Dil Muhammad Akbar Hussain

Terrorist Networks Analysis through Argument Driven Hypotheses Model

Social network analysis has been used for quite some time to analyze and understand the behavior of nodes in the network. Theses nodes could be individuals or group of persons, events or organizations, etc. In fact these nodes could be any thing, importantly, these nodes propagate or do some thing and obviously these nodes have attributes. Social network analysis (SNA) is a multi-model multi-link problem and one can imagine the challenge posed by such multidimensional task. Typically, models represent various processes and their organization including the interaction between processes. Such types of models are intellective simulation models, explaining one particular aspect of the model abstracting other factors present in the model. The standard or normal representation of a typical social network model is through a graph data structure. The dynamics of larger social networks is so complex some time it becomes difficult to understand the various levels of interactions and dependencies just by mere representation through a graph. However, to overcome this limitation many analytical methods provide relationship dependencies, role of different nodes and their importance in the social networks. Since the start of the new century many terrorism events have occurred around the globe. These events have provided a new impetus for the analysis, investigation, studying the behavior and tracking terrorist networks (individuals). In this paper we are presenting a very novel and absolutely new approach to SNA for locating important key players in the network. The system also predicts a path through these nodes which shows the vulnerability of the network and if the path along with these nodes is removed it can reduce/destabilize or even destroy the structure of the network

Dynamical Adaptation in Terrorist Cells/Networks

Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long history of their successful use in revealing the importance of various members of the network. However, modeling of covert, terrorist or criminal networks through social graph dose not really provide the hierarchical structure which exist in these networks as these networks are composed of leaders and followers etc. In this research we analyze and predict the most likely role a particular node can adapt once a member of the network is either killed or caught. The adaptation is based on computing Bayes posteriori probability of each node and the level of the said node in the network structure.

A nonlinear attitude estimator for attitude and heading reference systems based on mems sensors

In this paper, a nonlinear attitude estimator is designed for an Attitude Heading and Reference System (AHRS) based on Micro Electro-Mechanical Systems (MEMS) sensors. The design process of the attitude estimator is stated with detail, and the equilibrium point of the estimator error model is proved to be asymptotically stable using LaSalles invariance set theorem through limitation of the range of scalar element of quaternion without affecting practical use. Also, a new Lyapunov candidate function, satisfying continuously differentiable positive definite requirement, is presented to avoid the problems in previous research works. Moreover, the estimation of MEMS gyroscope bias is also inclueded in this estimator. The designed nonlinear attitude estimator is firstly tested in simulation environment and then implemented in an AHRS hardware for further experiments. Finally, the attitude estimation results from the designed AHRS are compared with a high-precision commercial AHRS to validate its estimation performance.

Attacks and their defenses for advanced metering infrastructure

The smart grid is the digitized, modernized, updated version of archaic traditional electric grid. Advanced Metering Infrastructure (AMI) is an imperative part of the smart grid. It has replaced legacy metering, as it reports the energy consumption to the utility automatically through communication channels. AMI is also featuring to communicate control functions from utility to the smart meters. So, both the consumption data and control data needs to be securely transmitted to their ends. Any leak and tempering may produce the dire effects to both utility and consumers. Hence security of AMI is a very important concern to take real advantage of this technology. In this paper, first we analyze the security threats faced by AMI components and then propose the countermeasures to tackle them. The aim is to visualize the possible threats in the context of confidentiality, integrity and availability (CIA Triad) context and propose countermeasure.