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In Ad-hoc networks every single node or station takes the responsibility to forward the data packets from the nodes that lie in the range with them. This additional routing responsibility might lead to performance degradation in some cases. Moreover, it is also reported that TCP which is designed for wired networks exhibit poor performance in terms of throughput and fairness in ad-hoc networks. Attempts to alleviate this issue included solutions from both TCP and MAC layer protocol modifications. This work aims at in-depth analysis of MAC level solutions (basic 802.11, 802.11 with RTS/CTS and Collision Detection Mechanism Based-MAC) to address TCP unfairness problem in 802.11-based multi-hop networks. A set of simulation based experiments are conducted and their observations are analyzed using metrics like throughput, goodput and loss probability. The metric loss probability is taken to investigate the protocols both from the perspective of congestion and collision i.e. the impact of congestion window and contention procedure on the end-to-end performance. The results obtained from the simulation revealed the inefficiency of the CDMB-MAC in the scenarios where hidden and exposed terminals do not exist. Further when TCP congestion window is set to 1 the basic 802.11 MAC is found sufficient to provide higher throughput with better fairness among the TCP connections but when TCP congestion window size is increased to 32 the 802.11 MAC with RTS/CTS scheme gives better performance. Added to this all the three MAC protocols fail in the scenario where the source and destination of a connection lie in the transmission ranges of destination and source of other connections. Therefore it can be concluded that it is indispensable to design an adaptive MAC protocol that could provide Fairness among TCP connections in all scenarios.

In Ad-hoc network, Packet reorder is effect of many causes like congestion loss, packet loss due to corruption, multi-path routing and node’s mobility. Transmission Control Protocol (TCP) performs poorly over wireless links which misinterprets the reordered packets as lost packets due to congestion. This has motivated researchers on developing TCP variants towards packet reordering problem for enhancing TCP performance. Some researchers have found the opportunity to use existing TCP variants like SACK, TCP-Westwood to address the reordering problem. TCP-DCR (TCP-Delayed Congestion Response) and RR-TCP (Reordering Robust TCP) are the TCP variants to acknowledge the packet reordering at the end level. In the existing investigations, the protocols were tested in a simulation environment with one or two causes (congestion or error) at a time over a simple topology. In our experiments, the simulation study of TCP variants has been done with all reordering causes simultaneously, over a large ad-hoc environment including mobility and multi-path routing. A performance analysis had been done using reordering metric (percentage of reordering) which accounts for earlier and lately arriving reordered packets and estimated using throughput and goodput metrics. From our analysis, it is observed that the Selective acknowledgement option of SACK-TCP and the delayed congestion response of DCR help to achieve better performance than other variants in presence of low reordering due to high congestion and low error. However, these variants were failed to meet up their performance in case of high reordering (reordering greater than 50%) due to high congestion loss and high channel error losses. This observation has given the research opportunity to incorporate a discrimination algorithm in the existing reordering solutions to classify the packet error from packet reordering.

The work aims at developing an algorithm for passive detection of copy move forgery in digital images. Accessibility and manipulability of the diverse and sophisticated digital image editing and processing tools has made the integrity of digital images debatable. The sensitivity and importance of the very many applications that revolve around digital images demand absolute authenticity of the digital images. As much simple as image tampering been made by the image editing tools, that much difficult the tampering detection process has become. In this work, a tamper detection method has been proposed that employs polar cosine transform for feature extraction and multi-dimensional spectral hashing for feature matching. The algorithm starts by dividing the image into overlapping patches and then feature vectors are extracted from the patches using Polar Cosine Transform (PCT) and similar patches are identified using multi-dimensional spectral hashing. Finally, post-verification is done to filter out false detection of forged regions. The multidimensional spectral hashing based method uses the outer product Eigen function to improve the performance of similar patch identification. The performance of the algorithm is measured in terms of precision F1 score and recall. Experimental results show that the multi-dimensional spectral hashing based identification of similar patches gives better results compared to some of the existing hashing based techniques. The proposed method proves to be effective in authenticating digital images which are employed in many fields like forensics, medicine, mass media etc.