Dr Priya Chandran

Abstract A group key agreement (GKA) protocol generates a secret key (session key) shared among the members of the group, from the contributions made by group members. \{GKA\} protocols are expected to satisfy the property of Implicit Key Authentication (IKA) which assures group members that the key generated by the protocol is not accessible to any member outside the group. In this article, we propose a technique to prove the correctness of \{GKA\} protocols with respect to IKA. We establish the soundness of our proposal and also illustrate its application. Normally İKA\} property of protocols is established by proving that the protocol satisfies authentication of participants and secrecy of the session keys. Most formal models would be able to analyze a \{GKA\} protocol with respect to IKA, using the above approach. However analysis of two security properties, namely authentication and secrecy, would increase the chances of errors. We propose a single condition for verifying whether the \{GKA\} protocol satisfies IKA.

"Virtualization is a vital part of computing today. Rollback is an important feature to be supported by virtualization. However, hackers leverage rollback and pose serious security threats to systems running in a virtualized environment. The aim of this paper is to identify such security threats and propose a comprehensive solution. In this paper, we propose Extended-HyperWall architecture as a solution to security of Virtual Machines (VMs) in a fully virtualized environment. Extended-HyperWall architecture is an integration of HyperWall with Rollback Sensitive Data Memory with Architecture Assistance (RSDM-A). HyperWall is a system that proposes hardware support to ensure confidentiality and integrity of a VM's data, with an assumption that hypervisor cannot be trusted. RSDM-A is an architectural support to a virtualized system that separates rollback sensitive data from rollback non-sensitive data which is one of the major causes of threats that arises due to rollback. Extended-HyperWall integrates CIP-table (Confidentiality and Integrity Table to ensure confidentiality and integrity of data) and RSDM-table (Rollback Sensitive Data Memory to protect the system from rollback attacks). The paper illustrates the design of Extended-HyperWall, and its implementation on the Xen Hypervisor kernel for testing and analysis."

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Simulation environments provide a comprehensive set of advantages to users, like cost effectiveness and capability to understand the shortcomings of the system under design, without physical implementation. Simulation platforms help the industry and academia, to document and publish their research outputs in a timely and cost efficient manner. The ECSim tool presented here, is meant for academic use in the initial stages of research. The platform provides an environment where the performance of erasure coded storage systems can be tested without much effort. The main highlight of the simulator is that it provides a very simple environment which can run on a standalone system. The environment does not require the user to be a programmer, since it provides an interactive command line interface to the user. The ability to simulate data center, clusters, master nodes, storage nodes with computing power, storage devices, bandwidth usage and disk I/O involved are notable features of ECSim.

Abstract Cloud-based MapReduce platforms offer ready to use MapReduce clusters. The problem of allocating Virtual Machines (VMs) carrying out the computation, for minimizing data transfer delay is a crucial one in this context, as the MapReduce tasks are communication intensive. The interaction between \{VMs\} may face varying delays, if the \{VMs\} are hosted in different Physical Machines (PMs). This work aims to optimize the data transfer delay between VMs, which is denoted by the distance between the VMs. We propose an approximation algorithm for \{VM\} allocation in data centers wherein the distances between \{VMs\} satisfy triangular inequality and an optimization algorithm for \{VM\} allocation in data centers where the distances between \{VMs\} do not satisfy triangular inequality. Simulations on CloudSim demonstrate the performance of our algorithms and the results affirm the reduction in job completion time compared to other allocation schemes.

Paper - 10's Abstract
Modeling communications between nodes in large-scale molecular interaction networks as information flows is useful for analyzing relationships between individual network components. Discovering causal genes and dysregulated pathways using network analysis based on information flow models is a very active, current topic of research. Recent research provides cubic order polynomial time solutions to the problem. Considering the huge size of interaction networks, calculating information flows can be costly, even with cubic order algorithms. An improvement to the computing time has been achieved by using the concept of approximation algorithms which are useful in solving large instances of problems requiring numerous resources. Proofs for the approximation factor and implementation results for the proposed algorithm are presented.