scholarly journals An analysis of influence of safe programming techniques on applications efficiency and security

2018 ◽  
Vol 6 ◽  
pp. 12-19
Author(s):  
Tomasz Kobiałka
Keyword(s):  
Theoretical Description ◽  
Security Vulnerabilities ◽  
Programming Techniques ◽  
Safe Programming ◽  
The Impact ◽  
Common Security

The topics covered in this article are the risks that must be taken into account when developing the software. This article gives you an overview of safeguards against some of the anticipated common security vulnerabilities. Based on the written programs, the impact of the various techniques of safe programming on the performance and security of the application has been analyzed. This article presents both a theoretical description of the protections as well as examples of their technical implementation.

Security Threat Analyses and Attack Models for Approximate Computing Systems

2021 ◽  
Vol 26 (4) ◽  
pp. 1-31
Author(s):  
Pruthvy Yellu ◽  
Landon Buell ◽  
Miguel Mark ◽  
Michel A. Kinsy ◽  
Dongpeng Xu ◽  
...  
Keyword(s):  
Error Resilience ◽  
Security Threats ◽  
Approximate Computing ◽  
Security Threat ◽  
Security Vulnerabilities ◽  
Computing Systems ◽  
Quantitative Analyses ◽  
Resilience Mechanisms ◽  
The Impact ◽  
Attack Models

Approximate computing (AC) represents a paradigm shift from conventional precise processing to inexact computation but still satisfying the system requirement on accuracy. The rapid progress on the development of diverse AC techniques allows us to apply approximate computing to many computation-intensive applications. However, the utilization of AC techniques could bring in new unique security threats to computing systems. This work does a survey on existing circuit-, architecture-, and compiler-level approximate mechanisms/algorithms, with special emphasis on potential security vulnerabilities. Qualitative and quantitative analyses are performed to assess the impact of the new security threats on AC systems. Moreover, this work proposes four unique visionary attack models, which systematically cover the attacks that build covert channels, compensate approximation errors, terminate normal error resilience mechanisms, and propagate additional errors. To thwart those attacks, this work further offers the guideline of countermeasure designs. Several case studies are provided to illustrate the implementation of the suggested countermeasures.

scholarly journals Theoretical Description of Carbon Felt Electrical Properties Affected by Compression

2019 ◽  
Vol 9 (19) ◽  
pp. 4030 ◽  
Author(s):  
Moshe Averbukh ◽  
Svetlana Lugovskoy
Keyword(s):  
Electrical Conductivity ◽  
Electrical Properties ◽  
Close Contact ◽  
Internal Surface ◽  
Theoretical Models ◽  
Theoretical Description ◽  
Carbon Felt ◽  
Long Carbon Fibers ◽  
Carbon Filaments ◽  
The Impact

Electro-conductive carbon felt (CF) material is composed by bonding together different lengths of carbon filaments resulting in a porous structure with a significant internal surface that facilitates enhanced electrochemical reactions. Owing to its excellent electrical properties, CF is found in numerous electrochemical applications, such as electrodes in redox flow batteries, fuel cells, and electrochemical desalination apparatus. CF electro-conductivity mostly arises from the close contact between the surface of two electrodes and the long carbon fibers located between them. Electrical conductivity can be improved by a moderate pressing of the CF between conducting electrodes. There exist large amounts of experimental data regarding CF electro-conductivity. However, there is a lack of analytical theoretical models explaining the CF electrical characteristics and the effects of compression. Moreover, CF electrodes in electrochemical cells are immersed in different electrolytes that affect the interconnections of fibers and their contacts with electrodes, which in turn influence conductivity. In this paper, we investigated both the role of CF compression, as well as the impact of electrolyte characteristics on electro-conductivity. The article presents results of measurements, mathematical analysis of CF electrical properties, and a theoretical analytical explanation of the CF electrical conductivity which was done by a stochastic description of carbon filaments disposition inside a CF frame.

scholarly journals Testing the impact of satellite anisotropy on large- and small-scale intrinsic alignments using hydrodynamical simulations

2019 ◽  
Vol 491 (4) ◽  
pp. 5330-5350 ◽  
Author(s):  
S Samuroff ◽  
R Mandelbaum ◽  
T Di Matteo
Keyword(s):  
Power Spectra ◽  
Theoretical Description ◽  
Small Scale ◽  
Spherically Symmetric ◽  
Number Density ◽  
Simulated Likelihood ◽  
Hydrodynamical Simulation ◽  
Likelihood Analysis ◽  
Hydrodynamical Simulations ◽  
The Impact

ABSTRACT Galaxy intrinsic alignments (IAs) have long been recognized as a significant contaminant to weak lensing-based cosmological inference. In this paper we seek to quantify the impact of a common modelling assumption in analytic descriptions of IAs: that of spherically symmetric dark matter haloes. Understanding such effects is important as the current generation of IA models are known to be limited, particularly on small scales, and building an accurate theoretical description will be essential for fully exploiting the information in future lensing data. Our analysis is based on a catalogue of 113 560 galaxies between z = 0.06 and 1.00 from massiveblack-ii, a hydrodynamical simulation of box length $100 \, h^{-1}$ Mpc. We find satellite anisotropy contributes at the level of $\ge 30\!-\!40{{\ \rm per\ cent}}$ to the small-scale alignment correlation functions. At separations larger than $1 \, h^{-1}$ Mpc the impact is roughly scale independent, inducing a shift in the amplitude of the IA power spectra of $\sim 20{{\ \rm per\ cent}}$. These conclusions are consistent across the redshift range and between the massiveblack-ii and the illustris simulations. The cosmological implications of these results are tested using a simulated likelihood analysis. Synthetic cosmic shear data are constructed with the expected characteristics (depth, area, and number density) of a future LSST-like survey. Our results suggest that modelling alignments using a halo model based upon spherical symmetry could potentially induce cosmological parameter biases at the ∼1.5σ level for S8 and w.

Analysis Of The Impact Of The Coal Bed Inclination And The Direction Of Exploitation On Surface Deformation

2015 ◽  
Vol 60 (4) ◽  
pp. 997-1012
Author(s):  
Andrzej Kowalski ◽  
Piotr Polanin
Keyword(s):  
Surface Deformation ◽  
Extreme Values ◽  
Theoretical Description ◽  
Coal Bed ◽  
Mining Institute ◽  
The Impact

Abstract The article presents deformation indexes for three examples, for which the quantitative relations of extreme values were described, including the influence of a coal bed dip and a direction of exploitation. The conclusion regards the mining prevention on minimizing longwall deformation. New experience allows improving methods of theoretical description of deformation, which is the aim of the research continuing at the Central Mining Institute.

A Comparison of the Effects of Logo and a CAI Learning Environment on Skills Acquisition

1987 ◽  
Vol 3 (4) ◽  
pp. 461-477 ◽  
Author(s):  
Joan K. Gallini
Keyword(s):  
Cognitive Outcomes ◽  
Skills Acquisition ◽  
Group Discussions ◽  
Affective Outcomes ◽  
Treatment Groups ◽  
Hands On ◽  
Fourth Grade Students ◽  
Programming Techniques ◽  
Computer Based ◽  
The Impact

The present study investigated the impact of computer-based environments in enhancing a particular set of cognitive outcomes. Of specific focus was a comparison between a Logo and a more traditional CAI context in promoting one's ability to follow directions and construct directions in the process of solving problems. Forty-four fourth-grade students were randomly assigned to one of the two treatment groups. Subjects engaged in group discussions and hands-on computer activities over a five-week period. In the Logo group subjects essentially tested programming techniques in constructing a variety of structures. The CAI group worked with similar stimuli, but in a “program-directed” format. Results demonstrated higher posttest achievement in the Logo group's ability to formulate directions in different instances. However, the following direction performances were essentially the same for both groups. The study raises important theoretical issues regarding the role of specific types of features of computer-based environments in effecting different types of cognitive as well as affective outcomes. Of particular note are the merits of such research to generate new hypotheses about CBI contexts adapted to meet individual differences in learning.

scholarly journals Analysis of Security Issues of Edge Computing Based Internet of Things Applications

2020 ◽  
Author(s):  
Shamim Muhammad ◽  
Inderveer Chana ◽  
Supriya Thilakanathan
Keyword(s):  
Internet Of Things ◽  
Edge Computing ◽  
The Internet ◽  
Security Vulnerabilities ◽  
Computing Power ◽  
Security Issues ◽  
Computing Paradigm ◽  
Improved Performance ◽  
The Internet Of Things ◽  
Common Security

Edge computing is a technology that allows resources to be processed or executed close to the edge of the internet. The interconnected network of devices in the Internet of Things has led to an increased amount of data, increasing internet traffic usage every year. Also, edge computing is driving applications and computing power away from the integrated points to areas close to users, leading to improved performance of the application. Despite the explosive growth of the edge computing paradigm, there are common security vulnerabilities associated with the Internet of Things applications. This paper will evaluate and analyze some of the most common security issues that pose a serious threat to the edge computing paradigm.

scholarly journals Robust Computing for Machine Learning-Based Systems

2020 ◽  
pp. 479-503
Author(s):  
Muhammad Abdullah Hanif ◽  
Faiq Khalid ◽  
Rachmad Vidya Wicaksana Putra ◽  
Mohammad Taghi Teimoori ◽  
Florian Kriebel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Rapid Development ◽  
Autonomous Driving ◽  
High Accuracy ◽  
Security Threats ◽  
Security Vulnerabilities ◽  
Smart Healthcare ◽  
Super Computer ◽  
Temporal Redundancy ◽  
The Impact

AbstractThe drive for automation and constant monitoring has led to rapid development in the field of Machine Learning (ML). The high accuracy offered by the state-of-the-art ML algorithms like Deep Neural Networks (DNNs) has paved the way for these algorithms to being used even in the emerging safety-critical applications, e.g., autonomous driving and smart healthcare. However, these applications require assurance about the functionality of the underlying systems/algorithms. Therefore, the robustness of these ML algorithms to different reliability and security threats has to be thoroughly studied and mechanisms/methodologies have to be designed which result in increased inherent resilience of these ML algorithms. Since traditional reliability measures like spatial and temporal redundancy are costly, they may not be feasible for DNN-based ML systems which are already super computer and memory intensive. Hence, new robustness methods for ML systems are required. Towards this, in this chapter, we present our analyses illustrating the impact of different reliability and security vulnerabilities on the accuracy of DNNs. We also discuss techniques that can be employed to design ML algorithms such that they are inherently resilient to reliability and security threats. Towards the end, the chapter provides open research challenges and further research opportunities.

On-Line Hemodiafiltration with Pre- and Postdilution: A Comparison of Efficacy

1997 ◽  
Vol 20 (2) ◽  
pp. 81-90 ◽  
Author(s):  
P. Ahrenholz ◽  
R.E. Winkler ◽  
W. Ramlow ◽  
M. Tiess ◽  
W. Müller
Keyword(s):  
Molecular Weight ◽  
Theoretical Description ◽  
Convective Transport ◽  
Small Molecular Weight ◽  
Dialysate Flow ◽  
Significant Difference ◽  
On Line ◽  
The Impact

Since the introduction of on-line substituate preparation, high substituate rates (Qs) in pre- and postdilution for hemodiafiltration (HDF) procedures can be realized. During postdilution HDF (POD-HDF) and additional convective removal is possible, but in vivo Qs is limited to approx. 1/3Qb (bloodflow). With predilution HDF (PRD-HDF) higher Qs and therefore high convective transport rates by ultrafiltration can be reached. On the other hand the blood concentration is diminished by predilution. Further decrease of the diffusive transport is caused by reduced dialysate flow Qd due to separation of the substituate from the dialysate (Fresenius 4008 On-Line HDF, Gambro AK100 Ultra). The theoretical description of the combined diffusive-convective transport is limited to 1-dimensional models and small UF-rates. Therefore for practical and theoretical purposes the assessment of the efficacy of on-line PRD-HDF and POD-HDF in different molecular weight ranges is desirable. By means of in vitro experiments the effective clearances Keff of hemodialysis (HD, dialyzer: Fresenius F60) for urea, creatinine, vitamin B12 and inulin were compared with measured and theoretical Keff of POD- and PRD-HDF. The theoretical expectation is confirmed that Keff for small molecular weight substances decreases slightly with PRD-HDF and increases for larger molecules. In the case of POD-HDF Keff for small molecular weight substances increases slightly and strongly for larger molecules. In vivo experiments were performed to measure the real substance removal from patient's blood and to figure out the impact of dialysate flow (collection of the used dialysate during the 1. treatment hour and concentration measurements for urea, creatinine, phosphate, ß2-MG). The results show that the substraction of Qs from Qd reduces Keff for urea, creatinine and phosphate but not for ß2-MG. PRD-HDF with Qd = 500 ml/min is significantly less effective for small molecules than HD. There is no significant difference of Keff for urea, creatinine, phosphate during HD and PRD-HDF with Qd = 800 ml/min, but a significant increase of 10-15% for POD-HDF Keff for ß2-MG increases by 75% for PRD-HDF and 95% for POD-HDF compared with HD (Qd = 500 ml/min).

The Impact of Awareness of Being Monitored on Computer Usage Policy Compliance: An Agency View

2019 ◽  
Vol 34 (1) ◽  
pp. 135-149 ◽  
Author(s):  
Nirmalee I. Raddatz ◽  
Kent Marett ◽  
Brad S. Trinkle
Keyword(s):  
Agency Theory ◽  
Deviant Behavior ◽  
Computer Usage ◽  
Policy Compliance ◽  
Security Vulnerabilities ◽  
General Deterrence ◽  
Computer Abuse ◽  
Study Results ◽  
Organizational Information ◽  
The Impact

ABSTRACT Computer abuse by employees has increased the potential for security vulnerabilities for organizations. Organizations have established various security countermeasures to prevent computer abuse and protect organizational information. However, these policies are only effective if followed. Thus, it is important for organizations to understand the factors that motivate employees to follow computer usage polices. We investigate the impact of different countermeasures, such as perceived sanctions, and awareness of being monitored on compliance with computer usage policies by drawing upon agency theory and general deterrence theory. After testing the hypothesized relationships using survey data, the results indicate that perceived sanction severity and certainty significantly influence intention to comply with computer usage policies. Furthermore, awareness of being monitored is found to significantly impact penalties. Study results further indicate that penalties may be effective only to the extent that organizations can detect employees' deviant behavior through managerial controls, such as computer monitoring.

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