ARPNetSteg: Network Steganography using Address Resolution Protocol

Steganography is a technique that allows hidden transfer of data using some media such as Image, Audio, Video, Network Protocol or a Document, without its existence getting noticed. Over the past few years, a lot of research has been done in the field of Image, Video and Audio Steganography but very little work has been done in Network Steganography. A Network Steganography technique hides data in a Network Data Unit, i.e., a Network Protocol Packet. In this paper we present an algorithm ARPNetSteg that implements Network Steganography using the Address resolution protocol. Our technique is a robust technique that can transfer 44 bits of covert data per ARP reply packet

Social Collaborative Retrieval

Socially-based recommendation systems have recently attracted significant interest, and a number of studies have shown that social information can dramatically improve a system's predictions of user interests. Meanwhile, there are now many potential applications that involve aspects of both recommendation and information retrieval, and the task of collaborative retrieval---a combination of these two traditional problems---has recently been introduced. Successful collaborative retrieval requires overcoming severe data sparsity, making additional sources of information, such as social graphs, particularly valuable. In this paper we propose a new model for collaborative retrieval, and show that our algorithm outperforms current state-of-the-art approaches by incorporating information from social networks. We also provide empirical analyses of the ways in which cultural interests propagate along a social graph using a real-world music dataset.Comment: 10 page

APSO based automated planning in Constructive Simulation

Constructive simulations are the applications used by the military for the training of their commanders in planning and analysis of various threats and Courses of Action. In the ‘analysis wargames’, there are need to automate many of the tasks of the commander which are carried out by subunit commanders on the ground. Deployment of defence units is one of such important decision making by commander. Deployments of units (and sub units) is dependent on multiple factors which needs to be satisfied/optimised for meeting the given objective of the unit. In this paper we have attempted to solve the multi criterion decision problem of optimal deployment of defence units in mountainous terrain using Particle Swarm Optimization(PSO) and Adaptive Particle Swarm Optimization(APSO). The algorithm has been tested with varied number of decision parameters and their weights using digital elevation and vector data of the terrain features. The auto deployment outcomes are found satisfactory. Our solution approach has potential in automated planning in constructive simulations.   &nbsp

Command Agent Belief Architecture to Support Commander Decision Making in Military Simulation

In the war, military conflicts have many aspects that are consistent with complexity theory e.g., the higher commander’s decision is directed at animate entity that react under hierarchical and self-organised structure in decentralised command and control for the collectivist dynamism of decomposed elements due to nonlinear complexity of warfare on the battlefield. Agent technology have been found to be suitable for modelling tactical behaviour of entities at multiple level of resolution under hierarchical command and control (C2) structure and provide a powerful abstraction mechanism required for designing simulations of complex and dynamic battlefield situations. Intelligent agents can potentially reduce the overhead on such experiments and studies. Command agents, plan how to carry out the operation and assign tasks to subordinate agents. They receive information from battlefield environment and use such information to build situation awareness and also to respond to unforeseen situations. In the paper, we have proposed a mechanism for modelling tactical behaviour of an intelligent agent by which higher command level entities should be able to synthesize their beliefs derived from the lower level sub ordinates entities. This paper presents a role-based belief, desire and intention mechanism to facilitate in the representation of military hierarchy, modelling of tactical behaviour based on agent current belief, teammate’s belief propagation, and coordination issues. Higher commander can view the battlefield information at different levels of abstraction based on concept of aggregation and disaggregation and take appropriate reactive response to any unforeseen circumstances happening in battlefield