Adrijit Goswami

A Secure Biometrics-Based Multi-Server Authentication Protocol Using Smart Cards

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 first analyze He-Wangs scheme and show that their 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 users anonymity. Furthermore, He-Wangs scheme cannot provide the user revocation facility when the smart card is lost/stolen or users authentication parameter is revealed. Apart from these, He-Wangs scheme has some design flaws, such as wrong password login and its consequences, and wrong password update during password change phase. We then propose a new secure multi-server authentication protocol using biometric-based smart card and ECC with more security functionalities. Using the Burrows-Abadi-Needham logic, we show that our scheme provides secure authentication. In addition, we simulate our scheme for the formal security verification using the widely accepted and used automated validation of Internet security protocols and applications tool, and show that our scheme is secure against passive and active attacks. Our scheme provides high security along with low communication cost, computational cost, and variety of security features. As a result, our scheme is very suitable for battery-limited mobile devices as compared with He-Wangs scheme.

On an inventory model with two levels of storage and stock-dependent demand rate

An order-level inventory model is developed by assuming that the demand rate is stock-dependent and two separate warehouses are used. When the stock level exceeds the capacity of the own warehouse (OW), a rented warehouse (RW) is used. The stock is transferred periodically in bulk from RW to OW and there is an associated transportation cost. No shortages are allowed. An algorithm is developed to obtain the optimal solution of the model. To study the effects of changes in the system parameters on the decision variables, a sensitivity analysis is carried out by taking a numerical example.

Multi-objective modeling of production and pollution routing problem with time window

Integration of two issues of vehicle routing problem, namely, production routing and pollution routing.Multi-period multi-vehicle production and pollution routing problem with time window is formulated.Multi-objective formulation with the objectives of minimization of cost and minimization of carbon emissions.SLPSO algorithm is enhanced in multi-objective framework.Comparison of the proposed algorithm with NSGA-II through a case study. Production routing and pollution routing problems are two important issues of vehicle routing problem (VRP) of the supply chain planning system. Both determine an optimum path for the vehicle, in addition, production routing problem (PRP) deals with production and distribution whereas pollution routing problem deals with carbon footprint. In this paper, we develop a VRP that simultaneously considers production and pollution routing problems with time window (PPRP-TW). The proposed PPRP-TW is a NP-hard problem concentrating to optimize the routing problem over the periods. A fleet of identical capacitated vehicles leave from a production plant to a set of customers scattered in different locations. The transportation part of PPRP-TW is concerned with carbon footprint. Thus, a multi-objective multi-vehicle PPRP-TW (MMPPRP-TW) is formulated with two objectives: minimization of the total operational cost and minimization of the total emissions (equivalently, minimization of the fuel consumption). A hybrid Self-Learning Particle Swarm Optimization (SLPSO) algorithm in multi-objective framework is proposed to solve the MMPPRP-TW. To establish superior computational efficiency of hybrid SLPSO algorithm, a comparison with the well-known Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is performed.

An EOQ model for deteriorating items under trade credit financing in the fuzzy sense

This paper deals with the problem of determining the economic order quantity (EOQ) for deteriorating items in the fuzzy sense where delay in payments for retailer and customer are permissible and generalizes the earlier published results in this direction. The demand rate, holding cost, ordering cost and purchasing cost are taken as fuzzy numbers. We also assume that the supplier would offer the retailer a delay period for payment and the retailer would also offer the trade credit period to the customer. The total variable cost in fuzzy sense is defuzzified using the graded mean integration representation method. Then we have shown that the defuzzified total variable cost is convex, that is, a unique solution exists. For determination of optimal ordering policies, with the help of theorems we have developed the neccessary algorithms. Finally, the theorems and the algorithms are illustrated with the help of numerical examples.

An economic production quantity inventory model involving fuzzy demand rate and fuzzy deterioration rate

Generally, in deriving the solution of economic production quantity (EPQ) inventory model, we consider the demand rate and deterioration rate as constant quantity. But in case of real life problems, the demand rate and deterioration rate are not actually constant but slightly disturbed from their original crisp value. The motivation of this paper is to consider a more realistic EPQ inventory model with finite production rate, fuzzy demand rate and fuzzy deterioration rate. The effect of the loss in production quantity due to faulty/old machine have also been taken into consideration. The methodology to obtain the optimum value of the fuzzy total cost is derived and a numerical example is used to illustrate the computation procedure. A sensitivity analysis is also carried out to get the sensitiveness of the tolarance of different input parameters.

An efficient approach for mining association rules from high utility itemsets

This paper addresses mining association rules from high utility itemsets.Designed FHIM algorithm extracts all high utility itemsets effectively.HUCI-Miner algorithm is used to derive itemsets with their generators efficiently.Condensed representation of association rules in share-confidence model is proposed.The method for extracting all rules from the compact representation is also proposed. 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 semantic measure among the items. The semantic measure of an itemset is characterized with utility values that are typically associated with transaction items, where a user will be interested to an itemset only if it satisfies a given utility constraint. In this paper, we first define the problem of finding association rules using utility-confidence framework, which is a generalization of the amount-confidence measure. Using this semantic concept of rules, we then propose a compressed representation for association rules having minimal antecedent and maximal consequent. This representation is generated with the help of high utility closed itemsets (HUCI) and their generators. We propose the algorithms to generate the utility based non-redundant association rules and methods for reconstructing all association rules. Furthermore, we describe the algorithms which generate high utility itemsets (HUI) and high utility closed itemsets with their generators. These proposed algorithms are implemented using both synthetic and real datasets. The results demonstrate better efficiency and effectiveness of the proposed HUCI-Miner algorithm compared to other well-known existing algorithms. In addition, the experimental results show better quality in the compressed representation of the entire rule set under the considered framework.

A secure and efficient ECC-based user anonymity preserving single sign-on scheme for distributed computer networks

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. Copyright

An Enhanced Biometric Authentication Scheme for Telecare Medicine Information Systems with Nonce Using Chaotic Hash Function

Recently, Awasthi and Srivastava proposed a novel biometric remote user authentication scheme for the telecare medicine information system (TMIS) with nonce. Their scheme is very efficient as it is based on efficient chaotic one-way hash function and bitwise XOR operations. In this paper, we first analyze Awasthi-Srivastava’s scheme and then show that their scheme has several drawbacks: (1) incorrect password change phase, (2) fails to preserve user anonymity property, (3) fails to establish a secret session key beween a legal user and the server, (4) fails to protect strong replay attack, and (5) lacks rigorous formal security analysis. We then a propose a novel and secure biometric-based remote user authentication scheme in order to withstand the security flaw found in Awasthi-Srivastava’s scheme and enhance the features required for an idle user authentication scheme. Through the rigorous informal and formal security analysis, we show that our scheme is secure against possible known attacks. In addition, we simulate our scheme for the formal security verification using the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool and show that our scheme is secure against passive and active attacks, including the replay and man-in-the-middle attacks. Our scheme is also efficient as compared to Awasthi-Srivastava’s scheme.

An interpolating by pass to Pareto optimality in intuitionistic fuzzy technique for a EOQ model with time sensitive backlogging

Abstract This article fuzzyfies EOQ crisp model with backlogged while demand of the customers varies with selling price and promotional effort. The demand rate in stock out situation decreases with duration of the shortage period and it comes back to its initial rate since promotional effort continues. The cost function consists of set up cost, inventory cost, shortage cost and cost for promotional effort. The coefficient vectors of the concerned minimization cost function are considered as fuzzy numbers which are transformed into interval numbers. Then, the interval objective function has been transformed into a classical multi-objective EOQ model using intuitionistic fuzzy technique. A comparative study on Pareto optimality and optimality under Lagrange’s interpolating polynomial function has been made illustrating numerical example.

Fuzzy inventory models for items with imperfect quality and shortage backordering under crisp and fuzzy decision variables

This paper considers inventory models for items with imperfect quality and shortage backordering in fuzzy environments by employing two types of fuzzy numbers, which are trapezoidal and triangular. Two fuzzy models are developed. In the first model the input parameters are fuzzified, while the decision variables are treated as crisp variables. In the second model, not only the input parameters but also the decision variables are fuzzified. For each fuzzy model, a method of defuzzification, namely the graded mean integration method, is employed to find the estimate of the profit function in the fuzzy sense, and then the optimal policy for the each model is determined. The optimal policy for the second model is determined by using the Kuhn-Tucker conditions after the defuzzification of the profit function. Numerical examples are provided in order to ascertain the sensitiveness in the decision variables with respect to fuzziness in the components.