Issues of Ethnic Diversity and Just Development in Pakistan with a Special Focus on the Seraiki Ethnic Group

Ethnicity implies the sense of belonging together as the cultural group in a given society. It is a complex combination of racial, cultural and historical characteristics by which people differentiate themselves from other groups. This research envisages the genesis and the evolution of ethnicity as a political concept, the problems of ethnicity in a heterogeneous, multicultural state and the phenomenon of ethno-nationalism in its historical and analytical perspective in the federation of Pakistan with special reference to the status of Seraiki ethnic group. In fact ethnic expressions exist in all multicultural states and distinct ethnic groups evaluate themselves through communal prism. The less privileged groups develop abhorrence against the over – privileged groups due to the persistence of socioeconomic injustices. Factors like the gap between core and periphery, asymmetrical modernization and authoritarian trends lead towards ethnic disruption. Same is the case with Pakistan, a multilingual, multiracial and multiethnic state with federating units reflecting various diversities. The analysis of ethno-nationalism in Pakistan highlights factors, like regional cultural identity, relative deprivation among regions, centralized state structure, denial of accepting regional language as national language, and the absence of democratic values as being the root causes of the Bengali separatism. The assimilationist policies of the government do not acknowledge the regional/ethnic aspirations. Denial of pluralistic approach has been thwarting the demand for provincial autonomy. The nature of ethnic consciousness in the Seraiki belt, analyzed in this article, is found to be nurtured by the perceived socio-economic injustice at intra-provincial level—between the regions of South Punjab and Central and Northern Punjab put together

Q-Gram Based Encrypted Codeword Dictionary for Fast Searches over a Large Collection of Encrypted Unstructured Documents

With the advent of cloud computing, many businesses prefer to store their unstructured documents over the cloud. The preference is to store the encrypted unstructured document over the cloud for security. In most of these instances, one of the main criteria is to support fast searches without requiring any form of decryption. It is thus important to develop methods and architectures that can perform fast searches without compromising security and return the rank results for a client query. The proposed scheme use the enhanced version of the symmetric encryption algorithm for unstructured documents and develops a novel secure searchable hierarchical in-memory indexing scheme for each encrypted document using multiple Bloom filters and construct a dictionary over a large collection of encrypted unstructured documents. The dissertation also proposes a method to perform parallel rank searches over a large collection of encrypted unstructured documents. This is a novel contribution that proposes a methodology of constructing a dictionary using hierarchical in-memory index for performing fast and parallel rank searches over a large collection of encrypted unstructured documents. It introduces the concept of Q-gram and X-gram to represent the sizes of secure words in a single keyword and multiple keyword setups for building the encrypted searchable index, and provide multiple Bloom filters for a given encrypted unstructured document or a chunk to build encrypted searchable indexes using a separate Bloom filter for a set of bytes. The proposed construction enables fast rank searches over encrypted unstructured documents. A detailed study of 44 billion codewords worked out using off the shelf serves to demonstrate the effectiveness of single keyword Layer Indexing method. A detailed study of up to 1 billion codewords from a patient health care data is worked out using of the shelf serves to demonstrate the effectiveness of M-Index method.