Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning

Federated learning (FL) enables multiple participants to train a global machine learning model without sharing their private training data. Peer-to-peer (P2P) FL advances existing centralized FL paradigms by eliminating the server that aggregates local models from participants and then updates the global model. However, P2P FL is vulnerable to (i) honest-but-curious participants whose objective is to infer private training data of other participants, and (ii) Byzantine participants who can transmit arbitrarily manipulated local models to corrupt the learning process. P2P FL schemes that simultaneously guarantee Byzantine resilience and preserve privacy have been less studied. In this paper, we develop Brave, a protocol that ensures Byzantine Resilience And privacy-preserving property for P2P FL in the presence of both types of adversaries. We show that Brave preserves privacy by establishing that any honest-but-curious adversary cannot infer other participants' private data by observing their models. We further prove that Brave is Byzantine-resilient, which guarantees that all benign participants converge to an identical model that deviates from a global model trained without Byzantine adversaries by a bounded distance. We evaluate Brave against three state-of-the-art adversaries on a P2P FL for image classification tasks on benchmark datasets CIFAR10 and MNIST. Our results show that the global model learned with Brave in the presence of adversaries achieves comparable classification accuracy to a global model trained in the absence of any adversary

Enhancement on the hardness and oxidation resistance property of TiN/Ag composite films for high temperature applications by addition of Si

Titanium nitride and silver (TiN/Ag) composite films exhibited the excellent self-lubricating properties in a wide temperature range due to the formation of the Ag rich tribolayer in the contact. However, Ag addition usually reduces the hardness and oxidation resistance properties of the films. In this paper, TiN/Ag/Si3N4 composite films were deposited using RF magnetron co-sputtering system to improve the mechanical and oxidation resistance properties of the TiN/Ag film. XRD and TEM analysis revealed that three-phases could be identified on the TiN/Ag/Si3N4 films: face-centered cubic (fcc) TiN, fcc-Ag and amorphous Si3N4 phases. The hardness of the TiN/ Ag film increased from ~16 GPa to ~24 GPa for TiN/Ag/Si3N4 with 15.3 at.% of Si due to the formation of the nanocomposite structure. The addition of Si allowed a significant improvement on the oxidation resistance temperature, and effectively avoiding of Ag diffusion, and thereby contributing the stability of the hardness of the film after annealing treatment.info:eu-repo/semantics/publishedVersio

Programming by Example Made Easy

Programming by example (PBE) is an emerging programming paradigm that automatically synthesizes programs specified by user-provided input-output examples. Despite the convenience for end-users, implementing PBE tools often requires strong expertise in programming language and synthesis algorithms. Such a level of knowledge is uncommon among software developers. It greatly limits the broad adoption of PBE by the industry. To facilitate the adoption of PBE techniques, we propose a PBE framework called Bee, which leverages an "entity-action" model based on relational tables to ease PBE development for a wide but restrained range of domains. Implementing PBE tools with Bee only requires adapting domain-specific data entities and user actions to tables, with no need to design a domain-specific language or an efficient synthesis algorithm. The synthesis algorithm of Bee exploits bidirectional searching and constraint-solving techniques to address the challenge of value computation nested in table transformation. We evaluated Bee's effectiveness on 64 PBE tasks from three different domains and usability with a human study of 12 participants. Evaluation results show that Bee is easier to learn and use than the state-of-the-art PBE framework, and the bidirectional algorithm achieves comparable performance to domain-specifically optimized synthesizers.Comment: Accepted by ACM Transactions on Software Engineering and Methodolog

Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications

Large language models (LLMs) are increasingly deployed as the service backend for LLM-integrated applications such as code completion and AI-powered search. LLM-integrated applications serve as middleware to refine users' queries with domain-specific knowledge to better inform LLMs and enhance the responses. Despite numerous opportunities and benefits, LLM-integrated applications also introduce new attack surfaces. Understanding, minimizing, and eliminating these emerging attack surfaces is a new area of research. In this work, we consider a setup where the user and LLM interact via an LLM-integrated application in the middle. We focus on the communication rounds that begin with user's queries and end with LLM-integrated application returning responses to the queries, powered by LLMs at the service backend. For this query-response protocol, we identify potential vulnerabilities that can originate from the malicious application developer or from an outsider threat initiator that is able to control the database access, manipulate and poison data that are high-risk for the user. Successful exploits of the identified vulnerabilities result in the users receiving responses tailored to the intent of a threat initiator. We assess such threats against LLM-integrated applications empowered by OpenAI GPT-3.5 and GPT-4. Our empirical results show that the threats can effectively bypass the restrictions and moderation policies of OpenAI, resulting in users receiving responses that contain bias, toxic content, privacy risk, and disinformation. To mitigate those threats, we identify and define four key properties, namely integrity, source identification, attack detectability, and utility preservation, that need to be satisfied by a safe LLM-integrated application. Based on these properties, we develop a lightweight, threat-agnostic defense that mitigates both insider and outsider threats

Joint Location, Bandwidth and Power Optimization for THz-enabled UAV Communications

In this paper, the problem of unmanned aerial vehicle (UAV) deployment, power allocation, and bandwidth allocation is investigated for a UAV-assisted wireless system operating at terahertz (THz) frequencies. In the studied model, one UAV can service ground users using the THz frequency band. However, the highly uncertain THz channel will introduce new challenges to the UAV location, user power, and bandwidth allocation optimization problems. Therefore, it is necessary to design a novel framework to deploy UAVs in the THz wireless systems. This problem is formally posed as an optimization problem whose goal is to minimize the total delays of the uplink and downlink transmissions between the UAV and the ground users by jointly optimizing the deployment of the UAV, the transmit power and the bandwidth of each user. The communication delay is crucial for emergency communications. To tackle this nonconvex delay minimization problem, an alternating algorithm is proposed while iteratively solving three subproblems: location optimization subproblem, power control subproblem, and bandwidth allocation subproblem. Simulation results show that the proposed algorithm can reduce the transmission delay by up to $59.3\%$, $49.8\%$ and $75.5\%$ respectively compared to baseline algorithms that optimize only UAV location, bandwidth allocation or transmit power control.Comment: 5 pages IEEE Communications Letter

Ultralight and porous cellulose nanofibers/polyethyleneimine composite aerogels with exceptional performance for selective anionic dye adsorption

It is significant to develop new adsorbents with excellent adsorption performance and convenient operation ability for removing pollutants from wastewater owing to the growing environmental problems. In this paper, a novel ultralight aerogel-based adsorbent with highly porous structure and good mechanical integrity was fabricated based on the interaction of amine groups on polyethyleneimine (PEI) and hydroxyl groups on cellulose nanofibers (CNF), with epichlorohydrin (ECH) serving as a crosslinker. The obtained CNF/PEI aerogel showed excellent water stability in harsh conditions, fast water-activated shape recovery, and ultra-fast water transport. The adsorption capacity for methyl orange (MO) in batch can reach to1226 mg g−1 at pH 6. Furthermore, the membrane also exhibited excellent selective adsorption and filtration, and separation performance. Therefore, this paper presents a new strategy to prepare low-cost and highly efficient adsorbents to remove organic dyes from wastewater for potential practical applications.</p

Identification and Characterization of New Resistance-Conferring SGI1s (Salmonella Genomic Island 1) in Proteus mirabilis

Salmonella genomic island 1 (SGI1) is a resistance-conferring chromosomal genomic island that contains an antibiotic resistance gene cluster. The international spread of SGI1-containing strains drew attention to the role of genomic islands in the dissemination of antibiotic resistance genes in Salmonella and other Gram-negative bacteria. In this study, five SGI1 variants conferring multidrug and heavy metal resistance were identified and characterized in Proteus mirabilis strains: SGI1-PmCAU, SGI1-PmABB, SGI1-PmJN16, SGI1-PmJN40, and SGI1-PmJN48. The genetic structures of SGI1-PmCAU and SGI1-PmABB were identical to previously reported SGI1s, while structural analysis showed that SGI1-PmJN16, SGI1-PmJN40, and SGI1-PmJN48 are new SGI1 variants. SGI1-PmJN16 is derived from SGI1-Z with the MDR region containing a new gene cassette array dfrA12-orfF-aadA2-qacEΔ1-sul1-chrA-orf1. SGI1-PmJN40 has an unprecedented structure that contains two right direct repeat sequences separated by a transcriptional regulator-rich DNA fragment, and is predicted to form two different extrachromosomal mobilizable DNA circles for dissemination. SGI1-PmJN48 lacks a common ORF S044, and its right junction region exhibits a unique genetic organization due to the reverse integration of a P. mirabilis chromosomal gene cluster and the insertion of part of a P. mirabilis plasmid, making it the largest known SGI1 to date (189.1 kb). Further mobility functional analysis suggested that these SGIs can be excised from the chromosome for transfer between bacteria, which promotes the horizontal transfer of antibiotic and heavy metal resistance genes. The identification and characterization of the new SGI1 variants in this work suggested the diversity of SGI1 structures and their significant roles in the evolution of bacteria