Department of Computer Science and Engineering

Indian Institute of Technology Hyderabad (IITH) is a premier institute of science and technology established in 2008. IITH has been consistently ranked in the&nbsp;<a href="https://iith.ac.in/reports/" rel="noopener noreferrer">top 10 institutes</a>&nbsp;in India for Engineering&nbsp;<a href="https://www.nirfindia.org/2021/EngineeringRanking.html" rel="noopener noreferrer" target="_blank">according to NIRF</a>&nbsp;making it one of the most coveted schools for science and technology in the country.

IITH offers&nbsp;<a href="https://iith.ac.in/academics/under-graduate/">undergraduate programs</a>&nbsp;in all the classical engineering disciplines, applied sciences, design, as well as several modern interdisciplinary areas. Students are given a flexibility to explore a broad set of areas, and potentially pursue a minor or double major in a discipline that is not their own. Students who wish to seek a deeper understanding of their own discipline are strongly encouraged to get involved in cutting-edge research with the help of a faculty to mentor them, and earn an Honors in their own field.

The very foundation of IIT Hyderabad is based on&nbsp;<a href="https://iith.ac.in/research/">research and innovation</a>. The vibrant research culture is evident from the number of patents and publications that IITH produces consistently every year. IITH offers&nbsp;<a href="https://iith.ac.in/academics/programmes-offered/">graduate programs</a>&nbsp;at both a masters, and a doctoral level, in several diverse areas. There are separate programs for technology, design, science, and liberal arts. The&nbsp;<a href="https://iith.ac.in/academics/post-graduate/">MTech program</a>&nbsp;is offered in various modes and durations to cater to the ever-growing need of postgraduate level professionals in the country.

IITH encourages and supports&nbsp;<a href="https://iic-iith.netlify.app/index.html" rel="noopener noreferrer" target="_blank">innovation and entrepreneurship</a>&nbsp;at every stage. The minor program in entrepreneurship is open to all students of IITH, and many of the courses are offered by industrialists who are entrepreneurs themselves. There are various&nbsp;<a href="https://iith.ac.in/research/centres-incubators/">innovation centers and incubators</a>&nbsp;that promote entrepreneurship and help mentor young innovators. IITH has been very successful in building tie-ups with leading academic institutions around the globe.

IITH enjoys a very special relationship with Japanese universities and industries that goes beyond academic and research collaborations. In fact, some of the iconic buildings in IITH campus will carry the signature of Japanese architecture.

IITH creates a unique holistic ecosystem for education that offers interactive learning, a very flexible academic structure, cutting-edge research, strong industry collaboration, and entrepreneurship. This is an environment which enables students and faculty to translate their dreams into realities.

IIT Hyderabad

IoT-based intrusions and network attacks are becoming ever more concerning. As a mitigatory measure, the IETF standardized Manufacturer Usage Description (MUD) which allows IoT device vendors to specify the legitimate communication patterns (as a MUD profile) of an IoT device. A MUD profile allows the validation of the actual communication pattern of an IoT device with the intended behavior at runtime. However, as the number of IoT devices increases, validation at runtime has scalability challenges in terms of the number of switch resources (e.g., TCAM) required to maintain MUD profiles.In this work, we propose a scalable data plane primitive and a system on top of the primitive, which together enforce MUD profiles of thousands of IoT devices in a P4 programmable switch data plane. Our main idea is to avoid inefficiencies because of the repetition of header values while representing MUD profile-based ACL rules. Further, we exploit the characteristics of header values in ACL rules of real IoT devices and carefully partition the rules across multiple hash-based exact match-action tables in the switch data plane. Since hash-based data structures can be implemented using SRAM which is cheap and abundantly available (order of MBs) in commodity programmable switches, our approach scales well for a large IoT network. © 2023 IEEE.

World University root node

Proceedings of IEEE/IFIP Network Operations and Management Symposium 2023, NOMS 2023

Scaling IoT MUD Enforcement using Programmable Data Planes

Many IoT use cases have ultra-low latency and strong security requirements. But achieving both simultaneously is challenging. In this paper, as a use case, we consider the authentication of IoT devices for every transaction and develop a fast and secure authentication protocol. Our key idea is to leverage highly secure Physically Unclonable Functions (PUFs) and high-speed programmable switch and offload PUF-based authentication protocol to the switch. By doing so, it enables authentication of every transaction at network speed. In this paper, we demonstrate the feasibility of our idea by offloading the authentication protocol to a programmable switch with Tofino chip. Our preliminary experiments show that protocol offloading reduces authentication latency by 2-4 times and scales to a few hundred thousand IoT devices. © 2023 IEEE.

Accelerating PUF-based Authentication Protocols Using Programmable Switch

Contemporary computing employs cache hierarchy to fill the speed gap between processors and main memories. In order to optimise system performance, Last Level Caches (LLC) are shared among all the cores. Cache sharing has made them an attractive surface for cross-core timing channel attacks. In these attacks, an attacker running on another core can exploit the access timing of the victim process to infiltrate the secret information. One such attack is called a cross-core Covert Channel Attack (CCA). Timely detection and then prevention of cross-core CCA is critical for maintaining the integrity and security of users, especially in a shared computing environment. In this work, we have proposed an efficient cross-core CCA mitigation technique. We propose a way-wise cache partitioning on targeted sets, only for the processes suspected to be attackers. In this way, the performance impact on the entire LLC is minimised and benign applications can utilise the LLC to its full capacity. We have used a cycle-accurate simulator (gem5) to analyse the performance of the proposed method and its security effectiveness. It has been successful in abolishing the cross-core covert timing channel attack with no significant performance impact on benign applications. It causes 23% less cache misses in comparison to existing partitioning based solutions while requiring ≈0.26% storage overhead. © 2022 Elsevier B.V.

Journal of Systems Architecture

TPPD: Targeted Pseudo Partitioning based Defence for cross-core covert channel attacks

Deep neural networks tend to reciprocate the bias of their training dataset. In object detection, the bias exists in the form of various imbalances such as class, background-foreground, and object size. In this paper, we denote size of an object as the number of pixels it covers in an image and size imbalance as the over-representation of certain sizes of objects in a dataset. We aim to address the problem of size imbalance in drone-based aerial image datasets. Existing methods for solving size imbalance are based on architectural changes that utilize multiple scales of images or feature maps for detecting objects of different sizes. We, on the other hand, propose a novel ARchitectUre-agnostic BAlanced Loss (ARUBA) that can be applied as a plugin on top of any object detection model. It follows a neighborhood-driven approach inspired by the ordinality of object size. We evaluate the effectiveness of our approach through comprehensive experiments on aerial datasets such as HRSC2016, DOTAv1.0, DOTAv1.5 and VisDrone and obtain consistent improvement in performance. © 2023 IEEE.

Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023

ARUBA: An Architecture-Agnostic Balanced Loss for Aerial Object Detection

Several recent works show that higher accuracy models may not be better teachers for every student, and hence, refer this problem as student-teacher "knowledge gap". Further, they propose techniques, which, in this paper, we discuss are constrained to certain pre-conditions: 1). Access to Teacher Model/Architecture 2). Retraining Teacher Model 3). Models in Addition to Teacher Model. Being well known that for a lot of settings, these conditions may not hold true challenges the applicability of such approaches. In this work, we propose RetroKD, which smoothes out the logits of a student network by leveraging students' past state logits with the ones from the teacher. By doing so, we hypothesize that the present target will no longer be as hard as the teacher target and not as more uncomplicated as the past student target. Such regularization on learning the parameters alleviates the needs as required by other methods. Our extensive set of experiments comparing against the baselines for CIFAR 10, CIFAR 100, and TinyImageNet datasets and a theoretical study further help in supporting our claim. We performed crucial ablation studies such as hyperparameter sensitivity, the generalization study by showing the flatness on loss landscape and feature similarly with teacher network. © 2023 ACM.

ACM International Conference Proceeding Series

RetroKD : Leveraging Past States for Regularizing Targets in Teacher-Student Learning

We investigate the parameterized complexity of finding diverse sets of solutions to three fundamental combinatorial problems. The input to the Weighted Diverse Bases problem consists of a matroid M, a weight function ω: E(M) → N, and integers k≥ 1 , d≥ 1. The task is to decide if there is a collection of kbasesB1, ⋯ , Bk of M such that the weight of the symmetric difference of any pair of these bases is at least d. The input to the Weighted Diverse Common Independent Sets problem consists of two matroids M1, M2 defined on the same ground set E, a weight function ω: E→ N, and integers k≥ 1 , d≥ 1. The task is to decide if there is a collection of kcommon independent setsI1, ⋯ , Ik of M1 and M2 such that the weight of the symmetric difference of any pair of these sets is at least d. The input to the Diverse Perfect Matchings problem consists of a graph G and integers k≥ 1 , d≥ 1. The task is to decide if G contains kperfect matchingsM1, ⋯ , Mk such that the symmetric difference of any two of these matchings is at least d. We show that none of these problems can be solved in polynomial time unless P=NP. We derive fixed-parameter tractable (FPT) algorithms for all three problems with (k, d) as the parameter, and present a poly(k, d) -sized kernel for Weighted Diverse Bases. © 2023, The Author(s).

Fulltext

Mathematical Programming

Diverse collections in matroids and graphs

The entanglement swap primitive facilitates the establishment of shared entanglement between non-adjacent nodes in a quantum network. This shared entanglement can subsequently be used for executing quantum communication protocols. The fundamental problem in quantum networks is to determine a path for entanglement swapping in response to demands for entanglement sharing between pairs of nodes. We investigate variants of this problem in this work. We propose a framework of Greedy algorithms that can be tweaked towards optimizing on various objective functions. In conjunction with a novel Spatial and Temporal (split across multiple paths) splitting approach to entanglement routing, we use this framework, which we call GST, to investigate the scenario when the demands are specified in terms of a starting time and a deadline. Considering the fragile nature of quantum memory, "bursty"demands are natural, and therefore the setting is important. We study the algorithm for maximizing the number of satisfied demands and the number of entangled pairs shared. We report empirical results on the performance against these objective functions, and compare with a naive algorithm that involves neither temporal and spatial splitting of the demands, nor the greedy approach to scheduling the demands. © 2023 ACM.

Greedy Algorithms for Finding Entanglement Swap Paths in Quantum Networks

Cell-free massive multiple-input-multiple-output (CF-mMIMO) systems provide spectral efficiency (SE) gains with a more uniform quality-of-service in the network area compared to cellular massive MIMO schemes but at the expense of higher capacity requirements on the fronthaul links. To reduce the signaling overhead on fronthaul links, we propose a selective user forwarding method for uplink data transmissions in CF-mMIMO systems, where each access point (AP) forwards the data of only a selected subset of users to the central processing unit (CPU) for joint processing. The simulation results show that the selective user forwarding scheme achieves nearly the same performance as a CF-mMIMO system with selected number of users, M, being equal to less than one-fourth of the total number of users in the network and resulting in a fronthaul signaling savings of about 75%. We then analytically study the performance of the proposed system in the presence of channel aging by deriving expressions for SE. The numerical evaluation of these expressions is shown to be close to the simulation results. © 2013 IEEE.

IEEE Access

Analysis of Selective User Forwarding in Cell-Free Massive MIMO with Channel Aging

3GPP Rel. 16 introduced 5G New Radio (NR) Vehicle to Everything (V2X) to support advanced use cases in Intelligent Transport Systems (ITS) with stringent Quality of Service (QoS) requirements, which include vehicular safety and traffic management applications. However, in highly congested traffic scenarios (i.e., too many vehicles in a single collision domain than the number of available channel resources), emergency vehicles performing sensing-based Semi-Persistent Scheduling (SPS) suffer from low Packet Reception Rate (PRR) and high Packet Inter-Reception time (PIR) due to scarcity of channel resources and increased collision rates. To address these issues, we propose a Priority-Based Semi-Persistent Scheduling (P-SPS) scheme which helps emergency vehicles by classifying them as high priority (HP) vehicles with higher Reselection Counter (RC) values and letting them to transmit in one of the channel resources whenever they have CAM messages ready for transmission irrespective of whether such resources are available or not. We also propose a complementary Probabilistic Collision Mitigation (PCM) scheme and an Intelligent Grant Removal (IGR) scheme to minimize the chances of collision among HP and low priority (LP) vehicles in the network. We implement the proposed enhancements to SPS in NR V2X module of the system level Network Simulator 3 (NS-3) and demonstrate how these help in improving the performance of HP and LP vehicles as compared to legacy SPS of 5G NR V2X in highly congested scenarios. © 2023 ACM.

On Enhancing Semi-Persistent Scheduling in 5G NR V2X to Support Emergency Communication Services in Highly Congested Scenarios

The unpaired domain-to-domain translation aims to learn inter-domain relationships between diverse modalities without relying on paired data, which can help complex structure prediction tasks such as age transformation where it is challenging to attain paired samples. A common approach used by most current methods is to factorize the data into a domain-invariant content space and a domain-specific style space. In this work, we argue that the style space can be further decomposed into smaller subspaces. Learning these style subspaces has two-fold advantages: (i) it allows more robustness and reliability in the generation of images in unpaired domain translation; and (ii) it allows better control and thereby interpolation of the latent space, which can be helpful in complex translation tasks involving multiple domains. To achieve this decomposition, we propose a novel scalable approach to partition the latent space into style subspaces. We also propose a new evaluation metric that quantifies the controllable generation capability of domain translation methods. We compare our proposed method with several strong baselines on standard domain translation tasks such as gender translation (male-to-female and female-to-male), age transformation, reference-guided image synthesis, multi-domain image translation and multi-attribute domain translation on celebA-HQ and AFHQ datasets. The proposed technique achieves state-of-the-art performance on various domain translation tasks while outperforming all the baselines on controllable generation tasks. Code - https://github.com/GauravBh1010tt/Controllable-Domain-Translation © 2023 IEEE.