• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.16 no.4
• /
• pp.3-12
• /
• 2006

RFID (Radio Frequency Identification) system is expected to play a critical role providing widespread services in the ubiquitous period. However, widespread use of RFID tags may create new threats to the privacy of individuals such as information leakage and traceability. It is difficult to solve the privacy problems because a tag has the limited computing power that is not the adequate resource to support the general encryption. Although the scheme of [2] protects the consumer privacy using an external agent, a tag should compute exponential operation needed high cost. We propose Self Re-Encryption Protocol (SREP) which provides song privacy without assisting of any external agent. Our SREP is well suitable to low-cost RFID system since it only needs multiplication and exclusive-or operation.

• Convergence Security Journal
• /
• v.17 no.5
• /
• pp.49-55
• /
• 2017

In case of security of IoT-based areas in ICBM industry, the anxiety about safety goes to extremes in public and national safety area, so that the demand for security service related to disaster/safety management is increasing. Like this, as a security service for safety, CCTVs are installed/operated for the purpose of maintenance of public order and crime prevention. Especially, as the recorded images are presented as crucial evidences of crimes, they are rapidly increasing. However, as adverse effects of CCTVs, it is highly possible to unintentionally leak personal information in the process of performing the original purpose, or to violate someone's privacy in case when such technologies are abused. Therefore, it would be necessary to have researches on the multilaterally-combined mechanism for the protection of image privacy.

• International Journal of Computer Science & Network Security
• /
• v.23 no.4
• /
• pp.25-31
• /
• 2023

Fog computing diversifies cloud computing by using edge devices to provide computing, data storage, communication, management, and control services. As it has a decentralised infrastructure that is capable of amalgamating with cloud computing as well as providing real-time data analysis, it is an emerging method of using multidisciplinary domains for a variety of applications; such as the IoT, Big Data, and smart cities. This present study provides an overview of the security and privacy concerns of fog computing. It also examines its fundamentals and architecture as well as the current trends, challenges, and potential methods of overcoming issues in fog computing.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.6
• /
• pp.121-134
• /
• 2009

Consumer-centric marketing business is surely one of the most successful emerging business but it poses a threat to personal privacy. Between the service provider and the user there are many contrary issues to each other. The enterprise asserts that to abuse the privacy data which is anonymous there is not a problem. The individual only will not be able to willingly submit the problem which is latent. Web traffic analysis technology itself doesn't create issues, but this technology when used on data of personal nature might cause concerns. The most criticized ethical issue involving web traffic analysis is the invasion of privacy. So we need to inspect how many and what kind of personal informations being used and if there is any illegal treatment of personal information. In this paper, we inspect the operation of consumer-centric marketing tools such as web log analysis solutions and data gathering services with web browser toolbar. Also we inspect Microsoft explorer-based toolbar application which records and analyzes personal web browsing pattern through reverse engineering technology. Finally, this identified and explored security and privacy requirement issues to develop more reliable solutions. This study is very important for the balanced development with personal privacy protection and web traffic analysis industry.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.15 no.4
• /
• pp.71-84
• /
• 2019

Various researchers conducted the research on two-factor authentication suitable for wireless sensor networks (WSNs) after Das first proposed two-factor authentication combining the smart card and password. After then, To improve the security of user authentication, elliptic curve cryptography(ECC)-based authentication protocols have been proposed. Jiang et al. proposed a privacy-aware two-factor authentication protocol based on ECC for WSM for resolving various problems of ECC-based authentication protocols. However, Jiang et al.'s protocol has the vulnerabilities on a lack of mutual authentication, a risk of SID modification and a lack of sensor anonymity, and user's ID exposed on sensor node Therefore, this paper proposed security enhanced privacy-aware two-factor authentication protocol for wireless sensor networks to solve the problem of Jiang et al.'s protocol, and security analysis was conducted for the proposed protocol.

• International Journal of Computer Science & Network Security
• /
• v.23 no.6
• /
• pp.99-106
• /
• 2023

Now a days, large volumes of data is accumulating in every field due to increase in capacity of storage devices. These large volumes of data can be applied with data mining for finding useful patterns which can be used for business growth, improving services, improving health conditions etc. Data from different sources can be combined before applying data mining. The data thus gathered can be misused for identity theft, fake credit/debit card transactions, etc. To overcome this, data mining techniques which provide privacy are required. There are several privacy preserving data mining techniques available in literature like randomization, perturbation, anonymization etc. This paper proposes an Enhanced Hybrid Privacy Preserving Data Mining(EHPPDM) technique. The proposed technique provides more privacy of data than existing techniques while providing better classification accuracy. The experimental results show that classification accuracies have increased using EHPPDM technique.

• International Journal of Computer Science & Network Security
• /
• v.22 no.4
• /
• pp.340-350
• /
• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• International Journal of Contents
• /
• v.12 no.2
• /
• pp.6-11
• /
• 2016

We developed a pilot-job based large-scale distributed computing system to support HTC and MTC, called HTCaaS (High-Throughput Computing as a Service), which helps scientists solve large-scale scientific problems in areas such as pharmaceutical domains, high-energy physics, nuclear physics and bio science. Since most of these problems involve critical data that affect the national economy and activate basic industries, data privacy is a very important issue. In this paper, we implement a privacy enhanced data security mechanism to support HTC and MTC in a large-scale distributed computing system and show how this technique affects performance in our system. With this mechanism, users can securely store data in our system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.3
• /
• pp.411-427
• /
• 2010

Data sharing is an essential process for collaborative works particularly in the banking, finance and healthcare industries. These industries require many collaborative works with their internal and external parties such as branches, clients, and service providers. When data are shared among collaborators, security and privacy concerns becoming crucial issues and cannot be avoided. Privacy is an important issue that is frequently discussed during the development of collaborative systems. It is closely related with the security issues because each of them can affect the other. The tradeoff between privacy and security is an interesting topic that we are going to address in this paper. In view of the practical problems in the existing approaches, we propose a collaborative framework which can be used to facilitate concurrent operations, single point failure problem, and overcome constraints for two-party computation. Two secure computation protocols will be discussed to demonstrate our collaborative framework.

• International Journal of Computer Science & Network Security
• /
• v.22 no.12
• /
• pp.1-12
• /
• 2022

Besides unexpected growth perceived by IoT's, the variety and volume of threats have increased tremendously, making it a necessity to introduce intrusion detections systems for prevention and detection of such threats. But Intrusion Detection and Prevention System (IDPS) inside the IoT network yet introduces some unique challenges due to their unique characteristics, such as privacy inference, performance, and detection rate and their frequency in the dynamic networks. Our research is focused on the privacy inferences of existing intrusion prevention and detection system approaches. We also tackle the problem of providing unified a solution to implement the open-source IDPS in the IoT architecture for assessing the performance of IDS by calculating; usage consumption and detection rate. The proposed scheme is considered to help implement the human health monitoring system in IoT networks