A Proposed Islamic Microfinance Impact Assessment Methodology

Impact assessment of microfinance programs have been remained the foremost concern of microfinance stakeholders for optimal policy measures. The existing literature regarding the impact assessment varies from parametric to experimental methods to evaluate the performance of microfinance programs across the world however; the literature is lacking a single measure to reveal maximum possible changes in socioeconomic variables resulting from microfinance institutions’ intervention. This study aims to develop a composite index for evaluating the performance of microfinance programs in multi-dimensional contexts. The study exposes a set of eight “diverse indicators” to evaluate the performance of a microfinance program on a wider socioeconomic scale. The dimensions of the index are consist of economic (Income, saving) and socioeconomic (poverty, access to basic facilities, family empowerment) indicators. The changes in deprivations of household, based on the selected indicators, reveal the intensity of success of a microfinance program towards their goals. Finally, we have developed an index by the interaction of incidence and intensity of socioeconomic deprivations. The index is named as “Multidimensional Microfinance Deprivation Index”. This is an index developed in the same line as multidimensional poverty index. The implications of this study are three folds; firstly, it will open up a new dimension of literature in the field of microfinance including Islamic microfinance by instigating an important area. Secondly, it may provide a better alternative to microfinance’s stakeholders to investigate the impact assessment of microfinance programs on a wider socioeconomic scale rather than a few economic. Last but not the least, the study integrates diverse socioeconomic indicators, after assigning weights and adjustment to portray an overall picture of the performance of microfinance in terms of uplifting the socioeconomic conditions of the poor and financially marginalized people.

Securing Routing in Mobile Adhoc Networks Manets Form Insider Attackers Through Trust Management

Routing, having focal responsibility in MANET’s successful operation, are based on the assumption of nodes’ cooperation. However, this assumption exposes routing to various insider attackers. These attackers are the legal participants having privileged access to network when inducing attacks on routing. Furthermore, these insider attackers are either in the form of selfish nodes or malicious nodes. The motive of selfish node is saving its resources by not cooperating in routing activities whereas the purpose of malcious node is to attack the network. Therefore, providing security in routing against affirmed attackers has emerged a challenging issue in MANETs. In research community, trust management schemes are used to defend routing against insider attackers. The very focus of this research is to develop a trust management scheme for securing routing from insider attackers to launch blackhole and greyhole attacks. We proposed a trust management scheme, named as MT-SECURER (“Multi Factors Trust for Secure and Reliable Routing in MANETs”), for making routing secure against insider attackers (i.e., blackhole and greyhole attackers). This scheme develops trust from multiple factors, i.e., “node’s cooperation” from communication networks and “node’s relationship maturity” and “mutual friends” from social networks. Whereas for trust development, nodes’ personal observations along with neighbours’ recommendations are utilized. Neighbors’ recommendations, having a pivotal role in computation of trust, if hampered may entail in colossal attacks from dishonest trust recommenders such as “bad mouthing”, “ballot stuffing” and “random opinion”. Therefore, mitigation of dishonest trust recommendations has emerged as a stimulating research issue in trust management systems. In order to cater these challenges associated with dishonest trust recommendations, a technique named “intelligently Selection of Trust Recommendations based on Dissimilarity factor (iSTRD)” has been devised. iSTRD exploits observer node’s personal experience in conjunction with majority vote of the recommenders for removing dishonest trust recommendations. For performance analysis, MT-SECURER is used with AODV and DSR routing protocols and detail simulations are performed in order to examine the proposed scheme’s effectiveness in presence of blackhole and greyhole attackers and nodes’ mobility. The experimental results show significant improvement in “detection rate”, “packet delivery ratio”, throughput and “normalized routing load” with slightly increased “average end-to-end delay” when compared to contemporary schemes. Furthermore, iSTRD successfully removes the trust recommendations of “low trustworthyrecommenders” aswellasdishonesttrustrecommendationsof“highlytrustworthy recommenders”. Its efficacy is evident from enhanced accuracy of “recognition rate”, “false rejection” and “false acceptance”. Moreover, experiential results depict that iSTRD has unprecedented performance compared to contemporary techniques in presence of “bad mouthing”, “ballot stuffing” and “random opinion” attacks.