Proof Framework Research Articles

Field Programmable Gate Array Implementation for Highly Secured Palm Print Authentication

To guarantee individual ID and profoundly secure recognizable proof issues, biometric innovations will give more prominent security while improving precision. This new innovation has been done lately because of exchange misrepresentation, security breaks, individual ID, and so on. The excellence of biometric innovation is that it gives an exceptional code to every individual and can’t be duplicated or manufactured by others. So as to conquer the withdrawal of finger impression frameworks, this paper proposed a palm-based individual distinguishing proof framework, a promising and new research region in biometric recognizable proof frameworks in light of their uniqueness, adaptability and a quicker and wide scope of high speeds. It gives higher security on biometric unique mark frameworks with rich highlights, for example, wrinkles, constant brushes, mainlines, details focuses and single focuses. The fundamental motivation behind the proposed palm unique finger impression framework is to actualize a framework with higher exactness and speed up palm unique finger impression acknowledgment for some clients. Here, in this we presented an exceptionally ensured palm print recognizable proof framework with intrigue extraction territory (ROI) with a morphological procedure utilizing a two-way un-crushed or course vector (UDBW) change to separate low-level palm fingerprints enrolled capacities for its vector work (FV) and afterward after correlation is by estimating the separation between the palm transporters and the capacity of the palm and the capacity of the enlisted transport line and palm control. The after effects of the recreation show that the proposed biometric recognizable proof framework gives more noteworthy precision and solid distinguishing proof speed.

A Conceptual Framework for the Integrated, Smart and Secure Remote Public Voting System (SSRPVS)

Elections are the backbone of democracy. It is through elections that individuals assert their voice, their perspectives, and choose a person whose philosophies most complement them. Elections allow citizens to choose their representatives. They are also important for the people to express their resentment at the ruling government. When there is high voter participation, the election process is considered successful. Unfortunately, developing countries such as India are facing a decline in the turnout. People in rural areas move to metropolitan cities or other countries, in most developing countries to make their livelihood or schooling. During elections, visiting their hometown and casting their votes becomes burdensome for them because of their commitment to their workplace. Challenges in moving to poll places and sometimes adverse weather conditions, cause people to miss the chance to choose the candidate of their choice. People with disabilities and senior citizens also refuse to go to the polling station due to travel-related difficulty. Therefore, many elections record only 50-70 percent electoral turnout, sometimes, even less than 50%. Only when all eligible voters are granted fair opportunities to exercise their franchise then only such a democratic system is considered fool proof. The need for the hour is such a fool proof framework that enables all eligible voters to cast their vote by visiting Polling Station or doing so remotely. This paper proposes a conceptual framework for the Integrated, Smart, and Secure Remote Public Voting System (SSRPVS) that allows voters from any part of India to exercise their franchise without moving place to place and wasting time and money. To develop the Framework, emerging technologies such as IoT, Cloud Computing, Edge Computing, Blockchain, and Data Analytics are included. The system will guarantee security through four different levels, Smart Voting Card based on RFID, One Time Password, Thumb Recognition, and Retina Recognition. The only theoretical model of the system that is open for further analysis and development is provided here.

Industry Fire Safety System Using Embedded Technology with Internet of Things

This paper holds tabs to the security additionally security of the piece of attire plant disillusionments and shock on his/her staff require getting the opportunity to be a most stunning issue presently multiple times. Those pieces of attire plant specialists confront an extensive measure about issues and broken insane of smokestack a champion among them without question. Those investors aren’t showing to whatever excitement toward this section and truth that this division might get toner. In this look at a smokestack recognizable proof framework might be propounded and conjointly gives information of the territory affected. Here we used ARM7 which are embedded with different sorts from the sensors. We give satisfactory interface check framework to Abstain from forewarning. The framework could immediately send a SMS of the administrator. Those administrator will confirm or deny the information. In the event that those administrator confirm mellowing out about flame. At that point framework could quickly raise a caution and SMS will an opportunity to be sent of the near to blast unit.

Vehicle Theft Recovery

Presently a-days the whole world is confronting the instability which has gotten one of the major challenges. Each nation has their own unconventional security issues. The crime percentage in all aspects of our general public nowadays has become an undermining issue with the end goal that vehicles are currently utilized for carrying out crimes more than previously. The issue of vehicle robbery has expanded massively, for the most part at gunpoint or vehicle leaves. There is a requirement for reasonable records of taken, recognized and recuperated vehicles which are not promptly accessible in our general public and in that capacity significant. The improvement of a vehicle robbery caution and area distinguishing proof framework turns out to be increasingly essential for vehicle proprietors to guarantee burglary anticipation and an expedient recognizable proof over recuperation which incorporates missing of vehicles by an unapproved individual. Our model utilizes a GSM application created and introduced in a cell phone gadget that is installed in the vehicle to speak with the vehicle proprietor's cell phone through SMS. The correspondences set up incorporate; (I). Sending an alarm message from introduced cell phone gadget to vehicle proprietor portable phone.(ii).Sending an admonition message from the vehicle proprietor's cell phone to begin and stop the introduced cell phone. Decide the present area of a vehicle utilizing GPS.

The 2D Dependency Pair Framework for Conditional Rewrite Systems—Part II: Advanced Processors and Implementation Techniques

Proving termination of programs in ‘real-life’ rewriting-based languages like CafeOBJ, Haskell, Maude, etc., is an important subject of research. To advance this goal, faithfully capturing the impact in the termination behavior of the main language features (e.g., conditions in program rules) is essential. In Part I of this work, we have introduced a 2D Dependency Pair Framework for automatically proving termination properties of Conditional Term Rewriting Systems. Our framework relies on the notion of processor as the main practical device to deal with proofs of termination properties of conditional rewrite systems. Processors are used to decompose and simplify the proofs in a divide and conquer approach. With the basic proof framework defined in Part I, here we introduce new processors to further improve the ability of the 2D Dependency Pair Framework to deal with proofs of termination properties of conditional rewrite systems. We also discuss relevant implementation techniques to use such processors in practice.

On the Convergence of Bregman ADMM With Variational Inequality

The alternating direction method of multipliers (ADMM) is one of most foundational algorithms for linear constrained composite minimization problems. For different specific problems, variations of ADMM (like linearized ADMM, proximal ADMM) are developed. By using the Bregman distances, lots of ADMMs can be formulated into a uniform mathematical scheme. Although variational inequalities have been well used to study ADMMs, the use for BADMM has still been missing. In this paper, we study the convergence of BADMM by variational inequalities. We present a proof framework for BADMMs. And then, we present very concise convergence proof for the basic BADMM. As applications, we consider several variations of BADMM and obtain corresponding convergence results.

Indian Language Identification using Deep Learning

Spoken language is the most regular method of correspondence in this day and age. Endeavours to create language recognizable proof frameworks for Indian dialects have been very restricted because of the issue of speaker accessibility and language readability. However, the necessity of SLID is expanding for common and safeguard applications day by day. Feature extraction is a basic and important procedure performed in LID. A sound example is changed over into a spectrogram visual portrayal which describes a range of frequencies in regard with time. Three such spectrogram visuals were generated namely Log Spectrogram, Gammatonegram and IIR-CQT Spectrogram for audio samples from the standardized IIIT-H Indic Speech Database. These visual representations depict language specific details and the nature of each language. These spectrograms images were then used as an input to the CNN. Classification accuracy of 98.86% was obtained using the proposed methodology.

Structure of Iris Recognition technique

In many iris recognizable proof frameworks, the total image obtains requirements are understood. These imperatives incorporate close infrared (NIR) enlightenment to release the co-events of surface measures in the mirror plane of human iris, just as closeness in the output lines of a device. In ongoing advances to various light developments presented in images caught in the earth. This condition incorporates an obvious wavelength (VW) light source a good way off over the nearby good ways from the catching device. For precise Iris recognizable proof a ways off, eye images require improvement of successful systems, whereas the light source is situating good ways off after the planar perspective on the iris. Adequately acting a highpoint abstraction system aimed at Close Infrared too Obvious wavelength images, the images are composed unrestrained point. The recognizable proof of iris exactness on the freely accessible database remained estimated here uses Hough transform algorithm to caught utilizing straight extending and turn for standardization. for utilizing towards channel also differentiation stretches the iris areas from multispectral iris images. An essential motivation behind this examination is to encompass a structure and actualize IRIS-recognition a good ways off (IAAD) by embracing a recurrence then Hough Transform change intended for exact element choice [1][2]. Here proposed strategy is depicted as pursues: At first, the information iris image will be exposed in the direction of pre-handling though at the same time separating highpoints with contrasts from neighborhood extrema also highest conditions. [3][4].

Unifying theories of reactive design contracts

Design-by-contract is an important technique for model-based design in which a composite system is specified by a collection of contracts that specify the behavioural assumptions and guarantees of each component. In this paper, we describe a unifying theory for reactive design contracts that provides the basis for modelling and verification of reactive systems. We provide a language for expression and composition of contracts that is supported by a rich calculational theory. In contrast with other semantic models in the literature, our theory of contracts allows us to specify both the evolution of state variables and the permissible interactions with the environment. Moreover, our model of interaction is abstract, and supports, for instance, discrete time, continuous time, and hybrid computational models. Being based in Unifying Theories of Programming (UTP), our theory can be composed with further computational theories to support semantics for multi-paradigm languages. Practical reasoning support is provided via our proof framework, Isabelle/UTP, including a proof tactic that reduces a conjecture about a reactive program to three predicates, symbolically characterising its assumptions and guarantees about intermediate and final observations. This allows us to verify programs with a large or infinite state space. Our work advances the state-of-the-art in semantics for reactive languages, description of their contractual specifications, and compositional verification.

Graphical Methods in Device-Independent Quantum Cryptography

We introduce a framework for graphical security proofs in device-independent quantum cryptography using the methods of categorical quantum mechanics. We are optimistic that this approach will make some of the highly complex proofs in quantum cryptography more accessible, facilitate the discovery of new proofs, and enable automated proof verification. As an example of our framework, we reprove a previous result from device-independent quantum cryptography: any linear randomness expansion protocol can be converted into an unbounded randomness expansion protocol. We give a graphical proof of this result, and implement part of it in the Globular proof assistant.

Diffusion operator and spectral analysis for directed hypergraph Laplacian

In spectral graph theory, the Cheeger inequality gives upper and lower bounds of edge expansion in normal graphs in terms of the second eigenvalue of the graph's Laplacian operator. Recently this inequality has been extended to undirected hypergraphs and directed normal graphs via a non-linear operator associated with a diffusion process in the underlying graph.In this work, we develop a unifying framework for defining a diffusion operator on a directed hypergraph with stationary vertices, which is general enough for the following two applications.1. Cheeger's inequality for directed hyperedge expansion.2. Quadratic optimization with stationary vertices in the context of semi-supervised learning.Despite the crucial role of the diffusion process in spectral analysis, previous works have not formally established the existence of the corresponding diffusion processes. In this work, we give a proof framework that can indeed show that such diffusion processes are well-defined. In the first application, we use the spectral properties of the diffusion operator to achieve the Cheeger's inequality for directed hyperedge expansion. In the second application, the diffusion operator can be interpreted as giving a continuous analog to the subgradient method, which moves the feasible solution in discrete steps towards an optimal solution.

A General Proof Framework for Recent AES Distinguishers

In this paper, a new framework is developed for proving and adapting the recently proposed multiple-of-8 property and mixture-differential distinguishers. The above properties are formulated as immediate consequences of an equivalence relation on the input pairs, under which the difference at the output of the round function is invariant. This approach provides a further understanding of these newly developed distinguishers. For example, it clearly shows that the branch number of the linear layer does not influence the validity of the property, on the contrary of what was previously believed. We further provide an extension of the mixture-differential distinguishers and multiple-of-8 property to any SPN and to a larger class of subspaces. These adapted properties can then be exhibited in a systematic way for other ciphers than the AES. We illustrate this with the examples of Midori, Klein, LED and Skinny.

A General Proof Framework for Recent AES Distinguishers

In this paper, a new framework is developed for proving and adapting the recently proposed multiple-of-8 property and mixture-differential distinguishers. The above properties are formulated as immediate consequences of an equivalence relation on the input pairs, under which the difference at the output of the round function is invariant. This approach provides a further understanding of these newly developed distinguishers. For example, it clearly shows that the branch number of the linear layer does not influence the validity of the property, on the contrary of what was previously believed. We further provide an extension of the mixture-differential distinguishers and multiple-of-8 property to any SPN and to a larger class of subspaces. These adapted properties can then be exhibited in a systematic way for other ciphers than the AES. We illustrate this with the examples of Midori, Klein, LED and Skinny.

Refinement to Certify Abstract Interpretations: Illustrated on Linearization for Polyhedra

Our concern is the modular development of a certified static analyzer in Coq: we extend a certified abstract domain of convex polyhedra with a linearization procedure approximating polynomial expressions. In order to help such a development, we propose a proof framework, embedded in Coq, that implements a refinement calculus.

Security-proof framework for two-way Gaussian quantum-key-distribution protocols

Two-way Gaussian protocols have the potential to increase quantum key distribution (QKD) protocols' secret-key rates by orders of magnitudes~[Phys.~Rev.~A {\bf 94}, 012322 (2016)]. Security proofs for two-way protocols, however, are underdeveloped at present. In this paper, we establish a security proof framework for the general coherent attack on two-way Gaussian protocols in the asymptotic regime. We first prove that coherent-attack security can be reduced to collective-attack security for all two-way QKD protocols. Next, we identify two different constraints that each provide intrusion parameters which bound an eavesdropper's coherent-attack information gain for any two-way Gaussian QKD protocol. Finally, we apply our results to two such protocols.

Thinking Slow About Abercrombie & Fitch: Straightening out the Judicial Confusion in the Lower Courts

In Abercrombie & Fitch, the U.S. Supreme Court fundamentally changed the way that Title VII religious accommodation cases are litigated and evaluated. This paper analyzes Abercrombie, explains how the Court eliminated religious accommodation as a freestanding cause of action, and suggests an altered proof framework for plaintiffs seeking an accommodation. The paper also explores the conflict between employee privacy rights and classic proof requirements for religious sincerity. The lower courts have largely failed to apprehend the change mandated by Abercrombie, with the result that their opinions are in disarray. The paper includes a chart organizing the diverse lower court opinions.

Hypersequents and Systems of Rules

We define a bi-directional embedding between hypersequent calculi and a subclass of systems of rules (2-systems). In addition to showing that the two proof frameworks have the same expressive power, the embedding allows for the recovery of the benefits of locality for 2-systems, analyticity results for a large class of such systems, and a rewriting of hypersequent rules as natural deduction rules.

Doppelgängers: Bijections of Plane Partitions

AbstractWe say two posets are doppelgängers if they have the same number of P-partitions of each height k. We give a uniform framework for bijective proofs that posets are doppelgängers by synthesizing K-theoretic Schubert calculus techniques of H. Thomas and A. Yong with M. Haiman’s rectification bijection and an observation of R. Proctor. Geometrically, these bijections reflect the rational equivalence of certain subvarieties of minuscule flag manifolds. As a special case, we provide the 1st bijective proof of a 1983 theorem of R. Proctor—that plane partitions of height k in a rectangle are equinumerous with plane partitions of height k in a shifted trapezoid.

Practical witness encryption for algebraic languages or how to encrypt under Groth–Sahai proofs

Witness encryption (\(\mathsf{WE}\)) is a recent powerful encryption paradigm, which allows to encrypt a message using the description of a hard problem (a word in an \({\mathbf{NP}}\)-language) and someone who knows a solution to this problem (a witness) is able to efficiently decrypt the ciphertext. Recent work thereby focuses on constructing \(\mathsf{WE}\) for \({\mathbf{NP}}\) complete languages (and thus \({\mathbf{NP}}\)). While this rich expressiveness allows flexibility w.r.t. applications, it makes existing instantiations impractical. Thus, it is interesting to study practical variants of \(\mathsf{WE}\) schemes for subsets of \({\mathbf{NP}}\) that are still expressive enough for many cryptographic applications. We show that such \(\mathsf{WE}\) schemes can be generically constructed from smooth projective hash functions (\(\mathsf {SPHF}\)s). In terms of concrete instantiations of \(\mathsf {SPHF}\)s (and thus \(\mathsf{WE}\)), we target languages of statements proven in the popular Groth–Sahai (\(\mathsf {GS}\)) non-interactive witness-indistinguishable/zero-knowledge proof framework. This allows us to provide a novel way to encrypt. In particular, encryption is with respect to a \(\mathsf {GS}\) proof and efficient decryption can only be done by the respective prover. The so obtained constructions are entirely practical. To illustrate our techniques, we apply them in context of privacy-preserving exchange of information.

Support recovery without incoherence: A case for nonconvex regularization

We develop a new primal-dual witness proof framework that may be used to establish variable selection consistency and $\ell_{\infty}$-bounds for sparse regression problems, even when the loss function and regularizer are nonconvex. We use this method to prove two theorems concerning support recovery and $\ell_{\infty}$-guarantees for a regression estimator in a general setting. Notably, our theory applies to all potential stationary points of the objective and certifies that the stationary point is unique under mild conditions. Our results provide a strong theoretical justification for the use of nonconvex regularization: For certain nonconvex regularizers with vanishing derivative away from the origin, any stationary point can be used to recover the support without requiring the typical incoherence conditions present in $\ell_{1}$-based methods. We also derive corollaries illustrating the implications of our theorems for composite objective functions involving losses such as least squares, nonconvex modified least squares for errors-in-variables linear regression, the negative log likelihood for generalized linear models and the graphical Lasso. We conclude with empirical studies that corroborate our theoretical predictions.