Search Results for author: Mauro Conti

Found 53 papers, 12 papers with code

"All of Me": Mining Users' Attributes from their Public Spotify Playlists

no code implementations25 Jan 2024 Pier Paolo Tricomi, Luca Pajola, Luca Pasa, Mauro Conti

In this work, we investigate the relationship between Spotify users' attributes and their public playlists.

Topology-Based Reconstruction Prevention for Decentralised Learning

no code implementations8 Dec 2023 Florine W. Dekker, Zekeriya Erkin, Mauro Conti

To preserve the confidentiality of users' data, decentralised learning relies on differential privacy, multi-party computation, or a combination thereof.

Federated Learning Privacy Preserving

Dr. Jekyll and Mr. Hyde: Two Faces of LLMs

no code implementations6 Dec 2023 Matteo Gioele Collu, Tom Janssen-Groesbeek, Stefanos Koffas, Mauro Conti, Stjepan Picek

This work shows that by using adversarial personas, one can overcome safety mechanisms set out by ChatGPT and Bard.


AGIR: Automating Cyber Threat Intelligence Reporting with Natural Language Generation

1 code implementation4 Oct 2023 Filippo Perrina, Francesco Marchiori, Mauro Conti, Nino Vincenzo Verde

In this paper, we introduce AGIR (Automatic Generation of Intelligence Reports), a transformative Natural Language Generation tool specifically designed to address the pressing challenges in the realm of CTI reporting.

Hallucination Text Generation

Your Battery Is a Blast! Safeguarding Against Counterfeit Batteries with Authentication

2 code implementations7 Sep 2023 Francesco Marchiori, Mauro Conti

By using our proposed methodologies, manufacturers can ensure that devices only use legitimate batteries, guaranteeing the operational state of any system and safety measures for the users.

BlindSage: Label Inference Attacks against Node-level Vertical Federated Graph Neural Networks

no code implementations4 Aug 2023 Marco Arazzi, Mauro Conti, Stefanos Koffas, Marina Krcek, Antonino Nocera, Stjepan Picek, Jing Xu

In this work, we are the first (to the best of our knowledge) to investigate label inference attacks on VFL using a zero-background knowledge strategy.

Federated Learning Node Classification

Your Attack Is Too DUMB: Formalizing Attacker Scenarios for Adversarial Transferability

1 code implementation27 Jun 2023 Marco Alecci, Mauro Conti, Francesco Marchiori, Luca Martinelli, Luca Pajola

An alarming side-effect of evasion attacks is their ability to transfer among different models: this property is called transferability.

Turning Privacy-preserving Mechanisms against Federated Learning

no code implementations9 May 2023 Marco Arazzi, Mauro Conti, Antonino Nocera, Stjepan Picek

Recently, researchers have successfully employed Graph Neural Networks (GNNs) to build enhanced recommender systems due to their capability to learn patterns from the interaction between involved entities.

Federated Learning Privacy Preserving +1

Boosting Big Brother: Attacking Search Engines with Encodings

1 code implementation27 Apr 2023 Nicholas Boucher, Luca Pajola, Ilia Shumailov, Ross Anderson, Mauro Conti

Search engines are vulnerable to attacks against indexing and searching via text encoding manipulation.

Chatbot Text Summarization

Spritz-PS: Validation of Synthetic Face Images Using a Large Dataset of Printed Documents

no code implementations6 Apr 2023 Ehsan Nowroozi, Yoosef Habibi, Mauro Conti

To highlight the problems involved with the evaluation of the dataset's IRIS images, we conducted a large number of analyses employing Siamese Neural Networks to assess the similarities between genuine and synthetic human IRISes, such as ResNet50, Xception, VGG16, and MobileNet-v2.

Social Honeypot for Humans: Luring People through Self-managed Instagram Pages

no code implementations31 Mar 2023 Sara Bardi, Mauro Conti, Luca Pajola, Pier Paolo Tricomi

However, by choosing an appropriate content topic, this attractive mechanism could be extended to any OSN users, rather than only luring malicious actors.


STIXnet: A Novel and Modular Solution for Extracting All STIX Objects in CTI Reports

no code implementations17 Mar 2023 Francesco Marchiori, Mauro Conti, Nino Vincenzo Verde

The automatic extraction of information from Cyber Threat Intelligence (CTI) reports is crucial in risk management.

Management Relation Extraction

Cryptocurrency wallets: assessment and security

no code implementations6 Mar 2023 Ehsan Nowroozi, Seyedsadra Seyedshoari, Yassine Mekdad, Erkay Savas, Mauro Conti

Digital wallet as a software program or a digital device allows users to conduct various transactions.

SoK: A Systematic Evaluation of Backdoor Trigger Characteristics in Image Classification

no code implementations3 Feb 2023 Gorka Abad, Jing Xu, Stefanos Koffas, Behrad Tajalli, Stjepan Picek, Mauro Conti

Nevertheless, it is vulnerable to backdoor attacks that modify the training set to embed a secret functionality in the trained model.

Image Classification Transfer Learning

Temporal Dynamics of Coordinated Online Behavior: Stability, Archetypes, and Influence

no code implementations17 Jan 2023 Serena Tardelli, Leonardo Nizzoli, Maurizio Tesconi, Mauro Conti, Preslav Nakov, Giovanni Da San Martino, Stefano Cresci

Large-scale online campaigns, malicious or otherwise, require a significant degree of coordination among participants, which sparked interest in the study of coordinated online behavior.

Community Detection Dynamic Community Detection

Follow Us and Become Famous! Insights and Guidelines From Instagram Engagement Mechanisms

no code implementations17 Jan 2023 Pier Paolo Tricomi, Marco Chilese, Mauro Conti, Ahmad-Reza Sadeghi

Thanks to our interpretable approaches, we conclude by outlining guidelines for creating successful posts.


Going In Style: Audio Backdoors Through Stylistic Transformations

1 code implementation6 Nov 2022 Stefanos Koffas, Luca Pajola, Stjepan Picek, Mauro Conti

This work explores stylistic triggers for backdoor attacks in the audio domain: dynamic transformations of malicious samples through guitar effects.

Backdoor Attack

On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target Models

no code implementations28 Oct 2022 Mauro Conti, Jiaxin Li, Stjepan Picek

Membership Inference Attacks (MIAs) infer whether a data point is in the training data of a machine learning model.

Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks against Phishing Website Detectors using Machine Learning

1 code implementation24 Oct 2022 Ying Yuan, Giovanni Apruzzese, Mauro Conti

By considering the application of ML for Phishing Website Detection (PWD), we formalize the "evasion-space" in which an adversarial perturbation can be introduced to fool a ML-PWD -- demonstrating that even perturbations in the "feature-space" are useful.

Phishing Website Detection

Employing Deep Ensemble Learning for Improving the Security of Computer Networks against Adversarial Attacks

no code implementations25 Sep 2022 Ehsan Nowroozi, Mohammadreza Mohammadi, Erkay Savas, Mauro Conti, Yassine Mekdad

In this study, we present a novel architecture based on an ensemble classifier that combines the enhanced security of 1-Class classification (known as 1C) with the high performance of conventional 2-Class classification (known as 2C) in the absence of attacks. Our architecture is referred to as the 1. 5-Class (SPRITZ-1. 5C) classifier and constructed using a final dense classifier, one 2C classifier (i. e., CNNs), and two parallel 1C classifiers (i. e., auto-encoders).

Ensemble Learning

An Adversarial Attack Analysis on Malicious Advertisement URL Detection Framework

1 code implementation27 Apr 2022 Ehsan Nowroozi, abhishek, Mohammadreza Mohammadi, Mauro Conti

In this study, we extract a novel set of lexical and web-scrapped features and employ machine learning technique to set up system for fraudulent advertisement URLs detection.

Adversarial Attack

Real or Virtual: A Video Conferencing Background Manipulation-Detection System

no code implementations25 Apr 2022 Ehsan Nowroozi, Yassine Mekdad, Mauro Conti, Simone Milani, Selcuk Uluagac, Berrin Yanikoglu

Additionally, it enables users to employ a virtual background to conceal their own environment due to privacy concerns or to reduce distractions, particularly in professional settings.

The Cross-evaluation of Machine Learning-based Network Intrusion Detection Systems

1 code implementation9 Mar 2022 Giovanni Apruzzese, Luca Pajola, Mauro Conti

By using XeNIDS on six well-known datasets, we demonstrate the concealed potential, but also the risks, of cross-evaluations of ML-NIDS.

BIG-bench Machine Learning Network Intrusion Detection

Dynamic Backdoors with Global Average Pooling

no code implementations4 Mar 2022 Stefanos Koffas, Stjepan Picek, Mauro Conti

It was recently shown that countermeasures in image classification, like Neural Cleanse and ABS, could be bypassed with dynamic triggers that are effective regardless of their pattern and location.

Classification Image Classification +2

Detecting High-Quality GAN-Generated Face Images using Neural Networks

no code implementations3 Mar 2022 Ehsan Nowroozi, Mauro Conti, Yassine Mekdad

On the other hand, the recent development of GAN models may create high-quality face images without evidence of spatial artifacts.

Image Generation Vocal Bursts Intensity Prediction

Captcha Attack: Turning Captchas Against Humanity

no code implementations11 Jan 2022 Mauro Conti, Luca Pajola, Pier Paolo Tricomi

Content moderators constantly monitor these online platforms to prevent the spreading of inappropriate content (e. g., hate speech, nudity images).

Hand Me Your PIN! Inferring ATM PINs of Users Typing with a Covered Hand

no code implementations15 Oct 2021 Matteo Cardaioli, Stefano Cecconello, Mauro Conti, Simone Milani, Stjepan Picek, Eugen Saraci

We consider the setting where the attacker can access an ATM PIN pad of the same brand/model as the target one.


Demystifying the Transferability of Adversarial Attacks in Computer Networks

no code implementations9 Oct 2021 Ehsan Nowroozi, Yassine Mekdad, Mohammad Hajian Berenjestanaki, Mauro Conti, Abdeslam El Fergougui

In this paper, we provide the first comprehensive study which assesses the robustness of CNN-based models for computer networks against adversarial transferability.

Breast Cancer Detection

The Spread of Propaganda by Coordinated Communities on Social Media

no code implementations27 Sep 2021 Kristina Hristakieva, Stefano Cresci, Giovanni Da San Martino, Mauro Conti, Preslav Nakov

Large-scale manipulations on social media have two important characteristics: (i) use of propaganda to influence others, and (ii) adoption of coordinated behavior to spread it and to amplify its impact.

Do Not Deceive Your Employer with a Virtual Background: A Video Conferencing Manipulation-Detection System

no code implementations29 Jun 2021 Mauro Conti, Simone Milani, Ehsan Nowroozi, Gabriele Orazi

On the other hand, users maybe want to fool people in the meeting by considering the virtual background to conceal where they are.

Fall of Giants: How popular text-based MLaaS fall against a simple evasion attack

1 code implementation13 Apr 2021 Luca Pajola, Mauro Conti

The increased demand for machine learning applications made companies offer Machine-Learning-as-a-Service (MLaaS).

BIG-bench Machine Learning Sentence

UAVs Path Deviation Attacks: Survey and Research Challenges

no code implementations12 Feb 2021 Francesco Betti Sorbelli, Mauro Conti, Cristina M. Pinotti, Giulio Rigoni

No specific attacks and defenses have been found in literature for GNSS+ or for UAVs moving in group without a pre-ordered arrangement.

Cryptography and Security

A Survey on Industrial Control System Testbeds and Datasets for Security Research

no code implementations10 Feb 2021 Mauro Conti, Denis Donadel, Federico Turrin

In dealing with this security requirement, the research community focuses on developing new security mechanisms such as Intrusion Detection Systems (IDSs), facilitated by leveraging modern machine learning techniques.

Intrusion Detection Cryptography and Security

A Machine Learning-based Approach to Detect Threats in Bio-Cyber DNA Storage Systems

no code implementations28 Sep 2020 Federico Tavella, Alberto Giaretta, Mauro Conti, Sasitharan Balasubramaniam

The similarities between these biological media and classical ones can also be a drawback, as malicious parties might replicate traditional attacks on the former archival system, using biological instruments and techniques.

BIG-bench Machine Learning

Assessing the Use of Insecure ICS Protocols via IXP Network Traffic Analysis

no code implementations2 Jul 2020 Giovanni Barbieri, Mauro Conti, Nils Ole Tippenhauer, Federico Turrin

Therefore, Shodan do not allow to understand the actual use of insecure industrial protocols on the Internet and the current security practices in ICS communications.

Cryptography and Security Networking and Internet Architecture

On Defending Against Label Flipping Attacks on Malware Detection Systems

no code implementations13 Aug 2019 Rahim Taheri, Reza Javidan, Mohammad Shojafar, Zahra Pooranian, Ali Miri, Mauro Conti

Our evaluation shows that using random forest feature selection and varying ratios of features can result in an improvement of up to 19\% accuracy when compared with the state-of-the-art method in the literature.

Android Malware Detection BIG-bench Machine Learning +4

Can Machine Learning Model with Static Features be Fooled: an Adversarial Machine Learning Approach

no code implementations20 Apr 2019 Rahim Taheri, Reza Javidan, Mohammad Shojafar, Vinod P, Mauro Conti

We also test our methods using various classifier algorithms and compare them with the state-of-the-art data poisoning method using the Jacobian matrix.

BIG-bench Machine Learning Data Poisoning +3

PILOT: Password and PIN Information Leakage from Obfuscated Typing Videos

no code implementations30 Mar 2019 Kiran Balagani, Matteo Cardaioli, Mauro Conti, Paolo Gasti, Martin Georgiev, Tristan Gurtler, Daniele Lain, Charissa Miller, Kendall Molas, Nikita Samarin, Eugen Saraci, Gene Tsudik, Lynn Wu

This paper studies leakage of user passwords and PINs based on observations of typing feedback on screens or from projectors in the form of masked characters that indicate keystrokes.

Cryptography and Security K.6.5

All You Need is "Love": Evading Hate-speech Detection

no code implementations28 Aug 2018 Tommi Gröndahl, Luca Pajola, Mika Juuti, Mauro Conti, N. Asokan

With the spread of social networks and their unfortunate use for hate speech, automatic detection of the latter has become a pressing problem.

Hate Speech Detection

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

no code implementations8 Aug 2018 Abbas Acar, Hossein Fereidooni, Tigist Abera, Amit Kumar Sikder, Markus Miettinen, Hidayet Aksu, Mauro Conti, Ahmad-Reza Sadeghi, A. Selcuk Uluagac

It is realized utilizing state-of-the-art machine-learning approaches for detecting and identifying particular types of IoT devices, their actions, states, and ongoing user activities in a cascading style by only observing passively the wireless traffic from smart home devices.

Cryptography and Security

Internet of Things Security and Forensics: Challenges and Opportunities

no code implementations27 Jul 2018 Mauro Conti, Ali Dehghantanha, Katrin Franke, Steve Watson

The Internet of Things (IoT) envisions pervasive, connected, and smart nodes interacting autonomously while offering all sorts of services.

Cryptography and Security

Forensics Analysis of Android Mobile VoIP Apps

no code implementations15 Sep 2017 Tooska Dargahi, Ali Dehghantanha, Mauro Conti

Voice over Internet Protocol (VoIP) applications (apps) provide convenient and low cost means for users to communicate and share information with each other in real-time.

Cryptography and Security

Breaking Fitness Records without Moving: Reverse Engineering and Spoofing Fitbit

1 code implementation28 Jun 2017 Hossein Fereidooni, Jiska Classen, Tom Spink, Paul Patras, Markus Miettinen, Ahmad-Reza Sadeghi, Matthias Hollick, Mauro Conti

In this paper, we provide an in-depth security analysis of the operation of fitness trackers commercialized by Fitbit, the wearables market leader.

Cryptography and Security

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

no code implementations30 Nov 2016 Parvez Faruki, Hossein Fereidooni, Vijay Laxmi, Mauro Conti, Manoj Gaur

We believe that, there is a need to investigate efficiency of the defense techniques used for code protection.

Cryptography and Security

ODIN: Obfuscation-based privacy preserving consensus algorithm for Decentralized Information fusion in smart device Networks

no code implementations21 Oct 2016 Moreno Ambrosin, Paolo Braca, Mauro Conti, Riccardo Lazzaretti

ODIN is a privacy-preserving extension of the popular consensus gossip algorithm, that prevents distributed agents have direct access to the data while they iteratively reach consensus; agents cannot access even the final consensus value, but can only retrieve partial information, e. g., a binary decision.

Cryptography and Security

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