Talks
Cyber Threat Management
Abstract: Cyber threats have evolved from isolated security incidents into sophisticated, rapidly changing risks capable of causing significant organizational and societal impact. Traditional approaches based primarily on security controls, compliance and periodic audits are increasingly inadequate against this dynamic threat landscape. In this talk, Rajeev Shukla will discuss the changing cyber-threat ecosystem and the need for real-time, intelligence-driven and proactive approaches to cyber threat management. The talk will explore threat intelligence, threat monitoring, rapid detection and response, automation, and emerging approaches to countering evolving cyber threats. It will also examine how AI and advanced security technologies can contribute to building more adaptive and resilient cybersecurity defences. Bio: Rajeev Shukla is a seasoned technology professional, entrepreneur, and cybersecurity thought leader, and the Founder and CEO of Castellum Labs. He has held senior leadership positions at organizations including Sun Microsystems, CA Technologies, Cygilant, Quark, Tally, and Infosys, where he has led technology, product, and business initiatives. His expertise spans cybersecurity, threat management, threat monitoring, SIEM, identity and access management, networking, data centres, and cloud technologies. Through Castellum Labs, he focuses on advanced cybersecurity and technology solutions, including AppSecOps, automated security response, dark-web and threat intelligence, AI-driven security, and cloud security.
Towards Secure-by-Construction Compilers for Practical Systems
Abstract: This talk presents two different projects that demonstrate the construction of practical but formally correct secure compilers in two security-critical domains: Correctness via Type Checking for Fully Homomorphic Encryption (FHE). FHE schemes add some small noise to the message during encryption. The noise accumulates with each homomorphic operation. When the noise exceeds a critical value, the FHE circuit produces an incorrect output. This makes developing FHE applications quite tedious and error-prone, as existing libraries and compilers offer limited support for statically tracking the noise. Additionally, FHE circuits are also plagued by wraparound errors that are common in finite modulus arithmetic. Unfortunately, none of the existing compilers and libraries guarantee correct FHE evaluation. In this work, she presents a correctness-oriented IR, ILA, for type-checking circuits intended for homomorphic evaluation. Her IR is backed by a type system that tracks low-level quantitative bounds (e.g., ciphertext noise) without using the secret key. Using her type system, she identifies and proves a strong functional correctness criterion for ILA circuits. Towards the end, she also shows its applications for the CKKS scheme, specifically for encrypted inference. Flexible, Fine-grained, and Secure-by-Construction Enclave Partitioning for LLVM Applications: While Trusted Execution Environments (TEEs) provide hardware isolation, they do not by themselves enforce information-flow security, and manually partitioning applications into enclave and non-enclave components is difficult and error-prone. She addresses these challenges by developing an LLVM-based type system that combines information-flow control with security-aware memory safety, extending it to reason about enclave-aware attackers, and providing a type-preserving compilation that automatically partitions applications while preserving security. Bio: Dr. Anitha Gollamudi is currently an assistant professor at Richard A. Miner School of Computer & Information Sciences, UMass, Lowell. Her research enforces security in software applications against powerful cyber attackers. Specifically, she leverages trusted execution environments, a hardware-based technology, to provide formal guarantees in security-critical applications. Her work enables a step closer toward secure collaboration of mutually distrusting parties by still maintaining their compliance to privacy governing laws such as HIPAA and FERPA. Her work is supported by NSF and ONR. She did her postdoc at Yale University and holds a Ph.D. in Computer Science from Harvard University. She was a NSF Computing Innovation Fellow and a 2021 Siebel Scholar. Prior to joining graduate school, Gollamudi was a compiler engineer at Atmel (now Microchip) and Advanced Micro Devices. She was one of the early engineers to develop an AVR-GCC compiler toolchain. Gollamudi holds a bachelor’s degree in computer science engineering from Andhra University, India.
Deterministic list decoding of Reed-Solomon codes
Abstract: Reed-Solomon codes are obtained by evaluating all univariate polynomials of degree less than $k$ over a finite field $F$ on a fixed set of $n (> k$) distinct inputs. These codes are widely studied and used in theory and in practice, and are known to be optimal in certain settings of parameters. Given the central importance of these codes, the question of designing efficient decoding algorithms for these codes has been a problem of great interest for decades. The state of the art for this problem is given by results of Sudan and Guruswami-Sudan from the 1990s, which show that these codes can be decoded from $(n - \sqrt{nk})$ errors, either via a randomized algorithm in time $\text{poly}(n, \log |F|)$ or via a deterministic algorithm in time $\text{poly}(n, |F|)$. Bio: Soham Chatterjee is a second-year Integrated MSc-PhD student at the Tata Institute of Fundamental Research (TIFR), where he is advised by Prof. Mrinal Kumar. His research interests primarily lie in Computational Algebra, Error-Correcting Codes, Pseudorandomness, Complexity Theory, and Algorithms. He completed his Bachelor’s degree in Mathematics and Computer Science at the Chennai Mathematical Institute.
Mempool Privacy in Blockchain Systems: Threshold Encryption, Batched Decryption, and Traitor Tracing
Abstract: Blockchain-based financial systems increasingly face the challenge of protecting pending transactions from manipulation while preserving transparency and decentralization. Encrypted mempools have emerged as a promising solution by hiding transaction contents until they are finalized on-chain. However, achieving privacy at scale requires efficient decryption mechanisms, and ensuring accountability remains a significant challenge when participants misuse their decryption privileges. In this talk, I will discuss recent advances in threshold encryption and batched decryption techniques for scalable blockchain systems. I will then present our recent work on incorporating traitor tracing mechanisms that enable the identification of malicious insiders who collude to violate transaction privacy. The talk will highlight how cryptographic tools can simultaneously provide scalability, privacy, and accountability for next-generation decentralized financial infrastructures. Bio: Anirban Chakrabarti is a Project Scientist (post-doctoral) at the Department of Computer Science and Automation, Indian Institute of Science (IISc), Bangalore. He was previously a post-doctoral researcher at Microsoft Research, and a PhD scholar in the same department at IISc. His broad research areas are applied cryptography, information theory and coding theory. His research has been published in top-tier CS conferences (CCS, ASIA CCS).
Public Key Encryption from the MinRank Problem
Abstract: He will discuss our new public-key encryption scheme from the hardness of the (planted) MinRank problem over uniformly random instances. This corresponds to the hardness of decoding random linear rank-metric codes. Existing constructions of public-key encryption from such problems require hardness for structured instances arising from the masking of efficiently decodable codes. Central to our construction is the development of a new notion of duality for rank-metric codes. Bio: Rohit is a postdoctoral research fellow at the School of Computing in NUS. He looks at the foundations of cryptographic primitives and the interplay between them. He also works on post-quantum and some aspects of quantum cryptography. He is broadly interested in the intersection of theory CS and cryptography.
Collaborative zkSNARKs: Scalability and Malicious Security
Abstract: Collaborative zk-SNARKs, introduced by Ozdemir and Boneh (USENIX’22), are a multi-prover extension of zk-SNARKs in which multiple mutually distrustful provers, each holding a private input, jointly generate a zk-SNARK that attests to the correctness of a computation over their collective secrets. A sequence of recent works has proposed efficient constructions of collaborative zk-SNARKs following a common template: designing secure multiparty computation (MPC) protocols that emulate the behavior of a zk-SNARK prover, while avoiding non-black-box use of cryptographic primitives. In this talk, I will survey this framework and highlight some specific results addressing scalability and malicious security (based on recent works at USENIX’23 and CRYPTO’25). Bio: Sruthi Sekar is currently an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay. Her research interests span both theoretical and applied cryptography, as well as theoretical computer science more broadly. Prior to this, she was a postdoctoral researcher at the University of California, Berkeley. She earned her Master’s and PhD degrees from the Indian Institute of Science, Bangalore. Her PhD thesis received an Honorable Mention at the ACM India Doctoral Dissertation Award 2022. She was also awarded the TCS PhD Fellowship and received the Prof. P. L. Bhatnagar Medal (Gold Medal for her Master’s degree) from IISc.
Securing the Frontier: Navigating Threats and Governance in the Age of Generative and Agentic AI
Abstract: As artificial intelligence transitions from content-generating Generative AI (GenAI) to autonomous, multi-step Agentic AI, the landscape of enterprise opportunities—ranging from operations automation to fraud detection—is expanding rapidly. However, this evolution introduces significant “double-edged sword” risks, where AI serves as both a powerful tool for defenders and a sophisticated weapon for attackers. This talk explores the critical security challenges inherent in AI-based systems, including model hallucinations, prompt injection, data poisoning, and the emergence of malicious generative frameworks such as MalGEN. The session will also discuss the global regulatory landscape, highlighting key frameworks such as India’s RBI ethical principles, the EU AI Act, and NIST’s AI Risk Management Framework. Attendees will gain insights into a Secure AI Development Lifecycle, emphasizing human-in-the-loop (HITL) oversight, continuous red-teaming, and robust explainability standards. By balancing innovation with rigorous technical safeguards and risk-based governance, organizations can enable the safe adoption of GenAI while ensuring systemic trustworthiness. Bio: Prof. Sandeep Kumar Shukla is currently the Director of IIIT Hyderabad. Before joining IIIT Hyderabad in August 2025, he served as the Rajiv and Ritu Batra Chair Professor of Cybersecurity at IIT Kanpur. He has been with IIT Kanpur since 2015, and prior to that he was a faculty member at Virginia Tech (2002–2015). Earlier in his career, he worked at GTE Labs, Intel Corporation, and the University of California at Irvine. He is an IEEE Fellow and a past Editor-in-Chief of ACM Transactions on Embedded Computer Systems. His primary research interests include cybersecurity of critical infrastructure, blockchain technology, and cybersecurity governance, risk, and compliance.
On Split-State Quantum Tamper Detection
Abstract: Tamper-detection codes (TDCs) are fundamental objects at the intersection of cryptography and coding theory. A TDC encodes messages in such a manner that tampering with the codeword causes the decoder to either output the original message or reject it. In this work, we study quantum analogs of one of the most well-studied adversarial tampering models: the so-called t-split-state tampering model, where the codeword is divided into t shares and each share is tampered with locally. It is impossible to achieve tamper detection in the split-state model using classical codewords. Nevertheless, we demonstrate that the situation changes significantly if the message can be encoded into a multipartite quantum state entangled across the t shares. Concretely, we define a family of quantum TDCs on any t ≥ 3 shares, which can detect arbitrary split-state tampering so long as the adversaries are unentangled, or even limited to a finite amount of pre-shared entanglement. Previously, this was only known in the limit of asymptotically large t. As our flagship application, we show how to augment threshold secret sharing schemes with similar tamper-detecting guarantees. We complement our results by establishing connections between quantum TDCs and quantum encryption schemes. Bio: Naresh Goud Boddu is Vice President and Applied Research Lead at J.P. Morgan Singapore. He completed his Ph.D. in September 2022 under Prof. Rahul Jain at the Centre for Quantum Technologies, National University of Singapore. Following his Ph.D., he was a Postdoctoral Researcher at NTT Research, where he worked with Prof. Vipul Goyal and Prof. Dakshita Khurana until November 2024. At J.P. Morgan, he has worked on lattice-based zero-knowledge proofs applications for financial institutions. His research interests lie at the intersection of post-quantum cryptography, quantum cryptography, and quantum information.
Next-generation Encryption Systems with Advanced Computational Power
Abstract: The classical paradigm of public-key encryption ensures confidentiality, but it either reveals the complete raw data or nothing—a limitation in scenarios where controlled computation over encrypted data is needed. In this talk, I will argue why traditional encryption is often insufficient for modern privacy-sensitive applications, especially in cloud-based data analytics. I will then introduce the notion of Functional Encryption (FE) including a brief survey about its state-of-the-art, with emphasis on specific instantiations such as inner-product FE, attribute-based inner-product FE, and attribute-weighted-sum FE. I will demonstrate how these schemes enable secure, privacy-preserving data analytics—for example, computing aggregate statistics over encrypted health records without revealing individual data. While classical FE enables controlled access to encrypted information, its traditional architecture relies on a single trusted authority which creates inherent limitations—including key-escrow, central trust bottlenecks, and vulnerability to master-key exfiltration attacks. To address these challenges, I will introduce Registered FE (RFE): a novel paradigm that decentralizes trust and allows users to register their own public keys and authorized functions, removing the need for a central trusted authority. I will present a generic framework from our recent work (IACR ePrint 2024/36006) that transforms classical FE primitives into RFE schemes, while preserving security and efficiency. Overall, this talk aims to highlight how modern encryption systems—based on FE and its registered extension—provide advanced computational power over encrypted data, opening the door to deployable, privacy-preserving intelligent systems that meet the needs of data-driven applications for securing our digital society.
Combining Partial Sums and FFT for the Fastest Known Attack on 6-Round AES
Abstract: The partial-sums technique introduced by Ferguson et al. (2000) achieved a 6-round AES attack with time complexity 2^{52} S-box evaluations, a benchmark that has stood since 2000. In 2014, Todo and Aoki proposed a comparable approach based on the Fast Fourier Transform (FFT). In this talk, I will show how to combine partial sums with FFT to get “the best of both worlds”. The resulting attack on 6-round AES has a complexity of about 2^{46.4} additions, and I will outline how to implement it efficiently. A proof-of-concept implementation achieves a speedup of more than 32x over the previous best result, setting a new practical record for 6-round AES after nearly 25 years.
Multiparty Computation with a Friend
Abstract: Secure multiparty computation (MPC) enables collaborative computation over sensitive data but remains expensive and difficult to deploy in the dishonest-majority and asynchronous settings. Traditional dishonest-majority MPC suffers from high overheads and weak security guarantees such as lack of fairness, while asynchronous MPC (AMPC) protocols incur significant costs and require a two-thirds honest majority to ensure correctness and liveness. We explore the MPC with a friend (helper-aided) model, which introduces a semi-honest, non-colluding helper party (HP)—a realistic assumption in many real-world applications such as financial dark pools. Leveraging this model, we design Asterisk, a practically efficient MPC framework that achieves fairness even with a malicious majority, invokes the HP only a constant number of times, and scales to hundreds of parties. Asterisk outperforms all existing dishonest-majority MPC protocols and is competitive with honest-majority systems, achieving 228–288× faster preprocessing and evaluating circuits with 10⁶ multiplications among 100 parties in ~20 seconds. We also implement fast and scalable dark pool applications using Asterisk. Additionally, we develop new asynchronous helper-aided MPC protocols (Pollux and Castor) under the preprocessing–online paradigm. Our construction, Pollux, uses only lightweight cryptography in the honest-majority setting and shows that oblivious transfer during preprocessing is necessary in the dishonest-majority case. Our experiments demonstrate substantial performance and robustness improvements over prior helper-aided MPC and AMPC schemes, particularly under network delays. Bio: Protik Kumar Paul is a postdoctoral researcher at TU Darmstadt, Germany, specializing in cryptography and privacy-preserving technologies. He completed his PhD from IISc Bangalore. His research is focused on Secure Multiparty Computation (MPC), Zero-Knowledge (ZK) proofs, and privacy-preserving frameworks for real-world applications. Protik has contributed to advancing both theory and practice, including designing efficient MPC protocols in challenging adversarial settings and developing privacy-preserving solutions for financial systems, secure machine learning, and digital services. He has published in leading venues such as IEEE S&P, PoPETS and Asiacrypt, and his work focuses on bridging foundational cryptographic research with practical, scalable applications.
Implicant Based Boolean system solver
Abstract: Boolean systems arise in many computationally intensive problems such as Cryptanalysis, Biological networks, SAT problems, Decoding problems, Constraint satisfaction and Verification. The talk is aimed at discussing an algorithm for returning all solutions of Boolean systems of equations or satisfying assignments of Boolean formulas. The algorithm makes use of orthogonal implicants of Boolean functions and shows that an effectively parallelizable algorithm can be constructed to compactly return all solutions of Boolean systems in terms of orthogonal implicants. Such an algorithm can provide a scalable approach for sparse formulas which occur in most practical problems and may provide practically feasible solutions. Bio: Prof. Virendra Sule retired as a Professor from the Department of Electrical Engineering at IIT Bombay in 2023. He has been active in the field of Cryptography and Computations in finite fields and number theory for over 20 years. He has over 600 citations to his papers and has guided several PhD and MTech students. He completed PhD from IIT Bombay in 1990 and since then worked on the faculty of IIT Kanpur, IIT Bombay and CR Rao Institute as well as worked with several Govt. agencies and the private entity Computational Research Laboratories, Pune, a venture of Tata Sons. He has also worked as a Research Fellow at University of Southampton UK. His research interests are in Cryptography, Cryptanalysis and Computational methods involving finite fields and Boolean equations.
FHE advances and HW acceleration opportunities
Abstract: Data privacy concerns are increasing significantly in the context of cloud computing, Internet of things and explosion of AI based applications FHE (Fully Homomorphic Encryption) has experienced significant breakthroughs and widespread adoption in recent years. Despite the rapid adoption and significant push from big players like Microsoft, Google, IBM with FHE libraries, some of the major hurdles are with computing overhead and storage cost. This talk will focus on opportunities for HW acceleration of some of the FHE primitives Bio: Venugopal Ramamurthy is a second year PhD student in the area of Computer Architecture under the guidance of Dr.Rajesh Kedia. Before starting my PhD program, he had over 25+ years of Industry experience working for Qualcomm, designing and developing wireless protocol software for 4G and 5G modem chipsets.
Local Inversion Problem and Black Box Cryptanalysis II
Abstract: In this talk, the speaker explained the concept of Linear Recurrence Relations and results on existence of minimal polynomials of sequences over finite fields, showing how they can be used to compute the local inverses of maps and sequences. The inverse computation utilises only the black box map operation and solving a Hankel linear system of equations over the field. The maximal rank of the Hankel system is the Linear Complexity of the sequence. Illustrations were shown for applications to stream cipher cryptanalysis, RSA inversion, RSA private key computation, the Quadratic Residue problem, and the Discrete Log problem over finite fields. The talk concluded with a list of further problems and applications of the approach. Bio: Prof. Virendra Sule retired as a Professor from the Department of Electrical Engineering at IIT Bombay in 2023. He has been active in the field of Cryptography and Computations in finite fields and number theory for over 20 years. He has over 600 citations to his papers and has guided several PhD and MTech students. He completed PhD from IIT Bombay in 1990 and since then worked on the faculty of IIT Kanpur, IIT Bombay and CR Rao Institute as well as worked with several Govt. agencies and the private entity Computational Research Laboratories, Pune, a venture of Tata Sons. He has also worked as a Research Fellow at University of Southampton UK. His research interests are in Cryptography, Cryptanalysis and Computational methods involving finite fields and Boolean equations.
Local Inversion Problem and Black Box Cryptanalysis I
This talk presented a new approach to solve problems of cryptanalysis of symmetric as well as public key algorithms, based on the solution of the problem of inversion of maps in cartesian products over finite fields (specialised to binary fields) and inversion of sequences. The approach utilises only the black box operation of the map — it does not depend on the algebraic or Boolean model, and is not a brute force search or its variation. This leads to a uniform methodology for diverse cryptanalysis problems. Bio: Prof. Virendra Sule retired as a Professor from the Department of Electrical Engineering at IIT Bombay in 2023. He has been active in Cryptography and Computations in finite fields and number theory for over 20 years, with over 600 citations to his papers. He completed his PhD from IIT Bombay in 1990.
Security and Privacy Challenges with GenAI Chatbots
Abstract: AI/ML for automation across industry sectors is having a positive impact on productivity. GenAI assistants such as ChatGPT, Gemini, and Perplexity Pro edition — being freely available — will have millions of users in a short span. This wide usage of AI/ML at the individual level has exposed various security and privacy challenges.The talk covered recent challenges related to data leakage, privacy compromises, vulnerabilities, and hallucination. Good practices to mitigate the risks associated with these assistants were also discussed. Bio: Dr. Lalit Mohan Sanagavrapu is Chief Product Officer at Quick Heal, responsible for envisioning the cyber security requirements of individuals and enterprises. He holds a PhD from IIIT-Hyderabad and has worked at IDRBT, Wells Fargo, and Infosys.
Advanced Persistent Threats (APT): Threat Hunting & Attribution Techniques
Abstract: Advanced Persistent Threats (APTs) are groups of cyber threat actors — usually affiliated with nation states — who possess extraordinary capabilities, resources, and access to dark market zero-day exploits. Such actors not only use advanced techniques to establish a foothold in a target organisation's infrastructure, but remain persistent, evading detection tools and maintaining communication with command-and-control (C2C) servers. The talk provided glimpses of initial research work at Prof. Shukla's group towards tracking, analysing, and attributing APT groups using India-local sensors, measurements, and AI/ML-based techniques — building a capability independent of US-centric threat intelligence. Bio: Prof. Sandeep Kumar Shukla is currently Director of IIIT Hyderabad. Before joining in August 2025, he was the Rajiv and Ritu Batra Chair Professor in Cyber Security at IIT Kanpur. He is an IEEE Fellow.
Correlations in Secure Computation
Abstract: A central concept in secure computation is that of correlated random variables (or correlations). This talk covered correlations, connections to cryptography, useful algebraic structures, and applications. Specifically, the speaker described a new class of correlations over groups called "Zero Alternating Sum" and showed how it allows secure 2-party computation over groups. Bio: Dr. Rajeev Raghunath completed his PhD under Professor Manoj Prabhakaran at IIT Bombay, and is currently a postdoc at IIT Madras. He works in MPC, cryptography, and complexity.
High-Level Approaches to Hardware and Embedded Security
Abstract: As designers increasingly rely on third-party intellectual property (IP) cores and outsourcing in the integrated circuit (IC) design and manufacturing process, security vulnerabilities have risen. The talk presented High-Level Design for Trust techniques developed by the speaker's team to address these threats: locking of designs and secure sourcing of IPs for high-level integration. Implementing built-in locking mechanisms aims to prevent reverse engineering. Secure Sourcing thwarts Trojan insertion in third-party IPs. The talk wrapped up by emphasising the importance of hardware security from economic, security, and safety standpoints. Bio: Ramesh Karri is a Professor of Electrical and Computer Engineering at New York University. He co-directs the NYU Center for Cyber Security (http://cyber.nyu.edu). He co-founded the Trust-Hub (http://trust-hub.org) and founded/organizes the Embedded Systems Challenge (https://csaw.engineering.nyu.edu/esc), the annual red team blue team event. Ramesh Karri holds a Ph.D. in Computer Science and Engineering from the University of California at San Diego, and a B.E in ECE from Andhra University. With a focus on hardware cybersecurity, his research and educational endeavors encompass trustworthy ICs, processors, and cyber-physical systems; security-aware computer-aided design, test, verification, validation, and reliability; nano meets security; hardware security competitions, benchmarks, and metrics; biochip security; and additive manufacturing security. Ramesh has published over 300 articles in prestigious journals and conferences.
Applying Machine Learning to Securing Cellular Networks
Abstract: Cellular network security is more critical than ever, given the increased complexity of these networks and the numbers of applications that depend on them, including telehealth, remote education, ubiquitous robotics and autonomous vehicles, smart cities, and Industry 4.0. In order to devise more effective defenses, a recent trend is to leverage machine learning (ML) techniques, which have become applicable because of today advanced capabilities for collecting data as well high-performance computing systems for training of ML models. Recent large language models (LLMs) are also opening new interesting directions for security applications. In this talk, I will first present a comprehensive threat analysis in the context of 5G cellular networks to give a concrete example of the magnitude of the problem of cellular network security. Then, I will present two specific applications of ML techniques for the security of cellular networks. The first application focuses on the use of natural language processing techniques to the problem of detecting inconsistencies in the “natural language specifications” of cellular network protocols. The second application addresses the design of an anomaly detection system able to detect the presence of malicious base stations and determine the type of attack. Then I’ll conclude with a discussion on research directions. Bio: Elisa Bertino is a Samuel Conte Distinguished Professor of Computer Science at Purdue University. She serves as Director of the Purdue Cyberspace Security Lab (Cyber2Slab). Prior to joining Purdue, she was a professor and department head at the Department of Computer Science and Communication of the University of Milan. She has been a visiting researcher at the IBM Research Laboratory in San Jose (now Almaden), at Rutgers University, at Telcordia Technologies. She has also held visiting professor positions at the Singapore National University and the Singapore Management University. Her recent research focuses on security and privacy of cellular networks and IoT systems, and on edge analytics for cybersecurity. Elisa Bertino is a Fellow member of IEEE, ACM, and AAAS. She received the 2002 IEEE Computer Society Technical Achievement Award for “For outstanding contributions to database systems and database security and advanced data management systems”, the 2005 IEEE Computer Society Tsutomu Kanai Award for “Pioneering and innovative research contributions to secure distributed systems”, the 2019-2020 ACM Athena Lecturer Award, and the 2021 IEEE 2021 Innovation in Societal Infrastructure Award. She received an Honorary Doctorate from Aalborg University in 2021 and an Honorary Research Doctorate in Computer Science from the University of Salerno in 2023. She is currently serving as ACM Vice-president.
A Look at Electronic Voting Systems
Abstract: Any secure voting system should demonstrate at least four properties. P1: The voter should remain anonymous. That is to say that it is hard to tie the voter to the vote she cast. P2: A voter should not be able to cast a vote more than once. P3: A voter should be able to convince herself that her vote has been counted as cast. P4: When challenged by an honest or dishonest voter, the Election Authority (EA) should be able to prove to the voter that her voter has indeed been counted as cast. Interestingly, these four properties do not talk to each other. Which means that making one property stronger makes the other property weaker, at least, intuitively. For example, the cover of anonymity could be used by a voter to cast a vote multiple times under the apparent impression that her misdeeds could not be detected. Similarly, the cover of anonymity allows a dishonest voter to sabotage the voting system with the false claim that her vote has not been counted. The problem is even more challenging when none of the voters, as well the Election Authority (EA), are trusted. We discuss these challenges in detail, and make an attempt to give a solution. Our solution critically uses sophisticated cryptographic algorithms such as Linkable Ring Signature (LRS), and of course Blockchain. Even then we encounter hurdles which are difficult to overcome. We conclude with certain open questions. Bio: Dr. Souradyuti Paul is currently the Department Head and an associate professor in the department of CSE of IIT Bhilai. Earlier, he worked as an assistant professor of CSE at IIT Gandhinagar (Jul. 2014 - Oct. 17). He obtained BE, MTech and PhD degrees, respectively, from Jadavpur University (1994 - 98), Indian Statistical Institute (1999 - 01) and KU Leuven (2001 - 06). He spent a long span of time (about 14 years) working as a doctoral, postdoctoral and a guest researcher at various prestigious data security research groups in Europe, USA, and Canada: in KU Leuven (2001 - 08), at NIST/USA (2008 - 12) and in the Univ. of Waterloo (2012 - 14). In addition to carrying out academic research in computer security, he was, in the past, directly involved with (and a major technical contributor to) two cryptographic standardization projects of global impact: ECRYPT-eSTREAM (organized by the European Union, 2005-2008) and SHA-3 (organized by NIST, Govt. of USA, 2007-2012). He led multiple Indian initiatives (undertaken by the Bureau of Indian Standards) in standardizing Blockchain-based applications under various ISO projects. Among others, currently, he is the Chief Coordinator of a Dantewada District Development Design project funded by the Dantewada District Administration, a Coordinator of the Vidya Samiksha Kendra (VSK) project funded by the Govt. of Chhattisgarh, and a Principal Investigator of the GI-tag-based trading platform funded by IBITF.
Evaluation of WiFi Security Standards
Abstract: This talk explores the evolution of Wi-Fi security protocols from WEP to WPA3. Key concepts such as encryption, integrity protection, and authentication will be discussed with practical insights from packet traces. The session will also highlight WPA3 enhancements, including SAE, WPA3-Enterprise, and OWE, offering a comprehensive understanding of modern Wi-Fi security standards for both home and enterprise networks. Bio: Srikanth obtained his B.E degree from College of Engineering, Anna University, Chennai, and M. A.Sc, and Ph. D. degrees from University of Victoria, British Columbia, Canada. He is currently the Chief Knowledge Officer for Nanocell Networks Pvt. Ltd. Srikanth began his career as a research associate at the University of Victoria, British Columbia, Canada working in the area of DSL and CDMA Systems. After his Ph. D., he joined Harris Corporation and worked on baseband algorithms for various wireless standards including IS-136 and 1S-95 systems. He then joined the KBC Research Foundation/AU-KBC Research Centre and has focused on OFDM systems for powerline and wireless applications. From 2004-2007 he was awarded a Young Scientist Fellowship by the Government of India to work on technologies related to upgrades on 802.11 and 802.16 standards. He has been following 802.11 and cellular standards and delivers several courses to corporate clients in this area. He consults on various areas and has also been involved in the setting up of a testlab for 802.11. He is also involved with the organization of Wi-Fi and wireless knowledge summits to help develop a community for exchange of technical information in these areas.
Strongly Secure Universal Thresholdizer from Lattices
Abstract: Threshold cryptography distributes a privileged operation, like signing in a signature scheme or decryption in a public key encryption scheme among multiple parties so that there is no single point of security failure. For example, in a t-out-of-n threshold signature scheme, each party is given a secret partial signing key using which it can generate a partial signature on any message m and then any t partial signatures can be combined to generate a valid signature on m. In 2018, Boneh et al. constructed the first lattice-based, non-interactive universal thresholdizer (UT) and used it to thresholdize any signature scheme (along with few other applications). They consider selective security where the adversary declares at most upto t-1 corrupt parties in the beginning of the game and is given their corresponding (partial) signing keys. However, during the rest of the game, the adversary is not allowed to get a partial signature from any honest party on the target message m, even if it corrupts less than t-1 parties in the beginning. In this talk, I will present a construction of threshold signature that improves upon Boneh et al’s construction to provide stronger security where the adversary is also allowed to query partial signature on m as long as it does not trivially let the adversary compute the final signature on m*. In the process, we also identified the desired stronger security property of the UT such that all the other thresholdized cryptographic primitives achieve stronger security in the similar sense. This is a joint work with Ehsan Ebrahimi from the University of Luxembourg which got accepted for publication at Asiacrypt, 2024. Towards the end of the talk, I will also briefly discuss my overall research interests and the areas/results that I have worked on. Bio: Anshu Yadav is currently a postdoctoral researcher at IST Austria in Prof. Krzysztof Pietrzak’s group. She received her PhD from IIT Madras, guided by Prof. Shweta Agrawal. Her research interests are in the area of theoretical cryptography in building various cryptographic primitives largely from post-quantum lattice-based cryptographic assumptions and some from classical assumptions as well. She has worked on problems related to threshold and blind signatures, and multi-input attribute-based and functional encryption systems.