Web applications are the objects most targeted by attackers. The technique most often used to attack web applications is SQL injection. This attack is categorized as dangerous because it can be used to illegally retrieve, modify, delete data, and even take over databases and web applications. To prevent SQL injection attacks from being executed by the database, a system that can identify attack patterns and can learn to detect new patterns from various attack patterns that have occurred is required. This study aims to build a system that acts as a proxy to prevent SQL injection attacks using the Hybrid Method which is a combination of SQL Injection Free Secure (SQL-IF) and Naïve Bayes methods. Tests were carried out to determine the level of accuracy, the effect of constants (K) on SQL-IF, and the number of datasets on Naïve Bayes on the accuracy and efficiency (average load time) of web pages. The test results showed that the Hybrid Method can improve the accuracy of SQL injection attack prevention. Smaller K values and larger dataset will produce better accuracy. The Hybrid Method produces a longer average web page load time than using only the SQL-IF or Naïve Bayes methods.
The property of shift-invariance associated with a a support of arbitrary shape. The SA-DCT is used in good directional selectivity is important for the application of a conjunction with the Anisotropic Local Polynomial wavelet transform, (WT), in many fields of image processing.Approximation (LPA) -Intersection of Confidence Intervals Generally, complex wavelet transforms, like for example the (ICI) technique, which defines the shape of the transform Double Tree Complex Wavelet Transform, (DTCWT), have these good properties. In this paper we propose the use of a new suppondin a pointwe ap e mnner. Snersupports implementation of such a WT, recently introduced, namely the crespondn etoiffe s are igera l oeapping hyperanalytic wavelet transform, (HWT), in denoising the local estimates are averaged together using adaptive applications. The proposed denoising method is very simple, weights that depend on the region's statistics. The denoising implying three steps: the computation of the forward WT, the system proposed in [3] is a M\AP filter that acts in the spatial filtering in the wavelets domain and the computation of the domain. It makes a different treatment of regions with inverse WT, (IWT). The goal of this paper is the association of a different homogeneity degree. These regions can be treated new implementation of the HWT, recently proposed, with a independent with the same M\AP filter choosing between maximum a posteriori (MAP) filter. Some simulation examples different prior models. The multi-resolution analysis and comparisons prove the performances of the proposed performed by the WT has been shown to be a powerful tool to denoising method. achieve good denoising. In the wavelet domain, the noise is uniformly spread throughout the coefficients, while most of Keywords -Directional selectivity, Hyperanalytic wavelet th img inomto is cocntae intefwlretoe transfom,Imag deosig Maiu a potrir fle. the image information iS concentrated in the few largest ones transform, ImaednoiingMaimmaposeri(sparsity of the wavelet representation), [4-7]. The corresponding denoising methods have three steps, [1]: 1) The computation of the forward WT, 2) the filtering of the wavelet coefficients, 3) the computation of the IWT of the During acquisition and transmission, imagesareof result obtained. Numerous WTs can be used to operate these Dfuringbyacquiition andis tr cansm ,images Garesftn treatments. The first one was the Discrete Wavelet Transform, cotoruthe byative.The nise tt can beag deledsing as gaussian DWT, [1]. It has three main disadvantages, [8]: lack of shift mostoftheno tme.uthe aoime ofvel, a himge-ren ingalgoithm is invariance, lack of symmetry of the mother wavelets and poor then to reduce the noise level, while preserving the image dietoa.eetv hs iavnae a be dimnihe features. Such a system must realize a big noise reduction in ty g the homogeneous regions and the preservation of the details using a complex wavelet transform [8, 9]. Over twenty years * * * -r-* r~~~~ago, Grossman and Morlet [10] developed the Co...
The need for data security arises because of the many threats made by outside parties to retrieve data and use it for personal interests. Security for medical images is carried out because medical images store patient health information data that is confidential. In this study, the image data used specifically uses radiological medical images. There are many techniques and algorithms that can be used to secure image data. This study uses the AES and Camellia algorithms which in their application use several different operating modes. To measure the quality of the encrypted image, the randomness level of the image was tested using the NPCR and UACI tests. Evaluation is used to determine the best algorithm and operating mode for encryption. Based on the measurement of image randomness on AES CBC, AES CFB, AES OFB, Camellia ECB, Camellia CBC, and Camellia OFB with NPCR values for encrypted images of 99.60%, 99.608%, 99.6093%, 99.6296%, 99.6072 %, and 99.6124%. Measurement of image randomness on AES CBC, AES CFB, AES OFB, Camellia ECB, Camellia CBC, and Camellia OFB with UACI values for encrypted images of 34.714%, 34.754%, 34.603%, 34.983%, 34.615%, and 34.707%.
Cloud computing is a technology that has powerful computing resources that can be applied to many organizations by using dynamic scalability as a virtual service source via the internet. SMK Ma'arif NU 1 Kembaran has a 2013 TKJ curriculum. The curriculum has topics such as Computer Assembly, Network Operating Systems and Server Administration. In the subject of Network Operating Systems, there is no subject that discusses cloud computing technology. This technology will have an impact on the average score of students before training to make VPN with cloud computing, namely 83, 12 and after training to 89.06 so that there is a descriptive increase. The hypothesis used is a two-way hypothesis so that it uses two tails with the result t table that is 2.039513 with a p value of 0.01249. Because the p value is smaller than alpha 5% or by looking at the value | t count | > t table then Ho is rejected. This means that there is a significant difference in the level of understanding of students before and after training to make VPN with cloud computing.Cloud computing is a technology that has powerful computing resources that can be applied to many organizations by using dynamic scalability as a virtual service source via the internet. SMK Ma'arif NU 1 Kembaran has a 2013 TKJ curriculum. The curriculum has topics such as Computer Assembly, Network Operating Systems and Server Administration. In the subject of Network Operating Systems, there is no subject that discusses cloud computing technology. This technology will have an impact on the average score of students before training to make VPN with cloud computing, namely 83, 12 and after training to 89.06 so that there is a descriptive increase. The hypothesis used is a two-way hypothesis so that it uses two tails with the result t table that is 2.039513 with a p value of 0.01249. Because the p value is smaller than alpha 5% or by looking at the value | t count | > t table then Ho is rejected. This means that there is a significant difference in the level of understanding of students before and after training to make VPN with cloud computing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.