• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.1
• /
• pp.138-140
• /
• 2020

As the IoT is applied to home and industrial networks, data generated by the IoT is being processed at the cloud edge. Intrusion detection function is very important because it can be operated by invading IoT devices through the cloud edge. Data delivered to the edge network in the cloud environment is traffic at the application layer. In order to determine the intrusion of the packet transmitted to the IoT, the intrusion should be detected at the application layer. This paper proposes the intrusion detection function at the application layer excluding normal traffic from IoT intrusion detection function. As the proposed method, we obtained the intrusion detection result by decision tree method and explained the detection result for each feature.

• Journal of Information Processing Systems
• /
• v.14 no.1
• /
• pp.239-251
• /
• 2018

In existing cloud services, information security and privacy concerns have been worried, and have become one of the major factors that hinder the popularization and promotion of cloud computing. As the cloud computing infrastructure, the security of virtual machine systems is very important. This paper presents an immune-inspired intrusion detection model in virtual machines of cloud computing environment, denoted I-VMIDS, to ensure the safety of user-level applications in client virtual machines. The model extracts system call sequences of programs, abstracts them into antigens, fuses environmental information of client virtual machines into danger signals, and implements intrusion detection by immune mechanisms. The model is capable of detecting attacks on processes which are statically tampered, and is able to detect attacks on processes which are dynamically running. Therefore, the model supports high real time. During the detection process, the model introduces information monitoring mechanism to supervise intrusion detection program, which ensures the authenticity of the test data. Experimental results show that the model does not bring much spending to the virtual machine system, and achieves good detection performance. It is feasible to apply I-VMIDS to the cloud computing platform.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.4
• /
• pp.107-113
• /
• 2012

Cloud computing has brought changes to the IT environment. Due to the spread of LTE, users of cloud services are growing more. This which provides IT resources to meet the needs of users of cloud services are noted as a core industry. But it is not activated because of the security of personal data and the safety of the service. In order to solve this, intrusion detection system is constructed as follows. This protects individual data safely which exists in the cloud and also protects information exhaustively from malicious attack. The cause of most attack risk which exists to cloud computing can find in distributed environment. In this study, we analyzed about necessary property of network-based intrusion detection system that process and analyze large amount of data which occur in cloud computing environment. Also, we studied functions which detect and correspond attack occurred in interior of virtualization.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.63-76
• /
• 2023

Identity and access management in cloud computing is one of the leading significant issues that require various security countermeasures to preserve user privacy. An authentication mechanism is a leading solution to authenticate and verify the identities of cloud users while accessing cloud applications. Building a secured and flexible authentication mechanism in a cloud computing platform is challenging. Authentication techniques can be combined with other security techniques such as intrusion detection systems to maintain a verifiable layer of security. In this paper, we provide an interactive, flexible, and reliable multi-factor authentication mechanisms that are primarily based on a proposed Authentication Method Selector (AMS) technique. The basic idea of AMS is to rely on the user's previous authentication information and user behavior which can be embedded with additional authentication methods according to the organization's requirements. In AMS, the administrator has the ability to add the appropriate authentication method based on the requirements of the organization. Based on these requirements, the administrator will activate and initialize the authentication method that has been added to the authentication pool. An intrusion detection component has been added to apply the users' location and users' default web browser feature. The AMS and intrusion detection components provide a security enhancement to increase the accuracy and efficiency of cloud user identity verification.

• Journal of Information Processing Systems
• /
• v.15 no.1
• /
• pp.137-150
• /
• 2019

Although the research of immune-based anomaly detection technology has made some progress, there are still some defects which have not been solved, such as the loophole problem which leads to low detection rate and high false alarm rate, the exponential relationship between training cost of mature detectors and size of self-antigens. This paper proposed an intrusion detection method based on changes of antibody concentration in immune response to improve and solve existing problems of immune based anomaly detection technology. The method introduces blood relative and blood family to classify antibodies and antigens and simulate correlations between antibodies and antigens. Then, the method establishes dynamic evolution models of antigens and antibodies in intrusion detection. In addition, the method determines concentration changes of antibodies in the immune system drawing the experience of cloud model, and divides the risk levels to guide immune responses. Experimental results show that the method has better detection performance and adaptability than traditional methods.

• Journal of Korea Multimedia Society
• /
• v.20 no.1
• /
• pp.58-65
• /
• 2017

The recent years, the cloud-based paradigm of cloud services are developed rapidly, it come with many a new problems. However, the collaboration between a individual with other users is still difficult. Cloud service is considered when users need to take advantage of security and the availability of cloud services. In this paper, we proposed an detection framework to detect an intrusion attack that threaten to cloud-based collaboration services and cloud security. Identify vulnerabilities and prepare for the safety of the collaboration services to create a variety of content in the cloud, it help to prevent the threats.

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

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

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

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.3
• /
• pp.57-64
• /
• 2012

Computing environment combined with development of internet and IT technology is changing to cloud computing environment. In addition, cloud computing is revitalized more because of propagation of LTE and suggestion of N-screen Service. Virtualization is the point technology for suggest IT resource to service form to users in this cloud computing. This technology combines other system physically or divides one system logically and uses resource efficiently. Many users can be provided application and hardware as needed using this. But, lately various attack using weak point of virtualization technology are increasing rapidly. In this study, we analyze type and weak point of virtualization technology, the point of cloud computing. And we study about function and the position which intrusion detection system has to prepare in order to detect and block attack using this.