http://repository.iiitd.edu.in/xmlui/handle/123456789/219 Fri, 10 Apr 2026 20:26:45 GMT 2026-04-10T20:26:45Z http://repository.iiitd.edu.in/xmlui/handle/123456789/385 A fail-fast mechanism for authenticated encryption schemes Gupta, Naina; Chang, Donghoon (Advisor) In the modern world, almost every computing device uses some cryptographic technique or the other. Over the years several schemes have been proposed implemented and standardized. For any kind of data transfer the primary goals are encryption and authentication. Historically, these two goals are achieved separately, via two different techniques. Any symmetric cipher scheme can be used for encryption, whereas, for authentication, usage of a keyed MAC is prevalent. There is another approach known as Authenticated Encryption (AE), which fulfills both the goals at the same time. From an implementation perspective, it is important that, if the packet is malformed, it is rejected as soon as possible. Common techniques like AES-CBC, allow for such a fail-fast paradigm using padding oracle. But, the same technique cannot be applied for other common AE techniques like AES-GCM. In this work, we provide a technique using which any AE scheme can be used directly (without any change), whilst providing the good fail-fast features at the same time. Fri, 01 Jan 2016 12:23:32 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/385 2016-01-01T12:23:32Z http://repository.iiitd.edu.in/xmlui/handle/123456789/361 Top-K high utility episode mining in complex event sequence Rathore, Sonam; Goyal, Vikram (Advisor) Mining high utility episodes in complex event sequences is an emerging topic in data mining. In utility mining, users set a minimum threshold and the episodes having higher utility than the threshold are reported. The utility framework introduced in episode mining provides more informative and usable knowledge as compared to frequent episode mining. However, it is difficult for the user to set an appropriate minimum utility thresh- old. As the user cannot predict the count of mined episodes by the utility threshold, the number of reported episodes can vary hugely in accordance to the set threshold. To address this issue, in this thesis we propose an algorithm for mining Top-K high utility episode in complex event sequence. It discovers episodes with highest utility to ones with kth highest utility where the user can set the desired count of episodes, k. We also propose two different strategies to reduce the search space by raising the minimum threshold e ectively. We conduct experiments on real dataset and show the effectiveness of our approach. Sat, 05 Dec 2015 06:10:35 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/361 2015-12-05T06:10:35Z http://repository.iiitd.edu.in/xmlui/handle/123456789/360 Face detection and verication in unconstrained videos: challenges, detection, and benchmark evaluation Shah, Mahek; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) With increasing security concerns, surveillance cameras are playing an important role in the society and face recognition in crowd is gaining more importance than ever. For video face recognition, researchers have primarily focused on controlled environments with a single person in a frame. However, in real world surveillance situations, the environment is unconstrained and the videos are likely to record multiple people within the eld of view. Surveillance videos encompass multiple challenges for face detection and face recognition. For instance, detection algorithms may be a ected due to size of a face image, occlusion, pose, illumination, and background while recognition algorithms may be a ected due to low resolution, occlusion, pose, illumination, and blurriness. State-of-the-art approaches for both face detection and face recognition in such challenging scenarios are currently in nascent stages. Moreover, due to the unavailability of such databases, it is difficult for researchers to pursue this important challenge. This thesis attempts to ll the gap in unconstrained face recognition in two ways:develop a large unconstrained video face database, and create a benchmark protocol and perform baseline experiments for both face detection and recognition. As the rst contribution of this thesis, a large video database of 384 videos consisting of 258 subjects is prepared. Each video generally contains multiple subjects in unconstrained settings. Further, ground truth for face and landmark (eye and mouth) detection is manually annotated. As the second contribution of this thesis, we design a benchmark protocol for face detection and recognition evaluation. Using the protocols, we evaluate existing face detection and face recognition approaches, including commercial systems. Poor face detection and veri cation results showcase the challenging nature of the problem and the database. Sat, 05 Dec 2015 06:04:24 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/360 2015-12-05T06:04:24Z http://repository.iiitd.edu.in/xmlui/handle/123456789/359 TASVEER : tomography of India's internet infrastructure Singh, Rahul Kumar; Chakravarty, Sambuddho (Advisor) With approximately 250 million Internet users, India stands amongst the top 5 Internet using nations of the world. India's network space is made up of 789 Autonomous Systems (ASes), that route all the network traffic of India. On the other hand, US has approximately 300 million users, whose traffic is routed over 22K ASes. Thus, a relatively small network routes the traffic of large number of Indian users. Failures and attacks in such networks could impact large number of users. However, being a relatively small number, it becomes easy to generate maps presenting the connectivity of ASes in the networks and the routers that make up the ASes. Such information could be used for various purposes such as diagnosing network failures and attacks, large scale network surveillance and bypassing such surveillance, load balancing, efficient content distribution and delivery. We present, a first effort to our knowledge, the topological information of India's entire Internet space representing the connectivity between all 789 ASes and intra-domain routers. Our research presents information of routers and ASes that transport relatively large fraction of tra c for vital network installations like popular ISP users, important organizations like nancial institutions, educational institutions, research organizations etc. Thu, 03 Dec 2015 13:08:14 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/359 2015-12-03T13:08:14Z