Simple Photonic Emission Attack with Reduced Data Complexity

Highlight choice might be significant as data is made ceaselessly and at a consistently developing charge, it decreases the extreme dimensionality of certain issues. Highlight decision as a pre-preparing venture to gadget acing, is groundbreaking in bringing down repetition, getting rid of unessential records, developing picking up learning of exactness, and improving final product fathom ability. This work offers far reaching strategy to work decision inside the extent of classification issues, clarifying the principles, genuine application issues, etc inside the setting of over the top dimensional records. To begin with, we consideration on the possibility of trademark decision gives an examination on history and essential standards. We advocate quick sub sampling calculations to effectually rough the most extreme shot gauge in strategic relapse. We initially build up consistency and asymptotic ordinariness of the estimator from a well known sub sampling calculation, and afterward determine choicest sub sampling probabilities that limit the asymptotic suggest squared blunder of the subsequent estimator. An open door minimization standard is additionally proposed to additionally diminish the computational esteem. The best sub sampling chances rely on the all out data gauge, so we increment a - step set of guidelines to inexact the perfect sub sampling strategy. This arrangement of guidelines is computationally effective and has a gigantic markdown in figuring time contrasted with the entire insights technique. Consistency and asymptotic typicality of the estimator from a two-advance arrangement of principles are likewise mounted. Fake and real data units are utilized to assess the pragmatic generally execution of the proposed system.

Download Full-text

Data sanitization against adversarial label contamination based on data complexity

International Journal of Machine Learning and Cybernetics ◽

10.1007/s13042-016-0629-5 ◽

2017 ◽

Vol 9 (6) ◽

pp. 1039-1052 ◽

Cited By ~ 8

Author(s):

Patrick P. K. Chan ◽

Zhi-Min He ◽

Hongjiang Li ◽

Chien-Chang Hsu

Keyword(s):

Data Complexity ◽

Data Sanitization

Download Full-text

The data complexity index to construct an efficient cross-validation method

Decision Support Systems ◽

10.1016/j.dss.2010.07.005 ◽

2010 ◽

Vol 50 (1) ◽

pp. 93-102 ◽

Cited By ~ 11

Author(s):

Der-Chiang Li ◽

Yao-Hwei Fang ◽

Y.M. Frank Fang

Keyword(s):

Cross Validation ◽

Data Complexity ◽

Validation Method ◽

Complexity Index

Download Full-text

Cryptanalysis of Loiss Stream Cipher-Revisited

Journal of Applied Mathematics ◽

10.1155/2014/457275 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7

Author(s):

Lin Ding ◽

Chenhui Jin ◽

Jie Guan ◽

Qiuyan Wang

Keyword(s):

Time Complexity ◽

Stream Cipher ◽

Linear Equations ◽

Data Complexity ◽

Secret Key ◽

Key Recovery ◽

Systems Of Linear Equations ◽

Key Recovery Attack ◽

Better Than

Loiss is a novel byte-oriented stream cipher proposed in 2011. In this paper, based on solving systems of linear equations, we propose an improved Guess and Determine attack on Loiss with a time complexity of 2231and a data complexity of 268, which reduces the time complexity of the Guess and Determine attack proposed by the designers by a factor of 216. Furthermore, a related key chosenIVattack on a scaled-down version of Loiss is presented. The attack recovers the 128-bit secret key of the scaled-down Loiss with a time complexity of 280, requiring 264chosenIVs. The related key attack is minimal in the sense that it only requires one related key. The result shows that our key recovery attack on the scaled-down Loiss is much better than an exhaustive key search in the related key setting.

Download Full-text