• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.139-145
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• 2023

These days, protecting location privacy has become essential and really challenging, especially protecting it from smart applications and services that rely on Location-Based Services (LBS). As the technology and the services that are based on it are developed, the capability and the experience of the attackers are increased. Therefore, the traditional protection ways cannot be enough and are unable to fully ensure and preserve privacy. Previously, a hybrid approach to privacy has been introduced. It used an obfuscation technique, called Double-Obfuscation Approach (DOA), to improve the privacy level. However, this approach has some weaknesses. The most important ones are the fog nodes that have been overloaded due to the number of communications. It is also unable to prevent the Tracking and Identification attacks in the Mix-Zone technique. For these reasons, this paper introduces a developed and enhanced approach, called Multi-Obfuscation Approach (MOA that mainly depends on the communication between neighboring fog nodes to overcome the drawbacks of the previous approach. As a result, this will increase the resistance to new kinds of attacks and enhance processing. Meanwhile, this approach will increase the level of the users' privacy and their locations protection. To do so, a big enough memory is needed on the users' sides, which already is available these days on their devices. The simulation and the comparison prove that the new approach (MOA) exceeds the DOA in many Standards for privacy protection approaches.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.4 s.304
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• pp.25-32
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• 2005

The spread of mobile devices, PDAs and sensors has enabled the construction of ubiquitous computing environments, transforming regular physical spaces into 'Smart space' augmented with intelligence and enhanced with services. However, the deployment of this computing paradigm in real-life is disturbed by poor security, particularly, the lack of proper authentication and authorization techniques. Also, it is very important not only to find security measures but also to preserve user privacy in ubiquitous computing environments. In this Paper, we propose efficient user authentication and authorization model with anonymity for the privacy-preserving for ubiquitous computing environments. Our model is suitable for distributed environments with the computational constrained devices by using MAC-based anonymous certificate and security association token instead of using Public key encryption technique. And our Proposed Protocol is better than Kerberos system in sense of cryptographic computation processing.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1079-1090
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• 2014

Data mining is a technique to get the useful information that can be utilized for marketing and pattern analysis by processing the data that we have. However, when we use this technique, data provider's personal data can be leaked by accident. To protect these data from leakage, there were several techniques have been studied to preserve privacy. Vertically partitioned data is a state called that the data is separately provided to various number of user. On these vertically partitioned data, there was some methods developed to distinguishing kth element and (k+1) th element by using score. However, in previous method, we can only use on two-party case, so in this paper, we propose the extended technique by using paillier cryptosystem which can use on multi-party case.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.347-355
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• 2012

A biometric hardware security module is a physical device that comes in the form of smartcard or some other USB type security token is composed with biometric sensor and microcontroller unit (MCU). These modules are designed to process key generation and electronic signature generation inside of the device (so that the security token can safely save and store confidential information, like the electronic signature generation key and the biometric sensing information). However, the existing model is not consistent that can be caused by the disclosure of an ID and password, which is used by the existing personal authentication technique based on the security token, and provide a high level of security and personal authentication techniques that can prevent any intentional misuse of a digital certificate. So, this paper presents a model that can provide high level of security by utilizing the biometric security token and Public Key Infrastructure efficiently, presenting a model for privacy preserving personal authentication that links the biometric security token and the digital certificate.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.51-58
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• 2016

The unprecedented power of cloud computing (CC) that enables free sharing of confidential data records for further analysis and mining has prompted various security threats. Thus, supreme cyberspace security and mitigation against adversaries attack during data mining became inevitable. So, privacy preserving data mining is emerged as a precise and efficient solution, where various algorithms are developed to anonymize the data to be mined. Despite the wide use of generalized K-anonymizing approach its protection and truthfulness potency remains limited to tiny output space with unacceptable utility loss. By combining L-diversity and (${\alpha}$,k)-anonymity, we proposed a hybrid K-anonymity data relocation algorithm to surmount such limitation. The data relocation being a tradeoff between trustfulness and utility acted as a control input parameter. The performance of each K-anonymity's iteration is measured for data relocation. Data rows are changed into small groups of indistinguishable tuples to create anonymizations of finer granularity with assured privacy standard. Experimental results demonstrated considerable utility enhancement for relatively small number of group relocations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2841-2860
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• 2018

Vehicular networks play an important role in current intelligent transportation networks and have gained much attention from academia and industry. Vehicular networks can be enhanced by Long Term Evolution-Vehicle (LTE-V) technology, which has been defined in a series of standards by the 3rd Generation Partnership Project (3GPP). LTE-V technology is a systematic and integrated V2X solution. To guarantee secure LTE-V communication, security and privacy issues must be addressed before the network is deployed. The present study aims to improve the security functionality of vehicular LTE networks by proposing an efficient and secure ID-based message authentication scheme for vehicular networks, named the ESMAV. We demonstrate its ability to simultaneously support both mutual authentication and privacy protection. In addition, the ESMAV exhibit better performance in terms of overhead computation, communication cost, and security functions, which includes privacy preservation and non-frameability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3319-3338
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• 2016

Cloud storage is becoming more and more popular because of its elasticity and pay-as-you-go storage service manner. In some cloud storage scenarios, the data that are stored in the cloud may be shared by a group of users. To verify the integrity of cloud data in this kind of applications, many auditing schemes for shared cloud data have been proposed. However, all of these schemes do not consider the access authorization problem for users, which makes the revoked users still able to access the shared cloud data belonging to the group. In order to deal with this problem, we propose a novel public auditing scheme for shared cloud data in this paper. Different from previous work, in our scheme, the user in a group cannot any longer access the shared cloud data belonging to this group once this user is revoked. In addition, we propose a new random masking technique to make our scheme preserve both data privacy and identity privacy. Furthermore, our scheme supports to enroll a new user in a group and revoke an old user from a group. We analyze the security of the proposed scheme and justify its performance by concrete implementations.

• ETRI Journal
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• v.33 no.6
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• pp.935-944
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• 2011

As a growing number of individuals are exposed to surveillance cameras, the need to prevent captured videos from being used inappropriately has increased. Privacy-related information can be protected through video encryption during transmission or storage, and several algorithms have been proposed for such purposes. However, the simple way of evaluating the security by counting the number of brute-force trials is not proper for measuring the security of video encryption algorithms, considering that attackers can devise specially crafted attacks for specific purposes by exploiting the characteristics of the target video codec. In this paper, we introduce a new attack for recovering contour information from encrypted H.264 video. The attack can thus be used to extract face outlines for the purpose of personal identification. We analyze the security of previous video encryption schemes against the proposed attack and show that the security of these schemes is lower than expected in terms of privacy protection. To enhance security, an advanced block shuffling method is proposed, an analysis of which shows that it is more secure than the previous method and can be an improvement against the proposed attack.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1149-1155
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• 2017

In these days, cloud environments such as cloud platforms, cloud services like Amazon AWS, IBM Bluemix are used in the Internet of Things for providing efficient services. These cloud platform environments have various security threats according to increasing of use, so the recent research results on cloud security and privacy protection technologies and related regimes and legislations are written in this paper and we suggest prospect of research on cloud platform environment security and privacy preserving.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3087-3103
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• 2022

Nearest neighbor query in location-based services has become a popular application. Aiming at the shortcomings of the privacy protection algorithms of traditional ciphertext nearest neighbor query having the high system overhead because of the usage of the double Hilbert curves and having the inaccurate query results in some special circumstances, a privacy protection algorithm of ciphertext nearest neighbor query which is based on the single Hilbert curve has been proposed. This algorithm uses a single Hilbert curve to transform the two-dimensional coordinates of the points of interest into Hilbert values, and then encrypts them by the order preserving encryption scheme to obtain the one-dimensional ciphertext data which can be compared in numerical size. Then stores the points of interest as elements composed of index value and the ciphertext of the other information about the points of interest on the server-side database. When the user needs to use the nearest neighbor query, firstly calls the approximate nearest neighbor query algorithm proposed in this paper to query on the server-side database, and then obtains the approximate nearest neighbor query results. After that, the accurate nearest neighbor query result can be obtained by calling the precision processing algorithm proposed in this paper. The experimental results show that this privacy protection algorithm of ciphertext nearest neighbor query which is based on the single Hilbert curve is not only feasible, but also optimizes the system overhead and the accuracy of ciphertext nearest neighbor query result.