• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.19-28
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• 2017

False data injection attacks have recently been introduced as one of important issues related to cyber-attacks on electric power grids. These attacks aim to compromise the readings of multiple power meters in order to mislead the operation and control centers. Recent studies have shown that if a malicious attacker has complete knowledge of the power grid topology and branch admittances, s/he can adjust the false data injection attack such that the attack remains undetected and successfully passes the bad data detection tests that are used in power system state estimation. In this paper, we investigate that a practical false data injection attack is essentially a cyber-attack with uncertain information due to the attackers lack of knowledge with respect to the power grid parameters because the attacker has limited physical access to electric facilities and limited resources to compromise meters. We mathematically formulated a method of identifying the most vulnerable locations to false data injection attack. Furthermore, we suggest minimum topology changes or phasor measurement units (PMUs) installation in the given power grids for mitigating such attacks and indicate a new security metrics that can compare different power grid topologies. The proposed metrics for performance is verified in standard IEEE 30-bus system. We show that the robustness of grids can be improved dramatically with minimum topology changes and low cost.

• Convergence Security Journal
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• v.15 no.2
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• pp.57-62
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• 2015

IP QoS is not required to overcome the limitations of the existing Best Effort Service to connect to the explosion of the Internet traffic revenue. To IP QoS requirements of next-generation communication network, Metric Sizing Methodology is very important. However, IP networks have been developed with a focus gender flexibility and scalability than the QoS. Therefore, it is necessary to secure the quality measures for different existing IP technology to apply QoS in IP networks. When establishing the connection quality and transmission quality, based on the IP QoS(Quality of Service) objective data quality metrics can be obtained by analyzing the communication quality hindrance. Understanding the communication quality level may evaluate quality sensitive area and quality hindrance. Establish effective quality metrics can be expected to promote effective and customer satisfaction through improved quality, improved call quality for this issue.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1359-1368
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• 2021

Steganography is a science of embedding secret data into innocent data and its goal is to conceal the existence of a carrier data. Many research on Steganography has been proposed by various hiding and detection techniques that are based on different algorithms. On the other hand, very few studies have been conducted to analyze the performance of each Steganography software. This paper describes five different Steganography software, each having its own algorithms, and analyzes the difference of each inherent feature. Image quality metrics of Peak Signal to Noise Ratio (PSNR) and Structural SIMilarity (SSIM) are used to define its performance of each Steganography software. We extracted PSNR and SSIM results of a quantitative amount of embedded output images for those five Steganography software. The results will show the optimal steganography software based on the evaluation metrics and ultimately contribute to forensics.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.319-328
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• 2021

Parallel administration of numerous drugs increases Drug-Drug Interaction (DDI) because one drug might affect the activity of other drugs. DDI causes negative or positive impacts on therapeutic output. So there is a need to discover DDI to enhance the safety of consuming drugs. Though there are several DDI system exist to predict an interaction but nowadays it becomes impossible to maintain with a large number of biomedical texts which is getting increased rapidly. Mostly the existing DDI system address classification issues, and especially rely on handcrafted features, and some features which are based on particular domain tools. The objective of this paper to predict DDI in a way to avoid adverse effects caused by the consumed drugs, to predict similarities among the drug, Drug pair similarity calculation is performed. The best optimal weight is obtained with the support of KHA. LSTM function with weight obtained from KHA and makes bets prediction of DDI. Our methodology depends on (LSTM-KHA) for the detection of DDI. Similarities among the drugs are measured with the help of drug pair similarity calculation. KHA is used to find the best optimal weight which is used by LSTM to predict DDI. The experimental result was conducted on three kinds of dataset DS1 (CYP), DS2 (NCYP), and DS3 taken from the DrugBank database. To evaluate the performance of proposed work in terms of performance metrics like accuracy, recall, precision, F-measures, AUPR, AUC, and AUROC. Experimental results express that the proposed method outperforms other existing methods for predicting DDI. LSTMKHA produces reasonable performance metrics when compared to the existing DDI prediction model.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.308-318
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• 2022

Noise is a serious issue. While sending images via electronic communication, Impulse noise, which is created by unsteady voltage, is one of the most common noises in digital communication. During the acquisition process, pictures were collected. It is possible to obtain accurate diagnosis images by removing these noises without affecting the edges and tiny features. The New Average High Noise Density Median Filter. (HNDMF) was proposed in this paper, and it operates in two steps for each pixel. Filter can decide whether the test pixels is degraded by SPN. In the first stage, a detector identifies corrupted pixels, in the second stage, an algorithm replaced by noise free processed pixel, the New average suggested Filter produced for this window. The paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. In this paper the comparison of known image denoising is discussed and a new decision based weighted median filter used to remove impulse noise. Using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structure Similarity Index Method (SSIM) metrics, the paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. A detailed simulation process is performed to ensure the betterment of the presented model on the Mini-MIAS dataset. The obtained experimental values stated that the HNDMF model has reached to a better performance with the maximum picture quality. images affected by various amounts of pretend salt and paper noise, as well as speckle noise, are calculated and provided as experimental results. According to quality metrics, the HNDMF Method produces a superior result than the existing filter method. Accurately detect and replace salt and pepper noise pixel values with mean and median value in images. The proposed method is to improve the median filter with a significant change.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1449-1461
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• 2018

As the number of software vulnerabilities grows year by year, attacks on software are also taking place a lot. As a result, the security administrator must identify and patch vulnerabilities in the software. However, it is important to prioritize the patches because patches for all vulnerabilities are realistically hard. In this paper, we propose a scoring system that expands the scale of risk assessment metric by taking into consideration attack patterns or weaknesses cause vulnerabilities with the vulnerability information provided by the NIST(National Institute of Standards and Technology). The proposed scoring system is expanded based on the CWSS and uses only public vulnerability information to utilize easily for any company. In this paper, we applied the automated scoring system to software vulnerabilities, and showed the expanded metrics with consideration for influence of attack pattern and weakness are meaningful.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.847-859
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• 2023

With the recent increase in damage caused by malcious codes using software vulnerabilities in Korea, it is essential to install anti-virus to prevent malicious codes, However, it is not easy for general users to know which anti-virus product has good performance or whether it is suitable for their environment. There are many institutions that provide information on anti-virus performance outside of korea, and these institutions have established their own test environments and test evaluation items, but they do not disclose detailed test environment information, detailed test evaluation items, and results. In addition, existing quality evaluation studies are not suitable for the evaluating the latest anti-virus products because there are many evaluation criteria that do not meet anti-virus product evaluation. Therefore, this paper establishes detailed anti-virus evaluation metrics suitable for the latest anti-virus evaluation and applies them to 9 domestic and foreign anti-virus products to verify the functions and performance of anti-viruses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1533-1556
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• 2017

The concept of trust in vehicular ad hoc networks (VANETs) is usually utilized to assess the trustworthiness of the received data as well as that of the sending entities. The quality of safety applications in VANETs largely depends on the trustworthiness of exchanged data. In this paper, we propose a self-organized distributed trust computing framework (DTCF) for VANETs to compute the trustworthiness of each vehicle, in order to filter out malicious nodes and recognize fully trusted nodes. The proposed framework is solely based on the investigation of the direct experience among vehicles without using any recommendation system. A tier-based dissemination technique for data messages is used to filter out non authentic messages and corresponding events before even going farther away from the source of the event. Extensive simulations are conducted using Omnet++/Sumo in order to investigate the efficiency of our framework and the consistency of the computed trust metrics in both urban and highway environments. Despite the high dynamics in such networks, our proposed DTCF is capable of detecting more than 85% of fully trusted vehicles, and filtering out virtually all malicious entities. The resulting average delay to detect malicious vehicles and fraudulent data is showed to be less than 1 second, and the computed trust metrics are shown to be highly consistent throughout the network.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.342-352
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• 2021

Multicast Routings is a big challenge due to limitations such as node power and bandwidth Mobile Ad-hoc Network (MANET). The path to be chosen from the source to the destination node requires protocols. Multicast protocols support group-oriented operations in a bandwidth-efficient way. While several protocols for multi-cast MANETs have been evolved, security remains a challenging problem. Consequently, MANET is required for high quality of service measures (QoS) such infrastructure and application to be identified. The goal of a MANETs QoS-aware protocol is to discover more optimal pathways between the network source/destination nodes and hence the QoS demands. It works by employing the optimization method to pick the route path with the emphasis on several QoS metrics. In this paper safe routing is guaranteed using the Secured Multicast Routing offered in MANET by utilizing the Ant Colony Optimization (ACO) technique to integrate the QOS-conscious route setup into the route selection. This implies that only the data transmission may select the way to meet the QoS limitations from source to destination. Furthermore, the track reliability is considered when selecting the best path between the source and destination nodes. For the optimization of the best path and its performance, the optimized algorithm called the micro artificial bee colony approach is chosen about the probabilistic ant routing technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4522-4536
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• 2020

Nowadays, cloud is the fastest emerging technology in the IT industry. We can store and retrieve data from the cloud. The most frequently occurring problems in the cloud are security and privacy preservation of data. For improving its security, secret information must be protected from various illegal accesses. Numerous traditional cryptography algorithms have been used to increase the privacy in preserving cloud data. Still, there are some problems in privacy protection because of its reduced security. Thus, this article proposes an ElGamal Elliptic Curve (EGEC) Homomorphic encryption scheme for safeguarding the confidentiality of data stored in a cloud. The Users who hold a data can encipher the input data using the proposed EGEC encryption scheme. The homomorphic operations are computed on encrypted data. Whenever user sends data access permission requests to the cloud data storage. The Cloud Service Provider (CSP) validates the user access policy and provides the encrypted data to the user. ElGamal Elliptic Curve (EGEC) decryption was used to generate an original input data. The proposed EGEC homomorphic encryption scheme can be tested using different performance metrics such as execution time, encryption time, decryption time, memory usage, encryption throughput, and decryption throughput. However, efficacy of the ElGamal Elliptic Curve (EGEC) Homomorphic Encryption approach is explained by the comparison study of conventional approaches.