activity
20162024
most citedPeek-a-Boo: I see your smart home activities, even encrypted!

253 citations · 364 across the 11 of their papers we have counts for

collaborators

14 papers

cs.CR2024★ 2 cited

Phantom: Untargeted Poisoning Attacks on Semi-Supervised Learning (Full Version)

Jonathan Knauer, Phillip Rieger, Hossein Fereidooni +1

Deep Neural Networks (DNNs) can handle increasingly complex tasks, albeit they require rapidly expanding training datasets. Collecting data from platforms with user-generated conte…

cs.CR2024

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning

Hossein Fereidooni, Alessandro Pegoraro, Phillip Rieger +2

Federated learning (FL) is a collaborative learning paradigm allowing multiple clients to jointly train a model without sharing their training data. However, FL is susceptible to p…

cs.CR2023

DEMASQ: Unmasking the ChatGPT Wordsmith

Kavita Kumari, Alessandro Pegoraro, Hossein Fereidooni +1

The potential misuse of ChatGPT and other Large Language Models (LLMs) has raised concerns regarding the dissemination of false information, plagiarism, academic dishonesty, and fr…

cs.CR2023★ 1 cited

FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks

Jorge Castillo, Phillip Rieger, Hossein Fereidooni +2

Federated learning (FL) is a distributed learning process that uses a trusted aggregation server to allow multiple parties (or clients) to collaboratively train a machine learning…

cs.LG2023★ 37 cited

To ChatGPT, or not to ChatGPT: That is the question!

Alessandro Pegoraro, Kavita Kumari, Hossein Fereidooni +1

ChatGPT has become a global sensation. As ChatGPT and other Large Language Models (LLMs) emerge, concerns of misusing them in various ways increase, such as disseminating fake news…

cs.CR2023★ 4 cited

ARGUS: Context-Based Detection of Stealthy IoT Infiltration Attacks

Phillip Rieger, Marco Chilese, Reham Mohamed +3

IoT application domains, device diversity and connectivity are rapidly growing. IoT devices control various functions in smart homes and buildings, smart cities, and smart factorie…

cs.CR2023★ 4 cited

AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms

Hossein Fereidooni, Jan König, Phillip Rieger +5

Mobile applications are widely used for online services sharing a large amount of personal data online. One-time authentication techniques such as passwords and physiological biome…

cs.LG2023★ 6 cited

BayBFed: Bayesian Backdoor Defense for Federated Learning

Kavita Kumari, Phillip Rieger, Hossein Fereidooni +2

Federated learning (FL) allows participants to jointly train a machine learning model without sharing their private data with others. However, FL is vulnerable to poisoning attacks…

cs.CR2021★ 33 cited

ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning

Oliver Lutz, Huili Chen, Hossein Fereidooni +4

Ethereum smart contracts are automated decentralized applications on the blockchain that describe the terms of the agreement between buyers and sellers, reducing the need for trust…

cs.CR2021★ 4 cited

FLAME: Taming Backdoors in Federated Learning (Extended Version 1)

Thien Duc Nguyen, Phillip Rieger, Huili Chen +10

Federated Learning (FL) is a collaborative machine learning approach allowing participants to jointly train a model without having to share their private, potentially sensitive loc…

cs.CR2018★ 253 cited

Peek-a-Boo: I see your smart home activities, even encrypted!

Abbas Acar, Hossein Fereidooni, Tigist Abera +6

A myriad of IoT devices such as bulbs, switches, speakers in a smart home environment allow users to easily control the physical world around them and facilitate their living style…

cs.CR2018

DÏoT: A Federated Self-learning Anomaly Detection System for IoT

Thien Duc Nguyen, Samuel Marchal, Markus Miettinen +3

IoT devices are increasingly deployed in daily life. Many of these devices are, however, vulnerable due to insecure design, implementation, and configuration. As a result, many net…

cs.CR2017

Breaking Fitness Records without Moving: Reverse Engineering and Spoofing Fitbit

Hossein Fereidooni, Jiska Classen, Tom Spink +5

Tens of millions of wearable fitness trackers are shipped yearly to consumers who routinely collect information about their exercising patterns. Smartphones push this health-relate…

cs.CR2016★ 20 cited

Android Code Protection via Obfuscation Techniques: Past, Present and Future Directions

Parvez Faruki, Hossein Fereidooni, Vijay Laxmi +2

Mobile devices have become ubiquitous due to centralization of private user information, contacts, messages and multiple sensors. Google Android, an open-source mobile Operating Sy…