A Hybrid Computational Intelligence based Technique for Automatic Cryptanalysis of Playfair Ciphers

The Playfair cipher is a symmetric key cryptosystem-based on encryption of digrams of letters. The cipher shows higher cryptanalytic complexity compared to mono-alphabetic cipher due to the use of 625 different letter-digrams in encryption instead of 26 letters from Roman alphabets. Population-based techniques like Genetic algorithm (GA) and Swarm intelligence (SI) are more suitable compared to the Brute force approach for cryptanalysis of cipher because of specific and unique structure of its Key Table. This work is an attempt to automate the process of cryptanalysis using hybrid computational intelligence. Multiple particle swarm optimization (MPSO) and GA-based hybrid technique (MPSO-GA) have been proposed and applied in solving Playfair ciphers. The authors have attempted to find the solution key applied in generating Playfair crypts by using the proposed hybrid technique to reduce the exhaustive search space. As per the computed results of the MPSO-GA technique, correct solution was obtained for the Playfair ciphers of 100 to 200 letters length. The proposed technique provided better results compared to either GA or PSO-based technique. Furthermore, the technique was also able to recover partial English text message for short Playfair ciphers of 80 to 120 characters length

Designing Secure and Survivable Stegosystems

Steganography, the art and science of carrying out hidden communication, is an emergingsub-discipline of information security. Unlike cryptography, steganography conceals the existenceof a secret message by embedding it in an innocuous container digital media, thereby enablingunobstrusive communication over insecure channels. Detection and extraction of steganographiccontents is another challenge for the information security professional and this activity iscommonly known as steganalysis. Recent progress in steganalysis has posed a challenge fordesign and development of stegosystems with high levels of security and survivability. In thispaper, different strategies have been presented that can be used to escape detection and foilan eavesdropper having high technical capabilities as well as adequate infrastructure. Based onthe strength and weaknesses of current steganographic schemes, ideas have been progressedto make detection and destruction of hidden information more difficult

A Survey of Computer Security Models

ABSTRACT A security model maps the abstract goals of the security policy of information system by specifying information flow necessary to enforce the security policy. The security model that characterize the security goal in a form, which are then mapped to system details. The security model takes the requirement and provides the necessary mathematical formulas, relationships, and structure to be followed to accomplish the security goal. This paper gives brief introduction of security model from the beginning

A Secure Image Encryption Algorithm Based on Hill Cipher System

We present a technique of image encryption based on Hill cipher system that provides better security than existing approach of Bibhudendra Acharya et al. by rendering the image content completely scrambled using multiple self-invertible keys, block shuffling and a new developed pel transformation. The Hill cipher algorithm is one of the symmetric key algorithms having several advantages in encryption. However, the inverse of the matrix used for encrypting the plain text in this algorithm may not always exist. Moreover this algorithm is susceptible to known plain text attack. Our proposed algorithm is aimed at better encryption of all types of images even ones with uniform background and makes the image encryption scheme more secure

A review of ambient air pollution exposure assessment methods in determining childhood respiratory health effects in children under five

Various epidemiological studies have reported on air pollution exposure-related lung function decline and respiratory health effects in children. Children have increased susceptibility to ambient air pollutants as physiological and structural changes of the lung are still occurring within the first five years of life after birth. This review examines applications in air pollution exposure assessment methods when evaluating lung function and respiratory health concentration-response effects in young children, while considering the effects of critical windows of exposure. We identified 13 studies that used various methods of exposure assessment in assessing respiratory health outcomes (presence of lower respiratory tract infections, respiratory symptoms, wheezing and asthma) in children under five. The methods applied included personal monitoring (n = 1), proximity-based methods (n = 3), inverse distance weighting (n = 2), geographic weighted regression (n = 1), dispersion modeling (n = 1), satellite-based methods (n = 2) and land use regression modeling (n = 5). These studies assessed exposure and outcomes at different "windows of susceptibility": antenatally/specific trimesters (n = 8), infancy (n = 5) and early childhood (n = 6). In most studies, the reported measures of air pollutants were noted to be below the prescribed limits, though for some, a cause-effect association was observed. It was also noted that there was very little variation in estimates between time points or trimesters of exposure, likely attributed to limitations in the selected exposure assessment method. Moderate to high correlations between trimesters were reported for most studies. © 2022 by the authors

A hybrid air pollution / land use regression model for predicting air pollution concentrations in Durban, South Africa

The objective of this paper was to incorporate source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter (PM10). The study was undertaken across two regions in Durban, South Africa, one with a high industrial profile and a nearby harbour, and the other with a primarily commercial and residential profile. Multiple hybrid models were developed by integrating air pollution dispersion modelling predictions for source specific NO2, SO2, and PM10 concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban. Industrial point sources, ship emissions, domestic fuel burning, and vehicle emissions were key emission sources. Standard linear regression was used to develop annual, summer and winter hybrid models to predict air pollutant concentrations. Higher levels of NO2 and SO2 were predicted in south Durban as compared to north Durban as these are industrial related pollutants. Slightly higher levels of PM10 were predicted in north Durban as compared to south Durban and can be attributed to either traffic, bush burning or domestic fuel burning. The hybrid NO2 models for annual, summer and winter explained 60%, 58% and 63%, respectively, of the variance with traffic, population and harbour being identified as important predictors. The SO2 models were less robust with lower R(2) annual (44%), summer (53%) and winter (46%), in which industrial and traffic variables emerged as important predictors. The R(2) for PM10 models ranged from 80% to 85% with population and urban land use type emerging as predictor variables

Effect of short-term exposure to ambient nitrogen dioxide and particulate matter on repeated lung function measures in infancy: a South African birth cohort

BACKGROUND: The developing lung is highly susceptible to environmental toxicants, with both short- and long-term exposure to ambient air pollutants linked to early childhood effects. This study assessed the short-term exposure effects of nitrogen dioxide (NO2) and particulate matter (PM10) on lung function in infants aged 6 weeks, 6, 12 and 24 months, the early developmental phase of child growth. METHODS: Lung function was determined by multiple breath washout and tidal breathing measurement in non-sedated infants. Individual exposure to NO2 and PM10 was determined by hybrid land use regression and dispersion modelling, with two-week average estimates (preceding the test date). Linear mixed models were used to adjust for the repeated measures design and an age*exposure interaction was introduced to obtain effect estimates for each age group. RESULTS: There were 165 infants that had lung function testing, with 82 of them having more than one test occasion. Exposure to PM10 (mug/m(3)) resulted in a decline in tidal volume at 6 weeks [-0.4 ml (-0.9; 0.0), p = 0.065], 6 months [-0.5 ml (-1.0; 0.0), p = 0.046] and 12 months [-0.3 ml (-0.7; 0.0), p = 0.045]. PM10 was related to an increase in respiratory rate and minute ventilation, while a decline was observed for functional residual capacity for the same age groups, though not statistically significant for these outcomes. Such associations were however less evident for exposure to NO2, with inconsistent changes observed across measurement parameters and age groups. CONCLUSION: Our study suggests that PM10 results in acute lung function impairments among infants from a low-socioeconomic setting, while the association with NO2 is less convincing