Department of Computer Science & Engineering

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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

Recently, the concept of Internet of Vehicles (IoVs) conquered the automotive industry, academia, research fields, vehicle manufacturers, etc., where vehicles are 'intelligent ones' capable of providing a wide variety of applications, such as traveller/driver safety, infotainment, traffic efficiency, reduced congestion, less pollution, etc. Ensuring proper authentication and secure communication are the major challenges of an IoV scenario. However, only limited works are available for authentication and communication, among them the 'lightweight property' is missing. Hence, in this paper, we design a lightweight mutual authentication protocol in an IoV scenario using cryptographic operations. The proposed protocol also enables a device and a server to establish a secret key, which can be used for secure communication, while minimizing the computational cost associated with the process. The protocol is implemented on two types of communication models, such as two Raspberry Pi's connected via an intermediate desktop computer acting as the Trusted Authority (TA) and two Raspberry Pi's connected via the cloud (here, Vehicle Server). The performance analysis results based on computation and communication cost show that the proposed protocol performs better than existing systems. © 1967-2012 IEEE.

World University root node

IEEE Transactions on Vehicular Technology

A lightweight mutual authentication protocol for V2V communication in internet of vehicles

Sensing the presence of occupants and estimating the occupancy level in an indoor environment are the fundamental requirements for various applications performing remote monitoring, home automation and optimal resource planning. Data generated from a set of passive heterogeneous sensors deployed for this purpose are multimodal and streaming in nature. This work aims to formulate the human occupancy estimation in an indoor environment as a multi-class problem and proposes a edge-based data management framework for human occupancy estimation. The proposed framework is low-cost and light-weight in addition to being capable of performing real-time inference. Also testbed experimentation results is provided to justify the performance of the proposed scheme. © 2020 IEEE.

2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020

A Study on Real-Time Edge Computed Occupancy Estimation in an Indoor Environment

A catalytic Turing machine is a model of computation that is created by equipping a Turing machine with an additional auxiliary tape which is initially filled with arbitrary content; the machine can read or write on auxiliary tape during the computation but when it halts auxiliary tape’s initial content must be restored. In this paper, we study the power of catalytic Turing machines with O(logn) -sized clean tape and a polynomial-sized auxiliary tape.We introduce the notion of randomized catalytic Turing machine and show that the resulting complexity class CBPL is contained in the class ZPP . We also introduce the notion of symmetricity in the context of catalytic computation and prove that, under a widely believed assumption, in the logspace setting the power of a randomized catalytic Turing machine and a symmetric catalytic Turing machine is equal to a deterministic catalytic Turing machine which runs in polynomial time.

International Computer Science Symposium in Russia

Randomized and Symmetric Catalytic Computation

This paper presents an Optical Character Recognition (OCR) system for documents with English text and mathematical expressions. Neural network architectures using CNN layers and/or dense layers achieve high level accuracy in character recognition task. However, these models require large amount of data to train the network, with balanced number of samples for each class. Recognition of mathematical symbols poses challenges of the imbalance and paucity of training data available. To address this issue, we pose the character recognition problem as a Distance Metric Learning problem. We propose a Siamese-CNN Network that learns discriminative features to identify if the two images in a pair contain similar or dissimilar characters. The network is then used to recognize different characters by character matching where test images are compared to sample images of any target class which may or may not be included during training. Thus our model can scale to new symbols easily. The proposed approach is invariant to author’s handwriting. Our model has been tested over images extracted from a dataset of scanned answer scripts collected by us. It is seen that our approach achieves comparable performance to other architectures using convolutional layers or dense layers while using lesser training data. © 2020, Springer Nature Singapore Pte Ltd.

Department of Electrical Engineering

Communications in Computer and Information Science

DocDescribor: Digits + Alphabets + Math Symbols - A Complete OCR for Handwritten Documents

In recent years, Physically Unclonable Functions (PUFs) have emerged as a promising technique for hardware based security primitives because of its inherent uniqueness and low cost. In this paper, we present an area efficient hybrid PUF design on field-programmable gate array (FPGA). Our approach combines units of conventional RS Latch-based PUF (RS-LPUF) and Arbiter-based PUF (A-PUF) which is then augmented by the programmable delay lines (PDLs) and Temporal Majority Voting (TMV) for performance enhancement. The area of the hybrid PUF is relatively high when compared to few conventional PUF designs, but is significantly small when compared to other composite and hybrid PUF designs reported so far. The measured results on the Xilinx Spartan-6 FPGA demonstrate PUF signatures exhibits good uniqueness, reliability, and uniformity with no occurrence of bit-aliasing. © 2020

Microprocessors and Microsystems

Efficient and Lightweight FPGA-based Hybrid PUFs with Improved Performance

True random number generators (TRNGs) play a fundamental role in cryptographic systems. This brief presents a new and efficient method to generate true random numbers on field programmable gate array (FPGA) by utilizing the random jitter of free-running oscillators as a source of randomness. The free-running oscillator rings incorporate programmable delay lines (PDLs) to generate large variation of the oscillations and to introduce jitter in the generated ring oscillators clocks. The main advantage of the proposed TRNG utilizing PDLs is to reduce correlation between several equal length oscillator rings, and thus improve the randomness qualities. In addition, a Von Neumann corrector as post-processor is employed to remove any bias in the output bit sequence. The validation of the proposed approach is demonstrated on Xilinx Spartan-3A FPGAS. The proposed TRNG occupies 528 slices, achieves 6 Mb/s throughput with 0.999 per bit entropy rate, and passes all the national institute of standards and technology (NIST) statistical tests. © 2004-2012 IEEE.

IEEE Transactions on Circuits and Systems II: Express Briefs

FPGA-Based True Random Number Generation Using Programmable Delays in Oscillator-Rings

Grover’s algorithm provides a quantum attack against block ciphers by searching for a k-bit key using O(2k) calls to the cipher, when given a small number of plaintext-ciphertext pairs. Recent works by Grassl et al. in PQCrypto’16 and Almazrooie et al. in QIP’18 have estimated the cost of this attack against AES by analyzing the quantum circuits of the cipher. We present a quantum reversible circuit of ARIA, a Korean standardized block cipher that is widely deployed in government-to-public services. Firstly, we design quantum circuits for the main components of ARIA, and then combine them to construct the complete circuit of ARIA. We implement Grover’s algorithm-based exhaustive key-search attack on ARIA. For all three variants of ARIA-{128, 192, 256}, we establish precise bounds for the number of qubits and the number of Clifford + T gates that are required to implement Grover’s algorithm. We also estimate the G-cost as the total number of gates, and DW-cost as the product of circuit depth and width. To find the circuit depth of various circuits such as squaring, multiplier, and permutation layer, we implement them in an open-source quantum computing platform QISKIT developed by IBM. © 2020, Springer Nature Switzerland AG.

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

Quantum Resource Estimates of Grover’s Key Search on ARIA

Threshold Implementation (TI) is one of the most widely used countermeasure for side channel attacks. Over the years several TI techniques have been proposed for randomizing cipher execution using different variations of secret-sharing and implementation techniques. For instance, sharing without decomposition (4-shares) is the most straightforward implementation of the threshold countermeasure. However, its usage is limited due to its high area requirements. On the other hand, sharing using decomposition (3-shares) countermeasure for cubic non-linear functions significantly reduces area and complexity in comparison to 4-shares. Nowadays, security of ciphers using a side channel countermeasure is of utmost importance. This is due to the wide range of security critical applications from smart cards, battery operated IoT devices, to accelerated crypto-processors. Such applications have different requirements (higher speed, energy efficiency, low latency, small area etc.) and hence need different implementation techniques. Although, many TI strategies and implementation techniques are known for different ciphers, there is no single study comparing these on a single cipher. Such a study would allow a fair comparison of the various methodologies. In this work, we present an in-depth analysis of the various ways in which TI can be implemented for a lightweight cipher. We chose GIFT for our analysis as it is currently one of the most energy-efficient lightweight ciphers. The experimental results show that different implementation techniques have distinct applications. For example, the 4-shares technique is good for applications demanding high throughput whereas 3-shares is suitable for constrained environments with less area and moderate throughput requirements. The techniques presented in the paper are also applicable to other blockciphers. For security evaluation, we performed TVLA (test vector leakage assessment) on all the design strategies. Experiments using up to 50 million traces show that the designs are protected against first-order attacks. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

IEEE Transactions on Information Forensics and Security

Threshold Implementations of GIFT: A Trade-Off Analysis

Accuracy booster: Performance boosting using feature map re-calibration

During gameplay, a player experiences emotional turmoil. In most of the cases, these emotions directly reflect the outcome of the game. Adapting game features based on players’ emotions necessitates a way to detect the current emotional state. Researchers in the area of “video game user research” has studied biometric data as a way to address the diverse characteristics of players, their individual preferences, gameplay expertise, and experiences. Identification of the player’s current state is fundamental for designing a game, which interacts with the player adaptively. In this paper, we present an artificially intelligent game framework with smart features based on automatic facial expression recognition and adaptive game features based on the gamer’s emotion. The gamer’s emotions are recognized at run-time during gameplay using Deep Convolutional Neural Networks (CNN), and the game is adapted accordingly to the emotional condition. Once identified, these features directly modify critical parameters of the underlying game engine to make the game more exciting and challenging. © 2020, Springer Nature Singapore Pte Ltd.