889 citations · 2k across the 11 of their papers we have counts for
11 papers
Propagation Model for SSC attacks: Why SBOM (tools) don't tell the whole truth
Ljubica Grgic, Lazar Maksimovic, Pavel Laskov
Ensuring security of software supply chains (SSC) is indispensable in today's world of modern software practices. SBOM (tools) have been introduced as relevant building blocks to e…
The Ephemeral Threat: Assessing the Security of Algorithmic Trading Systems powered by Deep Learning
Advije Rizvani, Giovanni Apruzzese, Pavel Laskov
We study the security of stock price forecasting using Deep Learning (DL) in computational finance. Despite abundant prior research on the vulnerability of DL to adversarial pertur…
SoK: On the Offensive Potential of AI
Saskia Laura Schröer, Giovanni Apruzzese, Soheil Human +13
Our society increasingly benefits from Artificial Intelligence (AI). Unfortunately, more and more evidence shows that AI is also used for offensive purposes. Prior works have revea…
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection
Giovanni Apruzzese, Pavel Laskov, Johannes Schneider
Machine Learning (ML) has become a valuable asset to solve many real-world tasks. For Network Intrusion Detection (NID), however, scientific advances in ML are still seen with skep…
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples
Giovanni Apruzzese, Rodion Vladimirov, Aliya Tastemirova +1
Fifth Generation (5G) networks must support billions of heterogeneous devices while guaranteeing optimal Quality of Service (QoS). Such requirements are impossible to meet with hum…
The Role of Machine Learning in Cybersecurity
Giovanni Apruzzese, Pavel Laskov, Edgardo Montes de Oca +4
Machine Learning (ML) represents a pivotal technology for current and future information systems, and many domains already leverage the capabilities of ML. However, deployment of M…
SoK: The Impact of Unlabelled Data in Cyberthreat Detection
Giovanni Apruzzese, Pavel Laskov, Aliya Tastemirova
Machine learning (ML) has become an important paradigm for cyberthreat detection (CTD) in the recent years. A substantial research effort has been invested in the development of sp…
Towards Understanding the Skill Gap in Cybersecurity
Francois Goupil, Pavel Laskov, Irdin Pekaric +3
Given the ongoing "arms race" in cybersecurity, the shortage of skilled professionals in this field is one of the strongest in computer science. The currently unmet staffing demand…
Evasion Attacks against Machine Learning at Test Time
Battista Biggio, Igino Corona, Davide Maiorca +5
In security-sensitive applications, the success of machine learning depends on a thorough vetting of their resistance to adversarial data. In one pertinent, well-motivated attack s…
Poisoning Attacks against Support Vector Machines
Battista Biggio, Blaine Nelson, Pavel Laskov
We investigate a family of poisoning attacks against Support Vector Machines (SVM). Such attacks inject specially crafted training data that increases the SVM's test error. Central…
Security Analysis of Online Centroid Anomaly Detection
Marius Kloft, Pavel Laskov
Security issues are crucial in a number of machine learning applications, especially in scenarios dealing with human activity rather than natural phenomena (e.g., information ranki…