scholarly journals A Design for Modular Exponentiation Coprocessor in Mobile Telecommunication Terminals

Author(s):  
Takehiko Kato ◽  
Satoru Ito ◽  
Jun Anzai ◽  
Natsume Matsuzaki
Author(s):  
Ann Ogbo ◽  
Kifordu Anyibuofu Anthony ◽  
Okagu Kosisochukwu

The study aimed at establishing an assessment of hygiene maintenance factors effects on employees’productivity. The hygiene/maintenance factors play vital role in employees’ productivity. They do not motivate employee in organization, yet they must be present or dissatisfaction will arise. . The study is aimed to pursue the following objectives: To determine the extent to which working conditions improve the performance of employees, to ascertain the effect of interpersonal relations within the organization on firms’ profitability and to assesthe extent to whichcompensation improve the performance of employees.The study was conducted using the survey approach. The geographical scope of the study was Mobile telecommunication network (MTN), located within Enugu metropolis. Two sources of data were utilized in the study: they included primary and secondary sources. The primary source wasthrough the administration of copies of designed questionnaire to a total of forty one respondents that made up the sample size for the study.


Author(s):  
Johannes Mittmann ◽  
Werner Schindler

AbstractMontgomery’s and Barrett’s modular multiplication algorithms are widely used in modular exponentiation algorithms, e.g. to compute RSA or ECC operations. While Montgomery’s multiplication algorithm has been studied extensively in the literature and many side-channel attacks have been detected, to our best knowledge no thorough analysis exists for Barrett’s multiplication algorithm. This article closes this gap. For both Montgomery’s and Barrett’s multiplication algorithm, differences of the execution times are caused by conditional integer subtractions, so-called extra reductions. Barrett’s multiplication algorithm allows even two extra reductions, and this feature increases the mathematical difficulties significantly. We formulate and analyse a two-dimensional Markov process, from which we deduce relevant stochastic properties of Barrett’s multiplication algorithm within modular exponentiation algorithms. This allows to transfer the timing attacks and local timing attacks (where a second side-channel attack exhibits the execution times of the particular modular squarings and multiplications) on Montgomery’s multiplication algorithm to attacks on Barrett’s algorithm. However, there are also differences. Barrett’s multiplication algorithm requires additional attack substeps, and the attack efficiency is much more sensitive to variations of the parameters. We treat timing attacks on RSA with CRT, on RSA without CRT, and on Diffie–Hellman, as well as local timing attacks against these algorithms in the presence of basis blinding. Experiments confirm our theoretical results.


Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3270 ◽  
Author(s):  
Baris Satar ◽  
Gokhan Soysal ◽  
Xue Jiang ◽  
Murat Efe ◽  
Thiagalingam Kirubarajan

Conventional methods such as matched filtering, fractional lower order statistics cross ambiguity function, and recent methods such as compressed sensing and track-before-detect are used for target detection by passive radars. Target detection using these algorithms usually assumes that the background noise is Gaussian. However, non-Gaussian impulsive noise is inherent in real world radar problems. In this paper, a new optimization based algorithm that uses weighted l 1 and l 2 norms is proposed as an alternative to the existing algorithms whose performance degrades in the presence of impulsive noise. To determine the weights of these norms, the parameter that quantifies the impulsiveness level of the noise is estimated. In the proposed algorithm, the aim is to increase the target detection performance of a universal mobile telecommunication system (UMTS) based passive radars by facilitating higher resolution with better suppression of the sidelobes in both range and Doppler. The results obtained from both simulated data with α stable distribution, and real data recorded by a UMTS based passive radar platform are presented to demonstrate the superiority of the proposed algorithm. The results show that the proposed algorithm provides more robust and accurate detection performance for noise models with different impulsiveness levels compared to the conventional methods.


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