• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.4122-4144
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• 2021

In this fast-paced technological world, the Internet of Things is a ground breaking technology which finds an immense role in the present electronic world which includes different embedded sensors, devices and most other things which are connected to the Internet. The IoT devices are designed in a way that it helps to collect various forms of data from varied sources and transmit them in digitalized form. In modern era of IoT technology data security is a trending issue which greatly affects the confidentiality of important information. Keeping the issue in mind a novel light encryption strategy known as LCB is designed for IoT devices for optimal security. LCB exploits the benefits of Feistel structure and the architectural benefits of substitution permutation network both to give more security. Moreover, this newly designed technique is tested on (Virtex-7) XC7VX330T FPGA board and it takes much little area of 224 GE (Gate Equivalent) and is extremely fast with very less combinational path delay of 0.877 ns. An in-depth screening confirms the proposed work to promise more security to counter cryptographic attacks. Lastly the Avalanche Effect (AE) of LCB showed as 63.125% and 63.875% when key and plaintext (PT) are taken into consideration respectively.

• 전기학회논문지
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• 제63권5호
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• pp.676-682
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• 2014

In this paper, precipitation echo(PRE) and non-precipitaion echo(N-PRE)(including ground echo and clear echo) through weather radar data are identified with the aid of neuro-fuzzy algorithm. The accuracy of the radar information is lowered because meteorological radar data is mixed with the PRE and N-PRE. So this problem is resolved by using RBFNN and judgement module. Structure expression of weather radar data are analyzed in order to classify PRE and N-PRE. Input variables such as Standard deviation of reflectivity(SDZ), Vertical gradient of reflectivity(VGZ), Spin change(SPN), Frequency(FR), cumulation reflectivity during 1 hour(1hDZ), and cumulation reflectivity during 2 hour(2hDZ) are made by using weather radar data and then each characteristic of input variable is analyzed. Input data is built up from the selected input variables among these input variables, which have a critical effect on the classification between PRE and N-PRE. Echo judgment module is developed to do echo classification between PRE and N-PRE by using testing dataset. Polynomial-based radial basis function neural networks(RBFNNs) are used as neuro-fuzzy algorithm, and the proposed neuro-fuzzy echo pattern classifier is designed by combining RBFNN with echo judgement module. Finally, the results of the proposed classifier are compared with both CZ and DZ, as well as QC data, and analyzed from the view point of output performance.

• International Journal of Computer Science & Network Security
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• 제22권11호
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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.

• 정보보호학회논문지
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• 제30권3호
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• pp.325-336
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• 2020

비선형 불변 공격은 비교적 간단한 구조의 키 스케줄을 갖는 경량 블록암호에서 필수적으로 고려되어야 할 공격이다. 간단한 구조의 키 스케줄을 갖는 경량 블록암호가 비선형 불변 공격에 저항성을 보이는 방법으로 가장 잘 알려진 것은 라운드 키 간의 차분 중 알려진 것들의 집합에서 선형계층에 대해 불변인 최소의 선형공간의 크기가 블록 크기와 같은지를 확인하는 것이다. 본 논문에서는 다음과 같은 연구 결과를 제시한다. 설계자 관점에서 비트 순열을 선형계층으로 사용하는 SPN 구조 경량 블록암호는 라운드 키 간의 차분의 종류가 한가지여도 비선형 불변 공격에 안전할 수 있음을 증명하고, 그러한 비트 순열의 형태와 개수를 제안한다. 또한, PRESENT 구조 블록암호는 비선형 불변 공격에 저항성을 갖기 위해 적어도 두 종류의 라운드 키 간의 차분이 필요함을 전수조사를 통해 보이며, 두 종류의 라운드 키 간의 차분을 필요로 하는 비트 순열을 사용해도 차분 공격에 대한 저항성이 오히려 증가할 수 있음을 보인다. 마지막으로 GIFT의 S-box를 사용하면서 BOGI 설계 논리를 유지하는 모든 비트 순열의 불변 성분 분포를 통해, 변형된 GIFT 구조 블록암호는 비선형 불변 공격에 저항성을 갖기 위해 적어도 8종류의 라운드 키 간의 차분이 필요함을 보인다.