Energy-Efficient Algorithms

We initiate the systematic study of the energy complexity of algorithms (in addition to time and space complexity) based on Landauer's Principle in physics, which gives a lower bound on the amount of energy a system must dissipate if it destroys information. We propose energy-aware variations of three standard models of computation: circuit RAM, word RAM, and transdichotomous RAM. On top of these models, we build familiar high-level primitives such as control logic, memory allocation, and garbage collection with zero energy complexity and only constant-factor overheads in space and time complexity, enabling simple expression of energy-efficient algorithms. We analyze several classic algorithms in our models and develop low-energy variations: comparison sort, insertion sort, counting sort, breadth-first search, Bellman-Ford, Floyd-Warshall, matrix all-pairs shortest paths, AVL trees, binary heaps, and dynamic arrays. We explore the time/space/energy trade-off and develop several general techniques for analyzing algorithms and reducing their energy complexity. These results lay a theoretical foundation for a new field of semi-reversible computing and provide a new framework for the investigation of algorithms.Comment: 40 pages, 8 pdf figures, full version of work published in ITCS 201

Conclave: secure multi-party computation on big data (extended TR)

Secure Multi-Party Computation (MPC) allows mutually distrusting parties to run joint computations without revealing private data. Current MPC algorithms scale poorly with data size, which makes MPC on "big data" prohibitively slow and inhibits its practical use. Many relational analytics queries can maintain MPC's end-to-end security guarantee without using cryptographic MPC techniques for all operations. Conclave is a query compiler that accelerates such queries by transforming them into a combination of data-parallel, local cleartext processing and small MPC steps. When parties trust others with specific subsets of the data, Conclave applies new hybrid MPC-cleartext protocols to run additional steps outside of MPC and improve scalability further. Our Conclave prototype generates code for cleartext processing in Python and Spark, and for secure MPC using the Sharemind and Obliv-C frameworks. Conclave scales to data sets between three and six orders of magnitude larger than state-of-the-art MPC frameworks support on their own. Thanks to its hybrid protocols, Conclave also substantially outperforms SMCQL, the most similar existing system.Comment: Extended technical report for EuroSys 2019 pape

Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME

We present a heuristic based algorithm to induce \textit{nonmonotonic} logic programs that will explain the behavior of XGBoost trained classifiers. We use the technique based on the LIME approach to locally select the most important features contributing to the classification decision. Then, in order to explain the model's global behavior, we propose the LIME-FOLD algorithm ---a heuristic-based inductive logic programming (ILP) algorithm capable of learning non-monotonic logic programs---that we apply to a transformed dataset produced by LIME. Our proposed approach is agnostic to the choice of the ILP algorithm. Our experiments with UCI standard benchmarks suggest a significant improvement in terms of classification evaluation metrics. Meanwhile, the number of induced rules dramatically decreases compared to ALEPH, a state-of-the-art ILP system

State space c-reductions for concurrent systems in rewriting logic

We present c-reductions, a state space reduction technique. The rough idea is to exploit some equivalence relation on states (possibly capturing system regularities) that preserves behavioral properties, and explore the induced quotient system. This is done by means of a canonizer function, which maps each state into a (non necessarily unique) canonical representative of its equivalence class. The approach exploits the expressiveness of rewriting logic and its realization in Maude to enjoy several advantages over similar approaches: exibility and simplicity in the definition of the reductions (supporting not only traditional symmetry reductions, but also name reuse and name abstraction); reasoning support for checking and proving correctness of the reductions; and automatization of the reduction infrastructure via Maude's meta-programming features. The approach has been validated over a set of representative case studies, exhibiting comparable results with respect to other tools

Bayesian computational methods

In this chapter, we will first present the most standard computational challenges met in Bayesian Statistics, focussing primarily on mixture estimation and on model choice issues, and then relate these problems with computational solutions. Of course, this chapter is only a terse introduction to the problems and solutions related to Bayesian computations. For more complete references, see Robert and Casella (2004, 2009), or Marin and Robert (2007), among others. We also restrain from providing an introduction to Bayesian Statistics per se and for comprehensive coverage, address the reader to Robert (2007), (again) among others.Comment: This is a revised version of a chapter written for the Handbook of Computational Statistics, edited by J. Gentle, W. Hardle and Y. Mori in 2003, in preparation for the second editio

An Efficient Digital Image Watermarking Based on DCT and Advanced Image Data Embedding Method

Digital image enhancement and digital content or data image secure using DCT and advanced image data embedding method (AIDEM). AIDEM improved robustness based on particle shifting concept is reproduced secure image data and manipulated there’s a robust would like for a digital image copyright mechanism to be placed in secure image data. There’s a necessity for authentication of the content because of the owner. It’s become more accessible for malicious parties to create scalable copies of proprietary content with any compensation to the content owner. Advanced Watermarking is being viewed as a potential goal to the current downside. Astounding watermarking plans are arranged assaults on the watermarked picture are twisted and proposed to give insurance of proprietorship freedoms, information treating, and information uprightness. These methods guarantee unique information recuperation from watermarked information, while irreversible watermarking plans safeguard proprietorship freedoms. This attribute of reversible watermarking has arisen as an applicant answer for the assurance of proprietorship freedoms of information, unfortunate to alterations, for example, clinical information, genetic information, Visa, and financial balance information. These attacks are also intentional or unintentional. The attacks are classified as geometric attacks. This research presents a comprehensive and old method of these techniques that are developed and their effectiveness. Digital watermarking was developed to supply copyright protection and owners’ authentication. Digital image watermarking may be a methodology for embedding some information into digital image sequences, like text image, image data, during this research analysis on image watermarking and attacks on watermarking process time image data, classification of watermarking and applications. We aim to secure image data using advanced image data embedding method (AIDEM) improved robustness based particle shifting concept is reproduced secure image data. To develop compelling digital image watermarking methodology using mat lab tool and reliable and robust

Monic Testing of Web Services Based on Algebraic Specifications

Web services are designed to be discovered and composed dynamically, which implies that testing must also be done dynamically. This involves both the generation of test cases and the checking of test results. This paper presents algorithms for both of these using the technique of algebraic specification. It focuses in particular on the problem that web services, when they are third-party, have poor controllability and observability, and introduces a solution known as monic floating checkable test cases. A prototype tool has implemented the proposed testing technique and it is applied to a case study with a real industry application GoGrid, demonstrating that the technique is both applicable and feasible