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The Analysis of Cipher Padding Problem for Message Recovery Security Function of Honey Encryption
http://doi.org/10.5626/JOK.2017.44.6.637
Honey Encryption (HE) is a technique to overcome the weakness of a brute-force attack of the existing password-based encryption (PBE). By outputting a plausible plaintext even if the wrong key is entered, it provides message recovery security which an attacker can tolerate even if the attacker tries a brute-force attack against a small entropy secret key. However, application of a cipher that requires encryption padding to the HE present a bigger problem than the conventional PBE method. In this paper, we apply a typical block cipher (AES-128) and a stream cipher (A5 / 1) to verify the problem of padding through the analysis of the sentence frequency and we propose a safe operation method of the HE.
Repeated Cropping based on Deep Learning for Photo Re-composition
Eunbin Hong, Junho Jeon, Seungyong Lee
This paper proposes a novel aesthetic photo recomposition method using a deep convolutional neural network (DCNN). Previous recomposition approaches define the aesthetic score of photo composition based on the distribution of salient objects, and enhance the photo composition by maximizing the score. These methods suffer from heavy computational overheads, and often fail to enhance the composition because their optimization depends on the performance of existing salient object detection algorithms. Unlike previous approaches, we address the photo recomposition problem by utilizing DCNN, which shows remarkable performance in object detection and recognition. DCNN is used to iteratively predict cropping directions for a given photo, thus generating an aesthetically enhanced photo in terms of composition. Experimental results and user study show that the proposed framework can automatically crop the photo to follow specific composition guidelines, such as the rule of thirds.
Robust Anti Reverse Engineering Technique for Protecting Android Applications using the AES Algorithm
Classes.dex, which is the executable file for android operation system, has Java bite code format, so that anyone can analyze and modify its source codes by using reverse engineering. Due to this characteristic, many android applications using classes.dex as executable file have been illegally copied and distributed, causing damage to the developers and software industry. To tackle such ill-intended behavior, this paper proposes a technique to encrypt classes.dex file using an AES(Advanced Encryption Standard) encryption algorithm and decrypts the applications encrypted in such a manner in order to prevent reverse engineering of the applications. To reinforce the file against reverse engineering attack, hash values that are obtained from substituting a hash equation through the combination of salt values, are used for the keys for encrypting and decrypting classes.dex. The experiments demonstrated that the proposed technique is effective in preventing the illegal duplication of classes.dex-based android applications and reverse engineering attack. As a result, the proposed technique can protect the source of an application and also prevent the spreading of malicious codes due to repackaging attack.
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