Abstract

Improving thermostability of industrial enzymes is an important protein engineering challenge. Point mutations, induced to increase thermostability, affect the structure and dynamics of the target protein in several ways and thus can also affect its activity. There appears to be no general rules for improving thermostabilty of enzymes, without adversely affecting their enzymatic activity. We report MD simulations, of wild type Bacillus subtilis lipase (WT) and its six progressively thermostable mutants (2M, 3M, 4M, 6M, 9M and 12M), performed at different temperatures, to address this issue. Less thermostable mutants (LTMs), 2M - 6M, show WT-like dynamics at all simulation temperatures. However, the two more thermostable mutants (MTMs), show required flexibility at appropriate temperature ranges and maintain conformational stability at high temperature. They show deep and rugged free-energy landscape, confining them within a near-native conformational space by conserving non-covalent interactions, and thus protecting them from possible aggregation. In contrast, the LTMs having marginally higher thermostabilities than WT show greater probabilities of accessing non-native conformations, which, due to aggregation, have reduced possibilities of reverting to their respective native states under refolding conditions. Our analysis indicates the possibility of non-additive effects of point mutations on the conformational stability of LTMs.

Abstract

The land use changes in forested landscape are highly complex and dynamic, affected by the natural, socio-economic, cultural, political and other factors. The remote sensing (RS) and geographical information system (GIS) techniques coupled with multi-criteria evaluation functions such as Markov-cellular automata (CA–Markov) model helps in analysing intensity, extent and future forecasting of human activities affecting the terrestrial biosphere. Karwar taluk of Central Western Ghats in Karnataka state, India has seen rapid transitions in its forest cover due to various anthropogenic activities, primarily driven by major industrial activities. A study based on Landsat and IRS derived data along with CA–Markov method has helped in characterizing the patterns and trends of land use changes over a period of 2004–2013, expected transitions was predicted for a set of scenarios through 2013-2022. The analysis reveals the loss of pristine forest cover from 75.51% to 67.36%(1973 to 2013) and increase in agriculture land as well as built-up area of 8.65%(2013), causing impact on local flora and fauna. The other factors driving these changes are the aggregated level of demand for land, local and regional effects of land use activities such as deforestation, improper practices in expansion of agriculture and infrastructure development, deteriorating natural resources availability. The spatio temporal models helped in visualizing on-going changes apart from prediction of likely changes. The CA-Markov based analysis provides us insights into the localized changes impacting these regions and can be useful in developing appropriate mitigation management …

Abstract

In the recent past, remotely sensed data with high spectral resolution has been made available and has been explored for various agricultural and geological applications. While these spectral signatures of the objects of interest provide important clues, the relatively poor spatial resolution of these hyperspectral images limits their utility and performance. In this context, hyperspectral image enhancement using multispectral data has been actively pursued to improve spatial resolution of such imageries and thus enhancing its use for classification and composition analysis in various applications. But, this also poses a challenge in terms of managing the trade-off between improved spatial detail and the distortion of spectral signatures in these fused outcomes. This paper proposes a strategy of using vector decomposition, as a model to transfer the spatial detail from relatively higher resolution data, in association with sensor simulation to generate a fused hyperspectral image while preserving the inter band spectral variability. The results of this approach demonstrates that the spectral separation between classes has been better captured and thus helped improve classification accuracies over mixed pixels of the original low resolution hyperspectral data. In addition, the quantitative analysis using a rank-correlation metric shows the appropriateness of the proposed method over the other known approaches with regard to preserving the spectral signatures.

Abstract

Mangroves are one of the productive and highly adaptive ecosystems on the Earth, and provide invaluable services to the coastal communities. Ecological and sustainable management of the mangrove ecosystem requires crucial knowledge of variability and dynamics over a time and space. There are no reliable recent spatial extent estimates of mangroves or trend of coverage in West coast. The mapping from medium spatial resolution remote sensing data often leads to the underestimation of spatial extent. An attempt has been made to provide detailed information of mangroves species distribution using remote sensing data of high spatial resolution integrated with the other collateral field information through GIS. The coastline changes and the mangrove dynamics during 1989–2010 were assessed using supervised classifier technique provided the spatial distribution of mangrove species namely Rhizophora mucronata, Sonneratia caseolaris, Avicennia officinalis, Sonneratia alba, and Kandelia candel with classification good accuracy. Delineation of mangroves at species wise records based on extensive field data will be invaluable for appropriate management (eg plantation, eco-tourism) and conservation measures for estuaries of Central Western Ghats. Mangroves play pivotal role in providing vital ecosystem goods and services, but are under threat due to anthropogenic activities, affecting habitat for specialised fauna and food resources for humans, birds and fish. This necessitates interventions of regulatory authorities to partner with the local communities in the restoration and conservation of mangrove habitats.

Abstract

Traditional association rule mining based on the support-confidence framework provides the objective measure of the rules that are of interest to users. However, it does not reflect the utility of the rules. To extract non-redundant association rules in support-confidence framework frequent closed itemsets and their generators play an important role. To extract non-redundant association rules among high utility itemsets, high utility closed itemsets (HUCI) and their generators should be extracted in order to apply traditional support-confidence framework. However, no efficient method exists at present for mining HUCIs with their generators. This paper addresses this issue. A postprocessing algorithm, called the HUCI-Miner, is proposed to mine HUCIs with their generators. The proposed algorithm is implemented using both synthetic and real datasets.

Abstract

Wireless body area networks (WBANs) can be applied to provide healthcare and patient monitoring. However, patient privacy can be vulnerable in a WBAN unless security is considered. Access to authorized users for the correct information and resources for different services can be provided with the help of efficient user access control mechanisms. This paper proposes a new user access control scheme for a WBAN. The proposed scheme makes use of a group-based user access ID, an access privilege mask, and a password. An elliptic curve cryptography-based public key cryptosystem is used to ensure that a particular legitimate user can only access the information for which he/she is authorized. We show that our scheme performs better than previously existing user access control schemes. Through a security analysis, we show that our scheme is secure against possible known attacks. Furthermore, through a formal security verification using the AVISPA (Automated Validation of Internet Security Protocols and Applications) tool, we show that our scheme is also secure against passive and active attacks.

Abstract

Lo et al. (2011) proposed an efficient key assignment scheme for access control in a large leaf class hierarchy where the alternations in leaf classes are more frequent than in non-leaf classes in the hierarchy. Their scheme is based on the public-key cryptosystem and hash function where operations like modular exponentiations are very much costly compared to symmetric-key encryptions and decryptions, and hash computations. Their scheme performs better than the previously proposed schemes. However, in this paper, we show that Lo et al.’s scheme fails to preserve the forward security property where a security class can also derive the secret keys of its successor classes ’s even after deleting the security class from the hierarchy. We aim to propose a new key management scheme for dynamic access control in a large leaf class hierarchy, which makes use of symmetric-key cryptosystem and one-way hash function. We show that our scheme requires significantly less storage and computational overheads as compared to Lo et al.’s scheme and other related schemes. Through the informal and formal security analysis, we further show that our scheme is secure against all possible attacks including the forward security. In addition, our scheme supports efficiently dynamic access control problems compared to Lo et al.’s scheme and other related schemes. Thus, higher security along with low storage and computational costs make our scheme more suitable for practical applications compared to other schemes.

Abstract

In a remote user authentication scheme, a remote server verifies whether a login user is genuine and trustworthy, and also for mutual authentication purpose a login user validates whether the remote server is genuine and trustworthy. Several remote user authentication schemes using the password, the biometrics, and the smart card have been proposed in the literature. However, most schemes proposed in the literature are either computationally expensive or insecure against several known attacks. In this paper, we aim to propose a new robust and effective password-based remote user authentication scheme using smart card. Our scheme is efficient, because our scheme uses only efficient one-way hash function and bitwise XOR operations. Through the rigorous informal and formal security analysis, we show that our scheme is secure against possible known attacks. We perform the simulation for the formal security analysis using the widely accepted AVISPA (Automated Validation Internet Security Protocols and Applications) tool to ensure that our scheme is secure against passive and active attacks. Furthermore, our scheme supports efficiently the password change phase always locally without contacting the remote server and correctly. In addition, our scheme performs significantly better than other existing schemes in terms of communication, computational overheads, security, and features provided by our scheme.

Abstract

Authentication plays an important role in an open network environment in order to authenticate two communication parties among each other. Authentication protocols should protect the sensitive information against a malicious adversary by providing a variety of services, such as authentication, user credentials’ privacy, user revocation and re-registration, when the smart card is lost/stolen or the private key of a user or a server is revealed. Unfortunately, most of the existing multi-server authentication schemes proposed in the literature do not support the fundamental security property such as the revocation and re-registration with same identity. Recently, in 2014, He and Wang proposed a robust and efficient multi-server authentication scheme using biometrics-based smart card and elliptic curve cryptography (ECC). In this paper, we analyze the He-Wang’s scheme and show that He-Wang’s scheme is vulnerable to a known session-specific temporary information attack and impersonation attack. In addition, we show that their scheme does not provide strong user’s anonymity. Furthermore, He-Wang’s scheme cannot support the revocation and re-registration property. Apart from these, He-Wang’s scheme has some design flaws, such as wrong password login and its consequences, and wrong password update during password change phase.

Abstract

A user authentication in the distributed computer networks (DCNs) plays a crucial rule to verify whether the user is a legal user and can therefore be granted access to the requested services to that user. In recent years, several RSA‐based single sign‐on mechanisms have been proposed in DCNs. However, most of them cannot preserve the user anonymity when possible attacks occur. The user devices are usually battery limited (e.g., cellular phones) and the elliptic‐curve cryptosystem is much efficient than RSA cryptosystem for the battery‐limited devices. In this paper, we aim to propose a new secure elliptic‐curve cryptosystem‐based single sign‐on mechanism for user authentication and key establishment for the secure communications in a DCNs using biometric‐based smart card. In our scheme, a user only needs to remember a private password and his or her selected unique identity to authenticate and agree on a high‐entropy cryptographic one‐time session key with a provider to communicate over untrusted public networks. Through formal and informal security analysis, we show that our scheme prevents other known possible attacks. In addition, we perform simulation on our scheme for the formal security verification using the widely‐accepted Automated Validation of Internet Security Protocols and Applications tool. The simulation results ensure that our scheme is secure against replay and man‐in‐the‐middle attacks. Furthermore, our scheme provides high security along with lower computational cost and communication cost, and as a result, our scheme is much suitable for the battery‐limited devices as compared to other related RSA‐based schemes.