Judong, Zhang, Shengxin.  2021.  Anonymity Analysis of Bitcoin, Zcash and Ethereum. 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE). :45–48.
As an innovative type of decentralized model, blockchain is a growing list of blocks linked by cryptography. Blockchain incorporates anonymity protocol, distributed data storage, consensus algorithm, and smart contract. The anonymity protocols in blockchain are significant in that they could protect users from leaking their personal information. In this paper, we will conduct a detailed review and comparison of anonymity protocols used in three famous cryptocurrencies, namely Bitcoin, Zcash, and Ethereum.
Weng, Jui-Hung, Chi, Po-Wen.  2021.  Multi-Level Privacy Preserving K-Anonymity. 2021 16th Asia Joint Conference on Information Security (AsiaJCIS). :61–67.
k-anonymity is a well-known definition of privacy, which guarantees that any person in the released dataset cannot be distinguished from at least k-1 other individuals. In the protection model, the records are anonymized through generalization or suppression with a fixed value of k. Accordingly, each record has the same level of anonymity in the published dataset. However, different people or items usually have inconsistent privacy requirements. Some records need extra protection while others require a relatively low level of privacy constraint. In this paper, we propose Multi-Level Privacy Preserving K-Anonymity, an advanced protection model based on k-anonymity, which divides records into different groups and requires each group to satisfy its respective privacy requirement. Moreover, we present a practical algorithm using clustering techniques to ensure the property. The evaluation on a real-world dataset confirms that the proposed method has the advantages of offering more flexibility in setting privacy parameters and providing higher data utility than traditional k-anonymity.
Buccafurri, Francesco, Angelis, Vincenzo De, Francesca Idone, Maria, Labrini, Cecilia.  2021.  WIP: An Onion-Based Routing Protocol Strengthening Anonymity. 2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM). :231–235.
Anonymous Communication Networks (ACNs) are networks in which, beyond data confidentiality, also traffic flow confidentiality is provided. The most popular routing approach for ACNs also used in practice is Onion. Onion is based on multiple encryption wrapping combined with the proxy mechanism (relay nodes). However, it offers neither sender anonymity nor recipient anonymity in a global passive adversary model, simply because the adversary can observe (at the first relay node) the traffic coming from the sender, and (at the last relay node) the traffic delivered to the recipient. This may also cause a loss of relationship anonymity if timing attacks are performed. This paper presents Onion-Ring, a routing protocol that improves anonymity of Onion in the global adversary model, by achieving sender anonymity and recipient anonymity, and thus relationship anonymity.
Zhao, Pengyuan, Yang, Shengqi, Chen, Zheng.  2021.  Relationship Anonymity Evaluation Model Based on Markov Chain. 2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE). :671–676.
In this paper, we propose a relational anonymous P2P communication network evaluation model based on Markov chain (AEMC), and show how to extend our model to the anonymous evaluation of sender and receiver relationship anonymity when the attacker attacks the anonymous P2P communication network and obtains some information. Firstly, the constraints of the evaluation model (the attacker assumption for message tracing) are specified in detail; then the construction of AEMC anonymous evaluation model and the specific evaluation process are described; finally, the simulation experiment is carried out, and the evaluation model is applied to the probabilistic anonymous evaluation of the sender and receiver relationship of the attacker model, and the evaluation is carried out from the perspective of user (message).
Buccafurri, Francesco, De Angelis, Vincenzo, Idone, Maria Francesca, Labrini, Cecilia.  2021.  A Distributed Location Trusted Service Achieving k-Anonymity against the Global Adversary. 2021 22nd IEEE International Conference on Mobile Data Management (MDM). :133–138.
When location-based services (LBS) are delivered, location data should be protected against honest-but-curious LBS providers, them being quasi-identifiers. One of the existing approaches to achieving this goal is location k-anonymity, which leverages the presence of a trusted party, called location trusted service (LTS), playing the role of anonymizer. A drawback of this approach is that the location trusted service is a single point of failure and traces all the users. Moreover, the protection is completely nullified if a global passive adversary is allowed, able to monitor the flow of messages, as the source of the query can be identified despite location k-anonymity. In this paper, we propose a distributed and hierarchical LTS model, overcoming both the above drawbacks. Moreover, position notification is used as cover traffic to hide queries and multicast is minimally adopted to hide responses, to keep k-anonymity also against the global adversary, thus enabling the possibility that LBS are delivered within social networks.
Sibahee, M. A. A., Lu, S., Abduljabbar, Z. A., Liu, E. X., Ran, Y., Al-ashoor, A. A. J., Hussain, M. A., Hussien, Z. A..  2020.  Promising Bio-Authentication Scheme to Protect Documents for E2E S2S in IoT-Cloud. 2020 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). :1—6.

Document integrity and origin for E2E S2S in IoTcloud have recently received considerable attention because of their importance in the real-world fields. Maintaining integrity could protect decisions made based on these message/image documents. Authentication and integrity solutions have been conducted to recognise or protect any modification in the exchange of documents between E2E S2S (smart-to-smart). However, none of the proposed schemes appear to be sufficiently designed as a secure scheme to prevent known attacks or applicable to smart devices. We propose a robust scheme that aims to protect the integrity of documents for each users session by integrating HMAC-SHA-256, handwritten feature extraction using a local binary pattern, one-time random pixel sequence based on RC4 to randomly hide authentication codes using LSB. The proposed scheme can provide users with one-time bio-key, robust message anonymity and a disappearing authentication code that does not draw the attention of eavesdroppers. Thus, the scheme improves the data integrity for a users messages/image documents, phase key agreement, bio-key management and a one-time message/image document code for each users session. The concept of stego-anonymity is also introduced to provide additional security to cover a hashed value. Finally, security analysis and experimental results demonstrate and prove the invulnerability and efficiency of the proposed scheme.

Soni, D. K., Sharma, H., Bhushan, B., Sharma, N., Kaushik, I..  2020.  Security Issues Seclusion in Bitcoin System. 2020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT). :223—229.

In the dawn of crypto-currencies the most talked currency is Bitcoin. Bitcoin is widely flourished digital currency and an exchange trading commodity implementing peer-to-peer payment network. No central athourity exists in Bitcoin. The users in network or pool of bitcoin need not to use real names, rather they use pseudo names for managing and verifying transactions. Due to the use of pseudo names bitcoin is apprehended to provide anonymity. However, the most transparent payment network is what bitcoin is. Here all the transactions are publicly open. To furnish wholeness and put a stop to double-spending, Blockchain is used, which actually works as a ledger for management of Bitcoins. Blockchain can be misused to monitor flow of bitcoins among multiple transactions. When data from external sources is amalgamated with insinuation acquired from the Blockchain, it may result to reveal user's identity and profile. In this way the activity of user may be traced to an extent to fraud that user. Along with the popularity of Bitcoins the number of adversarial attacks has also gain pace. All these activities are meant to exploit anonymity and privacy in Bitcoin. These acivities result in loss of bitcoins and unlawful profit to attackers. Here in this paper we tried to present analysis of major attacks such as malicious attack, greater than 52% attacks and block withholding attack. Also this paper aims to present analysis and improvements in Bitcoin's anonymity and privacy.

Tikhomirov, S., Moreno-Sanchez, P., Maffei, M..  2020.  A Quantitative Analysis of Security, Anonymity and Scalability for the Lightning Network. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :387—396.

Payment channel networks have been introduced to mitigate the scalability issues inherent to permissionless decentralized cryptocurrencies such as Bitcoin. Launched in 2018, the Lightning Network (LN) has been gaining popularity and consists today of more than 5000 nodes and 35000 payment channels that jointly hold 965 bitcoins (9.2M USD as of June 2020). This adoption has motivated research from both academia and industryPayment channels suffer from security vulnerabilities, such as the wormhole attack [39], anonymity issues [38], and scalability limitations related to the upper bound on the number of concurrent payments per channel [28], which have been pointed out by the scientific community but never quantitatively analyzedIn this work, we first analyze the proneness of the LN to the wormhole attack and attacks against anonymity. We observe that an adversary needs to control only 2% of nodes to learn sensitive payment information (e.g., sender, receiver, and amount) or to carry out the wormhole attack. Second, we study the management of concurrent payments in the LN and quantify its negative effect on scalability. We observe that for micropayments, the forwarding capability of up to 50% of channels is restricted to a value smaller than the channel capacity. This phenomenon hinders scalability and opens the door for denial-of-service attacks: we estimate that a network-wide DoS attack costs within 1.6M USD, while isolating the biggest community costs only 238k USDOur findings should prompt the LN community to consider the issues studied in this work when educating users about path selection algorithms, as well as to adopt multi-hop payment protocols that provide stronger security, privacy and scalability guarantees.

Sammoud, A., Chalouf, M. A., Hamdi, O., Montavont, N., Bouallegue, A..  2020.  A secure three-factor authentication and biometrics-based key agreement scheme for TMIS with user anonymity. 2020 International Wireless Communications and Mobile Computing (IWCMC). :1916—1921.

E- Health systems, specifically, Telecare Medical Information Systems (TMIS), are deployed in order to provide patients with specific diseases with healthcare services that are usually based on remote monitoring. Therefore, making an efficient, convenient and secure connection between users and medical servers over insecure channels within medical services is a rather major issue. In this context, because of the biometrics' characteristics, many biometrics-based three factor user authentication schemes have been proposed in the literature to secure user/server communication within medical services. In this paper, we make a brief study of the most interesting proposals. Then, we propose a new three-factor authentication and key agreement scheme for TMIS. Our scheme tends not only to fix the security drawbacks of some studied related work, but also, offers additional significant features while minimizing resource consumption. In addition, we perform a formal verification using the widely accepted formal security verification tool AVISPA to demonstrate that our proposed scheme is secure. Also, our comparative performance analysis reveals that our proposed scheme provides a lower resource consumption compared to other related work's proposals.

Fathi, Z., Rafsanjani, A. J., Habibi, F..  2020.  Anon-ISAC: Anonymity-preserving cyber threat information sharing platform based on permissioned Blockchain. 2020 28th Iranian Conference on Electrical Engineering (ICEE). :1—5.

In cyber threat information sharing, secure transfer and protecting privacy are very important. In this paper we solve these issues by suggesting a platform based on private permissioned Blockchain, which provides us with access control as well. The platform is called Anon-ISAC and is built on the Enhanced Privacy ID (EPID) zero-knowledge proof scheme. It makes use of permissioned Blockchain as a way to keep identity anonymous. Organizations can share their information on incidents or other artifacts among trusted parties, while they keep their identity hidden. This will save them from unwanted consequences of exposure of sensitive security information.

Salib, E. H., Aboutabl, M. S..  2020.  Hands-on Undergraduate Labs on Anonymity Cryptographic Algorithms. 2020 IEEE Frontiers in Education Conference (FIE). :1—9.

This is an innovative practice full paper. In past projects, we have successfully used a private TOR (anonymity network) platform that enabled our students to explore the end-to-end inner workings of the TOR anonymity network through a number of controlled hands-on lab assignments. These have saisfied the needs of curriculum focusing on networking functions and algorithms. To be able to extend the use and application of the private TOR platform into cryptography courses, there is a desperate need to enhance the platform to allow the development of hands-on lab assignments on the cryptographic algorithms and methods utilized in the creation of TOR secure connections and end-to-end circuits for anonymity.In tackling this challenge, and since TOR is open source software, we identify the cryptographic functions called by the TOR algorithms in the process of establishing TLS connections and creating end-to-end TOR circuits as well tearing them down. We instrumented these functions with the appropriate code to log the cryptographic keys dynamically created at all nodes involved in the creation of the end to end circuit between the Client and the exit relay (connected to the target server).We implemented a set of pedagogical lab assignments on a private TOR platform and present them in this paper. Using these assignments, students are able to investigate and validate the cryptographic procedures applied in the establishment of the initial TLS connection, the creation of the first leg of a TOR circuit, as well as extending the circuit through additional relays (at least two relays). More advanced assignments are created to challenge the students to unwrap the traffic sent from the Client to the exit relay at all onion skin layers and compare it with the actual traffic delivered to the target server.

Lin, G., Zhao, H., Zhao, L., Gan, X., Yao, Z..  2020.  Differential Privacy Information Publishing Algorithm based on Cluster Anonymity. 2020 International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE). :226—233.

With the development of Internet technology, the attacker gets more and more complex background knowledge, which makes the anonymous model susceptible to background attack. Although the differential privacy model can resist the background attack, it reduces the versatility of the data. In this paper, this paper proposes a differential privacy information publishing algorithm based on clustering anonymity. The algorithm uses the cluster anonymous algorithm based on KD tree to cluster the original data sets and gets anonymous tables by anonymous operation. Finally, the algorithm adds noise to the anonymous table to satisfy the definition of differential privacy. The algorithm is compared with the DCMDP (Density-Based Clustering Mechanism with Differential Privacy, DCMDP) algorithm under different privacy budgets. The experiments show that as the privacy budget increases, the algorithm reduces the information loss by about 80% of the published data.

Santos, W., Sousa, G., Prata, P., Ferrão, M. E..  2020.  Data Anonymization: K-anonymity Sensitivity Analysis. 2020 15th Iberian Conference on Information Systems and Technologies (CISTI). :1—6.

These days the digitization process is everywhere, spreading also across central governments and local authorities. It is hoped that, using open government data for scientific research purposes, the public good and social justice might be enhanced. Taking into account the European General Data Protection Regulation recently adopted, the big challenge in Portugal and other European countries, is how to provide the right balance between personal data privacy and data value for research. This work presents a sensitivity study of data anonymization procedure applied to a real open government data available from the Brazilian higher education evaluation system. The ARX k-anonymization algorithm, with and without generalization of some research value variables, was performed. The analysis of the amount of data / information lost and the risk of re-identification suggest that the anonymization process may lead to the under-representation of minorities and sociodemographic disadvantaged groups. It will enable scientists to improve the balance among risk, data usability, and contributions for the public good policies and practices.

Esmeel, T. K., Hasan, M. M., Kabir, M. N., Firdaus, A..  2020.  Balancing Data Utility versus Information Loss in Data-Privacy Protection using k-Anonymity. 2020 IEEE 8th Conference on Systems, Process and Control (ICSPC). :158—161.

Data privacy has been an important area of research in recent years. Dataset often consists of sensitive data fields, exposure of which may jeopardize interests of individuals associated with the data. In order to resolve this issue, privacy techniques can be used to hinder the identification of a person through anonymization of the sensitive data in the dataset to protect sensitive information, while the anonymized dataset can be used by the third parties for analysis purposes without obstruction. In this research, we investigated a privacy technique, k-anonymity for different values of on different number columns of the dataset. Next, the information loss due to k-anonymity is computed. The anonymized files go through the classification process by some machine-learning algorithms i.e., Naive Bayes, J48 and neural network in order to check a balance between data anonymity and data utility. Based on the classification accuracy, the optimal values of and are obtained, and thus, the optimal and can be used for k-anonymity algorithm to anonymize optimal number of columns of the dataset.

Kumar, B. S., Daniya, T., Sathya, N., Cristin, R..  2020.  Investigation on Privacy Preserving using K-Anonymity Techniques. 2020 International Conference on Computer Communication and Informatics (ICCCI). :1—7.

In the current world, day by day the data growth and the investigation about that information increased due to the pervasiveness of computing devices, but people are reluctant to share their information on online portals or surveys fearing safety because sensitive information such as credit card information, medical conditions and other personal information in the wrong hands can mean danger to the society. These days privacy preserving has become a setback for storing data in data repository so for that reason data in the repository should be made undistinguishable, data is encrypted while storing and later decrypted when needed for analysis purpose in data mining. While storing the raw data of the individuals it is important to remove person-identifiable information such as name, employee id. However, the other attributes pertaining to the person should be encrypted so the methodologies used to implement. These methodologies can make data in the repository secure and PPDM task can made easier.

Javed, M. U., Jamal, A., Javaid, N., Haider, N., Imran, M..  2020.  Conditional Anonymity enabled Blockchain-based Ad Dissemination in Vehicular Ad-hoc Network. 2020 International Wireless Communications and Mobile Computing (IWCMC). :2149—2153.

Advertisement sharing in vehicular network through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication is a fascinating in-vehicle service for advertisers and the users due to multiple reasons. It enable advertisers to promote their product or services in the region of their interest. Also the users get to receive more relevant ads. Usually, users tend to contribute in dissemination of ads if their privacy is preserved and if some incentive is provided. Recent researches have focused on enabling both of the parameters for the users by developing fair incentive mechanism which preserves privacy by using Zero-Knowledge Proof of Knowledge (ZKPoK) (Ming et al., 2019). However, the anonymity provided by ZKPoK can introduce internal attacker scenarios in the network due to which authenticated users can disseminate fake ads in the network without payment. As the existing scheme uses certificate-less cryptography, due to which malicious users cannot be removed from the network. In order to resolve these challenges, we employed conditional anonymity and introduced Monitoring Authority (MA) in the system. In our proposed scheme, the pseudonyms are assigned to the vehicles while their real identities are stored in Certification Authority (CA) in encrypted form. The pseudonyms are updated after a pre-defined time threshold to prevent behavioural privacy leakage. We performed security and performance analysis to show the efficiency of our proposed system.

Wang, N., Song, H., Luo, T., Sun, J., Li, J..  2020.  Enhanced p-Sensitive k-Anonymity Models for Achieving Better Privacy. 2020 IEEE/CIC International Conference on Communications in China (ICCC). :148—153.

To our best knowledge, the p-sensitive k-anonymity model is a sophisticated model to resist linking attacks and homogeneous attacks in data publishing. However, if the distribution of sensitive values is skew, the model is difficult to defend against skew attacks and even faces sensitive attacks. In practice, the privacy requirements of different sensitive values are not always identical. The “one size fits all” unified privacy protection level may cause unnecessary information loss. To address these problems, the paper quantifies privacy requirements with the concept of IDF and concerns more about sensitive groups. Two enhanced anonymous models with personalized protection characteristic, that is, (p,αisg) -sensitive k-anonymity model and (pi,αisg)-sensitive k-anonymity model, are then proposed to resist skew attacks and sensitive attacks. Furthermore, two clustering algorithms with global search and local search are designed to implement our models. Experimental results show that the two enhanced models have outstanding advantages in better privacy at the expense of a little data utility.