Chaos-based algorithms have been widely adopted to encrypt images. But previous chaos-based encryption schemes are not secure enough for batch image encryption, for images are usually encrypted using a single sequence. Once an encrypted image is cracked, all the others will be vulnerable. In this paper, we proposed a batch image encryption scheme into which a stacked autoencoder (SAE) network was introduced to generate two chaotic matrices; then one set is used to produce a total shuffling matrix to shuffle the pixel positions on each plain image, and another produces a series of independent sequences of which each is used to confuse the relationship between the permutated image and the encrypted image. The scheme is efficient because of the advantages of parallel computing of SAE, which leads to a significant reduction in the run-time complexity; in addition, the hybrid application of shuffling and confusing enhances the encryption effect. To evaluate the efficiency of our scheme, we compared it with the prevalent “logistic map,” and outperformance was achieved in running time estimation. The experimental results and analysis show that our scheme has good encryption effect and is able to resist brute-force attack, statistical attack, and differential attack.

Based on Restricted Boltzmann Machines (RBMs), an improved pseudo-stochastic sequential cipher generator is proposed. It is effective and efficient because of the two advantages: this generator includes a stochastic neural network that can perform the calculation in parallel, that is to say, all elements are calculated simultaneously; unlimited number of sequential ciphers can be generated simultaneously for multiple encryption schemas. The periodicity and the correlation of the output sequential ciphers meet the requirements for the design of encrypting s equential data. In the experiment, the generated sequential cipher is used to encrypt the image, and better performance is achieved in terms of the key space analysis, the correlation analysis, the sensitivity analysis and the differential attack. The expe rimental result is promising that could promote the development of image protection in computer security. IntroductionIn the field of communication and encryption for sequential data, sequential cipher generation algorithms have been one of the main technology used for military and diplomatic occasions. As a kind of symmetric encryption algorithm, sequential ciphers have the following characteristics: easy to be implemented , simple implementation with hardware, fast in encryption and decryption processing, none or limited error propagation. Shannon proved the one-time pad encryption system was safe [1]. It plays an important role in promoting the development of the sequential ciphering technology. The development of the sequential cipher technology has been attempting to imitate the one-time pad scheme, i.e., the one-time pad encryption system is the prototype of the sequential ciphering system. In order to cipher the sequential data, a stochastic sequence, determined by a cipher code, will be generated at first. The algorithms of generating stochastic sequential ciphers can be roughly divided into two categories: Linear Fee dback Shift Register sequential cipher generators (LFSR) and nonlinear sequential cipher generators. LFSR

Workflow scheduling is crucial to the efficient operation of cloud platforms, and has attracted a lot of attention. Up to now, many algorithms have been reported to schedule workflows with budget constraints, so as to optimize workflows' makespan on cloud resources. Nevertheless, the hourly-based billing model in cloud computing is an ongoing challenge for workflow scheduling that easily results in higher makespan or even infeasible solutions. Besides, due to data constraints among workflow tasks, there must be a lot of idle slots in cloud resources. Few works adequately exploit these idle slots to duplicate tasks' predecessors to shorten their completion time, thereby minimizing workflow's makespan while ensuring its budget constraint. Motivated by these, we propose a task duplication based scheduling algorithm, namely TDSA, to optimize makespan for budget-constrained workflows in cloud platforms. In TDSA, two novel mechanisms are devised: 1) a dynamic sub-budget allocation mechanism, it is responsible for recovering unused budget of scheduled workflow tasks and redistributing remaining budget, which is conducive to using more expensive/powerful cloud resources to accelerate completion time of unscheduled tasks; and 2) a duplication-based task scheduling mechanism, which strives to exploit idle slots on resources to selectively duplicate tasks' predecessors, such advancing these tasks' completion time while trying to ensuring their sub-budget constraints. At last, we carry out four groups of experiments, three groups on randomly generated workflows and another one on actual workflows, to compare the proposed TDSA with four baseline algorithms. Experimental results confirm that the TDSA has an overwhelming superiority in advancing the workflows' makespan and improving the utilization of cloud computing resources. INDEX TERMS Cloud computing, task duplication, workflow scheduling, resource provision, heuristic mechanism.

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