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The PASCAL Visual Object Classes Challenge

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

The number of changing pixel rate (NPCR) and the unified averaged changed intensity (UACI) are two most common quantities used to evaluate the strength of image encryption algorithms/ciphers with respect to differential attacks. Conventionally, a high NPCR/UACI score is usually interpreted as a high resistance to differential attacks. However, it is not clear how high NPCR/UACI is such that the image cipher indeed has a high security level. In this paper, we approach this problem by establishing a mathematical model for ideally encrypted images and then derive expectations and variances of NPCR and UACI under this model. Further, these theoretical values are used to form statistical hypothesis NPCR and UACI tests. Critical values of tests are consequently derived and calculated both symbolically and numerically. As a result, the question of whether a given NPCR/UACI score is sufficiently high such that it is not discernible from ideally encrypted images is answered by comparing actual NPCR/UACI scores with corresponding critical values. Experimental results using the NPCR and UACI randomness tests show that many existing image encryption methods are actually not as good as they are purported, although some methods do pass these randomness tests.

NPCR and UACI Randomness Tests for Image Encryption

A new 1D chaotic system for image encryption

Color image encryption based on paired interpermuting planes

In this paper, the properties of the classical confusion-substitution structure and some recently proposed pseudorandom number generators using one-dimensional chaotic maps are investigated. To solve the low security problem of the original structure, a new bit-level cellular automata strategy is used to improve the sensitivity to the cryptosystem. We find that the new evolution effects among different generations of cells in cellular automata can significantly improve the diffusion effect. After this, a new one-dimensional chaotic map is proposed, which is constructed by coupling the logistic map and the Bernoulli map (LBM). The new map exhibits a much better random behavior and is more efficient than comparable ones. Due to the favorable properties of the new map and cellular automata algorithm, we propose a new image-encryption algorithm in which three-dimensional bit-level permutation with LBM is employed in the confusion phase. Simulations are carried out, and the results demonstrate the superior security and high efficiency of the proposed scheme.

A Symmetric Image Encryption Algorithm Based on a Coupled Logistic–Bernoulli Map and Cellular Automata Diffusion Strategy

In this study, we describe a system-level multiple refactoring algorithm, which can identify the move method, move field, and extract class refactoring opportunities automatically according to the principle of “high cohesion and low coupling.” The algorithm works by merging and splitting related classes to obtain the optimal functionality distribution from the system-level. Furthermore, we present a weighted clustering algorithm for regrouping the entities in a system based on merged method-level networks. Using a series of preprocessing steps and preconditions, the “bad smells” introduced by cohesion and coupling problems can be removed from both the non-inheritance and inheritance hierarchies without changing the code behaviors. We rank the refactoring suggestions based on the anticipated benefits that they bring to the system. Based on comparisons with related research and assessing the refactoring results using quality metrics and empirical evaluation, we show that the proposed approach performs well in different systems and is beneficial from the perspective of the original developers. Finally, an open source tool is implemented to support the proposed approach.

Automatic Software Refactoring via Weighted Clustering in Method-Level Networks

Intensive use of libraries in Java projects brings potential risk of dependency conflicts, which occur when a project directly or indirectly depends on multiple versions of the same library or class. When this happens, JVM loads one version and shadows the others. Runtime exceptions can occur when methods in the shadowed versions are referenced. Although project management tools such as Maven are able to give warnings of potential dependency conflicts when a project is built, developers often ask for crashing stack traces before examining these warnings. It motivates us to develop Riddle, an automated approach that generates tests and collects crashing stack traces for projects subject to risk of dependency conflicts. Riddle, built on top of Asm and Evosuite, combines condition mutation, search strategies and condition restoration. We applied Riddle on 19 real-world Java projects with duplicate libraries or classes. We reported 20 identified dependency conflicts including their induced crashing stack traces and the details of generated tests. Among them, 15 conflicts were confirmed by developers as real issues, and 10 were readily fixed. The evaluation results demonstrate the effectiveness and usefulness of Riddle.

Could I have a stack trace to examine the dependency conflict issue

Recently, the robustness of networks under cascading failure has attracted extensive attention. Different from previous studies, we concentrate on how to improve the robustness of the networks from the perspective of intelligent optimization. We establish two multi-objective optimization models that comprehensively consider the operational cost of the edges in the networks and the robustness of the networks. The NNIA (Non-dominated Neighbor Immune Algorithm) is applied to solve the optimization models. We finished simulations of the Barabasi–Albert (BA) network and Erdos–Renyi (ER) network. In the solutions, we find the edges that can facilitate the propagation of cascading failure and the edges that can suppress the propagation of cascading failure. From the conclusions, we take optimal protection measures to weaken the damage caused by cascading failures. We also consider actual situations of operational cost feasibility of the edges. People can make a more practical choice based on the operational cost. Our work will be helpful in the design of highly robust networks or improvement of the robustness of networks in the future.

Hai Yu

Papers

Color image encryption based on paired interpermuting planes

A Symmetric Image Encryption Algorithm Based on a Coupled Logistic–Bernoulli Map and Cellular Automata Diffusion Strategy

Automatic Software Refactoring via Weighted Clustering in Method-Level Networks

Could I have a stack trace to examine the dependency conflict issue

Optimization of cascading failure on complex network based on NNIA