• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1343-1356
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• 2013

Cloud computing has emerged as perhaps the hottest development in information technology at present. This new computing technology requires that the users ensure that their infrastructure is safety and that their data and applications are protected. In addition, the customer must ensure that the provider has taken the proper security measures to protect their information. In order to achieve fine-grained and flexible access control for cloud computing, a new construction of hierarchical attribute-based encryption(HABE) with Ciphertext-Policy is proposed in this paper. The proposed scheme inherits flexibility and delegation of hierarchical identity-based cryptography, and achieves scalability due to the hierarchical structure. The new scheme has constant size ciphertexts since it consists of two group elements. In addition, the security of the new construction is achieved in the standard model which avoids the potential defects in the existing works. Under the decision bilinear Diffie-Hellman exponent assumption, the proposed scheme is provable security against Chosen-plaintext Attack(CPA). Furthermore, we also show the proposed scheme can be transferred to a CCA(Chosen-ciphertext Attack) secure scheme.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.538-547
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• 2016

Cloud computing is a new style of computing in which dynamically scalable and reconfigurable resources are provided as a service over the internet. The MapReduce framework is currently the most dominant programming model in cloud computing. It is necessary to protect the integrity of MapReduce data processing services. Malicious workers, who can be divided into collusive workers and non-collusive workers, try to generate bad results in order to attack the cloud computing. So, figuring out how to efficiently detect the malicious workers has been very important, as existing solutions are not effective enough in defeating malicious behavior. In this paper, we propose a security protection framework to detect the malicious workers and ensure computation integrity in the map phase of MapReduce. Our simulation results show that our proposed security protection framework can efficiently detect both collusive and non-collusive workers and guarantee high computation accuracy.

• Convergence Security Journal
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• v.12 no.3
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• pp.59-65
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• 2012

Clouding computing which is developing newly as IT and network technology develops become changed to internet and service environment of company. Especially, it can lend IT resource at low costs and no need to build up infra. Clouding computing environment become popular more and more because various computing environment using virtualization is provided. The attack threat range also becomes wider in proportion to broaden various connection ways and service supply range at these clouding computing. Therefore, intrusion detection system which can protect resource from various attack having malignant attempts is necessary. In this study, we analyzed about characteristic of intrusion detection system at cloud computing environment having big damage than other computing environment when intrusion happen by sharing of resource and virtualization.

• KIISE Transactions on Computing Practices
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• v.22 no.8
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• pp.345-350
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• 2016

Cloud computing services have different characteristics from the traditional computing environment such as resource sharing, virtualization, etc. These characteristics of cloud computing environment necessitate specific properties such as user identify, access control, security control property, etc. Recently, Yoo proposed an attribute-based authentication scheme for secure cloud computing. However, Yoo's authentication scheme is vulnerable to customer attack and an adversary can modify the authentication request message. In this paper, we propose a secure and efficient attribute-based authentication scheme for cloud computing based on Yoo's scheme.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.11-20
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• 2017

Recently, developments in the various fields of cloud computing technology has been utilized. Whereas the demand for cloud computing services is increasing, security threats are also increasing in the cloud computing environments. Especially, in case when the hosts interconnected in the cloud environments are infected and propagated through the attacks by malware. It can have an effect on the resource of other hosts and other security threats such as personal information can be spreaded and data deletion. Therefore, the study of malware analysis to respond these security threats has been proceeded actively. This paper proposes a type of attack clustering method of Zeus botnet using the k-means clustering algorithm for malware analysis that occurs in the cloud environments. By clustering the malicious activity by a type of the Zeus botnet occurred in the cloud environments. it is possible to determine whether it is a malware or not. In the future, it sets a goal of responding to an attack of the new type of Zeus botnet that may occur in the cloud environments.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.73-79
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• 2013

Cloud computing is a form which provides IT resources through network and pays the cost as much as you used. And it has advantages that it doesn't need to construct infrastructure and can be offered a variety of environments. The main core of these computing is virtualization technology. Security mechanism about attacks using vulnerabilities of virtualization technology isn't provided right and existing security tools can't be applied as it is. In this paper, we proposed honeyVM structure that can cope actively by collecting the information about attacks using virtualization vulnerability. Mamdani fuzzy inference is used to adjust dynamically the number of formed honeyVM depending on the load of system. Security structure to protect actual virtual machine from attacks and threats is proposed. The performance of the proposed structure in this paper measured occurred attack detection rate and resource utilization rate.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.67-74
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• 2022

One type of network security breach is the availability breach, which deprives legitimate users of their right to access services. The Denial of Service (DoS) attack is one way to have this breach, whereas using the Intrusion Detection System (IDS) is the trending way to detect a DoS attack. However, building IDS has two challenges: reducing the false alert and picking up the right dataset to train the IDS model. The survey concluded, in the end, that using a real dataset such as MAWILab or some tools like ID2T that give the researcher the ability to create a custom dataset may enhance the IDS model to handle the network threats, including DoS attacks. In addition to minimizing the rate of the false alert.

• Smart Media Journal
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• v.5 no.2
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• pp.65-76
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• 2016

Cloud Computing has recently begun to emerge as a new attack target. The malice DDoS attacks are ongoing to delay and disturb the various services of the Cloud Computing. In this paper, we propose the Hornet-Cloud using security Honeypot technique and resources of Cloud Computing, define and design the concept of security functions about active low-interaction framework by cyber resilience simply. In addition, for virtual honeypot service, we simulated and vitrified the possibility of functions of the low-interaction vHoneypot using cyber resilience.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.240-257
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• 2023

The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.276-282
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• 2022

One of the most essential foundations upon which big institutions rely in delivering cloud computing and hosting services, as well as other kinds of multiple digital services, is the security of infrastructures for digital and information services throughout the world. Distributed denial-of-service (DDoS) assaults are one of the most common types of threats to networks and data centers. Denial of service attacks of all types operates on the premise of flooding the target with a massive volume of requests and data until it reaches a size bigger than the target's energy, at which point it collapses or goes out of service. where it takes advantage of a flaw in the Transport Control Protocol's transmitting and receiving (3-way Handshake) (TCP). The current study's major focus is on an architecture that stops DDoS attacks assaults by producing code for DDoS attacks using a cloud controller and calculating Round-Tripe Time (RTT).