Department of Computer Science & Engineering

&ldquo;IIT Jodhpur is committed to impart quality education to facilitate the creation of qualified, competent and responsible human resources to meet the emerging technological challenges of the world. It is working towards creating an equitable learning platform that is positive, accessible and effective in the face of the modern societal and scientific advancements.

Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

The lifetime of sensor network depends on the efficient utilization of resource-constrained sensor nodes. Several MAC protocols like DMAC and its variants have been proposed to save critical sensor resources through sleep-wakeup scheduling over data gathering tree. For applications where data aggregation is not possible, the sleep duration decreases gradually from the leaves to the root of the data gathering tree. This results early failure of sensor nodes near the sink, and affects network connectivity and coverage. Deploying redundant sensors can solve this problem where a faulty node is replaced by a redundant node to maintain network connectivity and coverage. However, the amount of redundancy depends on the node failure pattern, and thus more number of redundant nodes required to be deployed near the sink. This paper proposes a gradient based sensor deployment scheme for energy-efficient data gathering exploring the trade-off among connectivity, coverage, fault-tolerance and redundancy. The density of deployment is estimated based on the distance of a node from the sink while dealing with connectivity, coverage and fault-tolerance. The effectiveness of the proposed scheme has been analyzed both theoretically and with the help of simulation. © 2013 IEEE.

World University root node

2013 9th International Wireless Communications and Mobile Computing Conference, IWCMC 2013

Exploring gradient in sensor deployment pattern for data gathering with sleep based energy saving

Graph algorithms play a prominent role in several fields of sciences and engineering. Notable among them are graph traversal, finding the connected components of a graph, and computing shortest paths. There are several efficient implementations of the above problems on a variety of modern multiprocessor architectures. It can be noticed in recent times that the size of the graphs that correspond to real world data sets has been increasing. Parallelism offers only a limited succor to this situation as current parallel architectures have severe short-comings when deployed for most graph algorithms. At the same time, these graphs are also getting very sparse in nature. This calls for particular work efficient solutions aimed at processing large, sparse graphs on modern parallel architectures. In this paper, we introduce graph pruning as a technique that aims to reduce the size of the graph. Certain elements of the graph can be pruned depending on the nature of the computation. Once a solution is obtained for the pruned graph, the solution is extended to the entire graph. We apply the above technique on three fundamental graph algorithms: breadth first search (BFS), Connected Components (CC), and All Pairs Shortest Paths (APSP). To validate our technique, we implement our algorithms on a heterogeneous platform consisting of a multicore CPU and a GPU. On this platform, we achieve an average of 35% improvement compared to state-ofthe- art solutions. Such an improvement has the potential to speed up other applications that rely on these algorithms. © 2013 IEEE.

20th Annual International Conference on High Performance Computing, HiPC 2013

Work efficient parallel algorithms for large graph exploration

Generalized Feistel network (GFN) is a widely used design for encryption algorithm such as DES, IDEA and others. Generally, block ciphers are used not only for symmetric encryption but also as building blocks of cryptographic hash functions in modes such as Matyas-Meyer-Oseas (MMO) and Miyaguchi-Preneel. For these compression function modes, block ciphers are used with a key that is known to the attacker. Therefore a known-key distinguisher on the internal block cipher can be directly converted into a distinguisher on the compression function. In other words, the security of a compression mode relies on the security of the internal block cipher used. The security of the cipher in known-key setting is only due to the round function. Block ciphers popularly use sub-key XOR-ing followed by one or more SP-functions as the building block of a round function. The general understanding is that increasing the number of active S-boxes will cause more confusion and guarantee more secure ciphers against differential and linear cryptanalysis. In Indocrypt 2012, Sasaki compared the security of single-SP function with double-SP function and successfully mounted a distinguisher up to 7-round for 4-branch type-2 GFN with double-SP functions and up to 11-rounds of 2-branch single-SP functions by using the rebound attack technique. Based on the total number of S-boxes used and the number of rounds attacked, he argued that double-SP is in fact weaker than single-SP. The basis of this result is the number of rounds that the author could attack. In this work, we successfully increase the number of rounds attacked from 7 to 8 for 4-branch type-2 double-SP. The presented distinguisher is the first known distinguisher for 8 round 4-branch type-2 GFN with double SP-function. In our attack, we use an improved matching technique which is simpler than the byte-by-byte matching. This simple matching technique results in better complexity than the previously known 7 round distinguisher for most of the practical cases, allowing us to attack one extra round. © 2013 Springer International Publishing Switzerland.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Security analysis of GFN: 8-round distinguisher for 4-branch type-2 GFN

Recently Gao et al. proposed a lightweight RFID mutual authentication protocol [3] to resist against intermittent position trace attacks and desynchronization attacks and called it RIPTA-DA. They also verified their protocol’s security by data reduction method with the learning parity with noise (LPN) and also formally verified the functionality of the proposed scheme by Colored Petri Nets. In this paper, we investigate RIPTA-DA’s security. We present an efficient secret disclosure attack against the protocol which can be used to mount both de-synchronization and traceability attacks against the protocol. Thus our attacks show that RIPTA-DA protocol is not a RIPTA-DA. © Springer-Verlag Berlin Heidelberg 2013.

Desynchronization and traceability attacks on RIPTA-DA protocol

Recognizing text in images taken in the wild is a challenging problem that has received great attention in recent years. Previous methods addressed this problem by first detecting individual characters, and then forming them into words. Such approaches often suffer from weak character detections, due to large intra-class variations, even more so than characters from scanned documents. We take a different view of the problem and present a holistic word recognition framework. In this, we first represent the scene text image and synthetic images generated from lexicon words using gradient-based features. We then recognize the text in the image by matching the scene and synthetic image features with our novel weighted Dynamic Time Warping (wDTW) approach. We perform experimental analysis on challenging public datasets, such as Street View Text and ICDAR 2003. Our proposed method significantly outperforms our earlier work in Mishra et al. (CVPR 2012), as well as many other recent works, such as Novikova et al. (ECCV 2012), Wang et al. al.(ICPR 2012), Wang et al.(ICCV 2011). © 2013 IEEE.

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR

Whole is greater than sum of parts: Recognizing scene text words

In this paper, a dynamic texture based compression scheme is devised for videos. Correspondence analysis is explored for the analysis of motion patterns in a video on the basis of optic flow data and then clusters of different motion patterns are created. Dynamic textures tend to disobey Horn and Schunck's assumption of brightness constancy and hence, optic flow residual is used as an indicator of their presence. The correspondence analysis results and optic flow residual are combined together in a new segmentation scheme. The optic flow data tracks the motion of groups of pixels to generate the flow lines. These flow lines are used in a synthesis scheme for creating an illusion of continuously flowing texture. The integration of this synthesis scheme in the compression format gives us considerable bit stream reduction corresponding to the dynamic texture regions. The scheme is integrated with standard H.264/AVC model, texture regions that do not fall under the above precinct of dynamic textures and non-texture regions are encoded-decoded by the H.264 model directly. © 2013 IEEE.

2013 National Conference on Communications, NCC 2013

Dynamic texture synthesis for video compression

In this paper we propose a novel multi-agent planning framework that attempts to deal with dynamic nature of cyber physical system while planning and show usefulness of our approach in exploring different strategies and configurations of planning architecture. The proposed approach use multi-agent planners at different layers of abstraction to collaborate by using concepts of task sharing, brokering of task allocation, continuous adaptive planning and blackboard based multi-agent interaction. © Springer-Verlag 2013.

C-MAP: Framework for multi-agent planning in cyber physical systems

Heritage preservation requires preserving the tangibles (monuments, sculpture, coinage, etc) and the intangibles (history, traditions, stories, dance, etc). Besides these artefacts, there is a huge amount of background knowledge that correlates all these resources and establishes their context. In this work, we present a new paradigm for heritage preservation - 'an Intellectual Journey into the past', which is more advanced than physical explorations of heritage sites and virtual explorations of monuments and museums. This paradigm proposes an experiential expedition into a historical era by using an ontology to inter-link the digital heritage artefacts with their background knowledge. A multimedia ontology encoded in the Multimedia Web Ontology Language (MOWL) is used to illustrate this paradigm by correlating the digital artefacts with their history as well their living context in today's world. The user experience of this paradigm involves a virtual traversal of a heritage site, with an ontology guided navigation through space and time and a dynamic display of different kinds of media. © 2013 Springer-Verlag.

An intellectual journey in history: Preserving Indian cultural heritage

Recently Saliency maps from input images are used to detect interesting regions in images/videos and focus on processing these salient regions. This paper introduces a novel, macroblock level visual saliency guided video compression algorithm. This is modelled as a 2 step process viz. salient region detection and frame foveation. Visual saliency is modelled as a combination of low level, as well as high level features which become important at the higher-level visual cortex. A relevance vector machine is trained over 3 dimensional feature vectors pertaining to global, local and rarity measures of conspicuity, to yield probabilistic values which form the saliency map. These saliency values are used for non-uniform bit-allocation over video frames. To achieve these goals, we also propose a novel video compression architecture, incorporating saliency, to save tremendous amount of computation. This architecture is based on thresholding of mutual information between successive frames for flagging frames requiring re-computation of saliency, and use of motion vectors for propagation of saliency values. © 2013 Elsevier B.V. All rights reserved.

Signal Processing: Image Communication

Visual saliency guided video compression algorithm

This paper addresses the problems encountered during digitization and preservation of inscriptions such as perspective distortion and minimal distinction between foreground and background. In general inscriptions neither possess standard size and shape nor colour difference between the foreground and background. Hence the existing methods like variance based extraction and Fast-ICA based analysis fail to extract text from these inscription images. Natural gradient Flexible ICA (NGFICA) is a suitable method for separating signals from a mixture of highly correlated signals, as it minimizes the dependency among the signals by considering the slope of the signal at each point. We propose an NGFICA based enhancement of inscription images. The proposed method improves word and character recognition accuracies of the OCR system by 65.3% (from 10.1% to 75.4%) and 54.3% (from 32.4% to 86.7%) respectively. © 2013 IEEE.