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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

In recent years, chaos-based image cipher has been widely studied and a growing number of schemes based on permutation-diffusion architecture have been proposed. However, most of the existing schemes are based on low-dimensional chaotic systems and have the drawbacks of small key space and weak security. In this paper, we present a security improved image cipher which utilises chaotic Baker map and hyperchaotic Lorenz system for permutation and diffusion. Compared with ordinary chaotic systems, hyperchaotic systems, with more complex dynamical behaviours and number of system variables, offer greater potential for secure cryptosystem construction. In diffusion stage, a plain-image related key stream generation scheme is introduced, which further improves the security against known/chosen plaintext attack. Extensive security analysis has been performed on the proposed scheme, including the most important ones like key space analysis, key sensitivity analysis, differential analysis and various statistical analyses, which has demonstrated the satisfactory security of the proposed scheme.

A security improved image encryption scheme based on chaotic Baker map and hyperchaotic Lorenz system

Java projects are often built on top of various third-party libraries If multiple versions of a library exist on the classpath, JVM will only load one version and shadow the others, which we refer to as dependency conflicts This would give rise to semantic conflict (SC) issues, if the library APIs referenced by a project have identical method signatures but inconsistent semantics across the loaded and shadowed versions of libraries SC issues are difficult for developers to diagnose in practice, since understanding them typically requires domain knowledge Although adapting the existing test generation technique for dependency conflict issues, Riddle, to detect SC issues is feasible, its effectiveness is greatly compromised This is mainly because Riddle randomly generates test inputs, while the SC issues typically require specific arguments in the tests to be exposed To address that, we conducted an empirical study of 316 real SC issues to understand the characteristics of such specific arguments in the test cases that can capture the SC issues Inspired by our empirical findings, we propose an automated testing technique Sensor, which synthesizes test cases using ingredients from the project under test to trigger inconsistent behaviors of the APIs with the same signatures in conflicting library versions Our evaluation results show that Sensor is effective and useful: it achieved a Precision of 0898 and a Recall of 0725 on open-source projects and a Precision of 0821 on industrial projects; it detected 306 semantic conflict issues in 50 projects, 704% of which had been confirmed as real bugs, and 842% of the confirmed issues have been fixed quickly

Will Dependency Conflicts Affect My Program's Semantics?

Using reliability risk analysis to prioritize test cases

Superpixels are widely used in computer vision applications, as they conserve the running costs of subsequent processing while preserving the original performance. In most of the existing algorithms, the boundary adherence and the compactness of superpixels are necessarily inter-inhibitive because the color/gradient information is balanced against the position constraints, and the set criteria define all pixels indiscriminately. In this paper, we present a two-phase superpixel segmentation method based on the watershed transformation. After designing a new approach for calculating the flooding priority, we propose a new strategy with two distinct criteria for global and local refinement of the boundary pixels. These criteria reduce the compromise between the boundary adherence and compactness. Unlike the indiscriminate standards, our method applies different treatments to pixels in different environments, preserving the color homogeneity in content-rich areas while improving the regularity of the superpixels in content-plain regions. The superior accuracy and computing time of our proposed method are verified in comparison experiments with several state-of-the-art methods.

Watershed-Based Superpixels With Global and Local Boundary Marching

Online fountain codes have been proven to require lower overhead and fewer feedbacks than growth codes for successful decoding. In an attempt to improve the intermediate symbol recovery rate, the authors propose sending a number of degree-1 input symbols prior to the build-up phase based on a simple application of probability theory. In addition, during the completion phase, received encoded symbols with three neighbouring white (un-decoded) symbols are retained for decoding and updating the decoding graph later. The performance and characteristics of the proposed improved online fountain codes are compared to those of the original online fountain codes over an erasure channel. Simulation results reveal that the improved online fountain codes outperform the original fountain codes in terms of intermediate symbol recovery rate, average encoded symbols required to be generated by the sender, average feedback transmissions, and encoding/decoding efficiency.

Hai Yu

Papers

A security improved image encryption scheme based on chaotic Baker map and hyperchaotic Lorenz system

Will Dependency Conflicts Affect My Program's Semantics?

Using reliability risk analysis to prioritize test cases

Watershed-Based Superpixels With Global and Local Boundary Marching

Improved online fountain codes