• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4742-4770
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• 2019

Cloud computing provides a broad range of services like operating systems, hardware, software and resources. Availability of these services encourages data owners to outsource their intensive computations and massive data to the cloud. However, considering the untrusted nature of cloud server, it is essential to encrypt the data before outsourcing it to the cloud. Unfortunately, this leads to a challenge when it comes to providing search functionality for encrypted data located in the cloud. To address this challenge, this paper presents a public key encryption with equality test for heterogeneous systems (PKE-ET-HS). The PKE-ET-HS scheme simulates certificateless public encryption with equality test (CLE-ET) with the identity-based encryption with equality test (IBE-ET). This scheme provides the authorized cloud server the right to actuate the equivalence of two messages having their encryptions performed under heterogeneous systems. Basing on the random oracle model, we construct the security of our proposed scheme under the bilinear Diffie-Hellman (BDH) assumption. Eventually, we evaluate the size of storage, computation complexities, and properties with other related works and illustrations indicate good performance from our scheme.

• Convergence Security Journal
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• v.14 no.7
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• pp.85-90
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• 2014

Cloud computing originated simply to request and execute the desired operation from the network of clouds. It means that an IT resource that provides a service using the Internet technology. It is getting the most attention in today's IT trends. In cloud computing networks, devices and data centers which are composed of the server, storage and application are connected over network. That is, data of computers in different physical locations are integrated using the virtualization technology to provide a service. Therefore cloud computing system is a key information resource, standardized methods and assessment system are required. In this paper, we aims to derive the parameters and information for research of technical standards stability evaluation method associated with various cloud computing equipment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1892-1903
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• 2016

Mobile social network is becoming more and more popular with respect to the development and popularity of mobile devices and interpersonal sociality. As the amount of social data increases in a great deal and cloud computing techniques become developed, the architecture of mobile social network is evolved into cloud-based that mobile clients send data to the cloud and make data accessible from clients. The data in the cloud should be stored in a secure fashion to protect user privacy and restrict data sharing defined by users. Ciphertext-policy attribute-based encryption (CP-ABE) is currently considered to be a promising security solution for cloud-based mobile social network to encrypt the sensitive data. However, its ciphertext size and decryption time grow linearly with the attribute numbers in the access structure. In order to reduce the computing overhead held by the mobile devices, in this paper we propose a new Outsourcing decryption and Match-then-decrypt CP-ABE algorithm (OM-CP-ABE) which firstly outsources the computation-intensive bilinear pairing operations to a proxy, and secondly performs the decryption test on the attributes set matching access policy in ciphertexts. The experimental performance assessments show the security strength and efficiency of the proposed solution in terms of computation, communication, and storage. Also, our construction is proven to be replayable choosen-ciphertext attacks (RCCA) secure based on the decisional bilinear Diffie-Hellman (DBDH) assumption in the standard model.

• Journal of Convergence Society for SMB
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• v.1 no.1
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• pp.29-37
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• 2011

As the area of informatization has been expanding followed by the development of information communication technology, cloud computing which can use infra sources like server, storage, and network in IT area as an efficient service whenever and wherever skyrockets. But users who use cloud computing technology may have some problems like exposure personal data, surveillance on person, and process on commercial purpose on their personal data. This paper proposes a security technique which protect user's privacy by creating imaginary user information not to be used by other people. The proposed technique virtualizes user's information as an anonymity value not to let other people know user's identity by combining PIN code with it and guarantees user's anonymity. Also it can manage and certificate personal information that is important in cloud computing, so that it can solve security problem of cloud computing which centers all informations. Therefore this paper can assist upgrading of the level of information of poor SMBs through safe use of cloud computing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.366-369
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• 2014

Recently been viewed as a core technology of the IT industry, cloud computing services. It is expected that the market for cloud services industry showed a growth rate of 18.9% annually, to form a scale of $ 1,330 billion dollars in 2013, and to form a 1,768 billion dollars in 2015. Growth of cloud computing services industry, provides the operational efficiency and reduce costs for many companies, but the risks associated with it is also increasing. There is a problem that phenomenon is to lose control of the data on features of the cloud service, more data is gathered in one place, when a failure occurs, it is removed simultaneously the data of all devices. therefore, in the present paper is investigate the area a quick recovery with up to the problem and secure data storage INT the cloud computing service is available in only the data in the cloud service possible.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.429-436
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• 2018

Electronic documents are efficient to be created and managed, but they are liable to lose their originality because copies are created during distribution and delivery. For this reason, various security technologies for electronic documents have been applied. However, most security technologies currently used are for document management such as file access privilege control, file version and history management, and therefore can not be used in environments where authenticity is absolutely required, such as confidential documents. In this paper, we propose a method to detect document forgery and tampering through analysis of file system without installing an agent inside the instance operating system in cloud computing environment. BubbleDoc monitors the minimum amount of virtual volume storage in an instance, so it can efficiently detect forgery and tampering of documents. Experimental results show that the proposed technique has 0.16% disk read operation overhead when it is set to 1,000ms cycle for monitoring for document falsification and modulation detection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1363-1374
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• 2012

The number and use of Internet connected devices has dramatically increased in the last several years. Therefore many services synchronizing data in real-time is increasing such as mail, calendar and storage service. This service provides convenience to users. However, after devices are seized, the data could be changed because of characteristic about real-time synchronization. Therefore digital investigation could be difficult by this service. This work investigates the traces on each local device and proposes a method for the preservation of real-time synchronized data. Based on these, we propose the procedures of real-time synchronization data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.295-311
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• 2023

Cloud computing has evolved significantly, intending to provide users with fast, dependable, and low-cost services. With its development, malicious users have become increasingly capable of attacking both its internal and external security. To ensure the security of cloud services, encryption, authorization, firewalls, and intrusion detection systems have been employed. However, these single monitoring agents, are complex, time-consuming, and they do not detect ransomware and zero-day vulnerabilities on their own. An innovative Record and Replay-based hybrid Honeynet (R2NET) system has been developed to address this issue. Combining honeynet with Record and Replay (RR) technology, the system allows fine-grained analysis by delaying time-consuming analysis to the replay step. In addition, a machine learning algorithm is utilized to cluster the logs of attackers and store them in a database. So, the accessing time for analyzing the attack may be reduced which in turn increases the efficiency of the proposed framework. The R2NET framework is compared with existing methods such as EEHH net, HoneyDoc, Honeynet system, and AHDS. The proposed system achieves 7.60%, 9.78%%, 18.47%, and 31.52% more accuracy than EEHH net, HoneyDoc, Honeynet system, and AHDS methods.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.89-96
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• 2023

Intrusion detection has been widely studied in both industry and academia, but cybersecurity analysts always want more accuracy and global threat analysis to secure their systems in cyberspace. Big data represent the great challenge of intrusion detection systems, making it hard to monitor and analyze this large volume of data using traditional techniques. Recently, deep learning has been emerged as a new approach which enables the use of Big Data with a low training time and high accuracy rate. In this paper, we propose an approach of an IDS based on cloud computing and the integration of big data and deep learning techniques to detect different attacks as early as possible. To demonstrate the efficacy of this system, we implement the proposed system within Microsoft Azure Cloud, as it provides both processing power and storage capabilities, using a convolutional neural network (CNN-IDS) with the distributed computing environment Apache Spark, integrated with Keras Deep Learning Library. We study the performance of the model in two categories of classification (binary and multiclass) using CSE-CIC-IDS2018 dataset. Our system showed a great performance due to the integration of deep learning technique and Apache Spark engine.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.60-66
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• 2024

Host's data during transmission. Data tempering results in loss of host's sensitive information, which includes number of VM, storage availability, and other information. In the distributed cloud environment, each server (computing server (CS)) configured with Local Resource Monitors (LRMs) which runs independently and performs Virtual Machine (VM) migrations to nearby servers. Approaches like predictive VM migration [21] [22] by each server considering nearby server's CPU usage, roatative decision making capacity [21] among the servers in distributed cloud environment has been proposed. This approaches usage underlying server's computing power for predicting own server's future resource utilization and nearby server's resource usage computation. It results in running VM and its running application to remain in waiting state for computing power. In order to reduce this, a decentralized decision making hybrid model for VM migration need to be proposed where servers in decentralized cloud receives, future resource usage by analytical computing system and takes decision for migrating VM to its neighbor servers. Host's in the decentralized cloud shares, their detail with peer servers after fixed interval, this results in chance to tempering messages that would be exchanged in between HC and CH. At the same time, it reduces chance of over utilization of peer servers, caused due to compromised host. This paper discusses, an roatative decisive (RD) approach for VM migration among peer computing servers (CS) in decentralized cloud environment, preserving confidentiality and integrity of the host's data. Experimental result shows that, the proposed predictive VM migration approach reduces extra VM migration caused due over utilization of identified servers and reduces number of active servers in greater extent, and ensures confidentiality and integrity of peer host's data.