Related papers: FIRST: FrontrunnIng Resilient Smart ConTracts
This paper address a new problem in RFID authentication research for the first time. That is, existing RFID authentication schemes generally assume that the backend server is absolutely secure, however, this assumption is rarely tenable in…
Financial markets are undergoing an unprecedented transformation. Technological advances have brought major improvements to the operations of financial services. While these advances promote improved accessibility and convenience,…
Fintech provides technological services to increase operational efficiency in financial institutions, but traditional perimeter-based defense mechanisms are insufficient against evolving cyber threats like insider attacks, malware…
Blockchain technology has become almost as famous for incidents involving security breaches as for its innovative potential. We shed light on the prevalence and nature of these incidents through a database structured using the STIX format.…
In this paper we present ODIN, a front-running protection system that uses a novel algorithm to measure Round-Trip-Time (RTT) to untrusted servers. ODIN is the decentralized equivalent of THOR, a RTT-aware front-running protection system…
The management of identities on the Internet has evolved from the traditional approach (where each service provider stores and manages identities) to a federated identity management system (where the identity management is delegated to a…
The foundation models (FMs) have been used to generate synthetic public datasets for the heterogeneous federated learning (HFL) problem where each client uses a unique model architecture. However, the vulnerabilities of integrating FMs,…
The recent surge of blockchain systems has renewed the interest in traditional Byzantine fault-tolerant consensus protocols. Many such consensus protocols have a primary-backup design in which an assigned replica, the primary, is…
Forward Secrecy (FS) is a security property in key-exchange algorithms which guarantees that a compromise in the secrecy of a long-term private-key does not compromise the secrecy of past session keys. With a growing awareness of long-term…
Decentralized finance (DeFi) protocols are crypto projects developed on the blockchain to manage digital assets. Attacks on DeFi have been frequent and have resulted in losses exceeding $80 billion. Current tools detect and locate possible…
Federated Learning (FL) has emerged as a key paradigm for building Trustworthy AI systems by enabling privacy-preserving, decentralized model training. However, FL is highly susceptible to adversarial attacks that compromise model integrity…
Blockchains are maintained by a network of participants that run algorithms designed to maintain collectively a distributed machine tolerant to Byzantine attacks. From the point of view of users, blockchains provide the illusion of…
Recent years have witnessed a rapid development of platform economy, as it effectively addresses the trust dilemma between untrusted online buyers and merchants. However, malicious platforms can misuse users' funds and information, causing…
Some of the most significant high-level properties of currencies are the sums of certain account balances. Properties of such sums can ensure the integrity of currencies and transactions. For example, the sum of balances should not be…
Recently, we saw the emergence of consensus-based database systems that promise resilience against failures, strong data provenance, and federated data management. Typically, these fully-replicated systems are operated on top of a…
In this paper, we continue the line of work initiated by Boneh and Zhandry at CRYPTO 2013 and EUROCRYPT 2013 in which they formally define the notion of unforgeability against quantum adversaries specifically, for classical message…
Bitcoin, the first peer-to-peer electronic cash system, opened the door to permissionless, private, and trustless transactions. Attempts to repurpose Bitcoin's underlying blockchain technology have run up against fundamental limitations to…
Deep reinforcement learning (DRL) has been envisioned to have a competitive edge in quantitative finance. However, there is a steep development curve for quantitative traders to obtain an agent that automatically positions to win in the…
In the realm of Artificial Intelligence (AI), the need for privacy and security in data processing has become paramount. As AI applications continue to expand, the collection and handling of sensitive data raise concerns about individual…
Federated learning is a prominent framework that enables clients (e.g., mobile devices or organizations) to train a collaboratively global model under a central server's orchestration while keeping local training datasets' privacy. However,…