Davide Maiorca

University of Cagliari | UNICA · Department of Electrical and Electronic Engineering

Nowadays, many tools are used to facilitate forensic tasks about data extraction and data analysis. In particular, some tools leverage Artificial Intelligence (AI) to automatically label examined data into specific categories (\ie, drugs, weapons, nudity). However, this raises a serious concern about the robustness of the employed AI algorithms aga...

Android is the most used operating system (OS) worldwide for mobile devices, with hundreds of thousands of apps downloaded daily. Although these apps are primarily written in Java and Kotlin, advanced functionalities such as graphics or cryptography are provided through native C/C++ libraries. These libraries can be affected by common vulnerabiliti...

Macro-based Office files have been extensively used as infection vectors to embed malware. In particular, VBA macros allow leveraging kernel functions and system routines to execute or remotely drop malicious payloads, and they are typically heavily obfuscated to make static analysis unfeasible. Current state-of-the-art approaches focus on discrimi...

Android is the most used Operating System worldwide for mobile devices, with hundreds of thousands of apps downloaded daily. Although these apps are primarily written in Java and Kotlin, advanced functionalities such as graphics or cryptography are provided through native C/C++ libraries. These libraries can be affected by common vulnerabilities in...

Cryptography allows for guaranteeing secure communications, concealing critical data from reverse engineering, or ensuring mobile users’ privacy. Android malware developers extensively leveraged cryptographic libraries to obfuscate and hide malicious behavior. Various system-based and third-party libraries provide cryptographic functionalities for...

Android applications ship with several native C/C++ libraries. Research on Android security has revealed that these libraries often come from third-party components that are not kept up to date by developers, possibly posing security concerns. To assess if known vulner-abilities in these libraries constitute an immediate security problem, we need t...

Android applications ship with several native C/C++ libraries. Research on Android security has revealed that these libraries often come from third-party components that are not kept up to date by developers, possibly posing security concerns. To assess if known vulnerabilities in these libraries constitute an immediate security problem, we need to...

Malicious Windows executables still constitute one of the major threats to computer security. Various machine learning-based approaches have been proposed to distinguish them from benign applications or perform family classification, a critical task for threat intelligence. However, most of these techniques do not explicitly model the relationships...

Cryptography has been extensively used in Android applications to guarantee secure communications, conceal critical data from reverse engineering, or ensure mobile users' privacy. Various system-based and third-party libraries for Android provide cryptographic functionalities, and previous works mainly explored the misuse of cryptographic API in be...

While machine-learning algorithms have demonstrated a strong ability in detecting Android malware, they can be evaded by sparse evasion attacks crafted by injecting a small set of fake components, e.g., permissions and system calls, without compromising intrusive functionality. Previous work has shown that, to improve robustness against such attack...

Due to its popularity, the Android operating system is a critical target for malware attacks. Multiple security efforts have been made on the design of malware detection systems to identify potentially harmful applications. In this sense, machine learning-based systems, leveraging both static and dynamic analysis, have been increasingly adopted to...

Machine-learning algorithms trained on features extracted from static code analysis can successfully detect Android malware. However, these approaches can be evaded by sparse evasion attacks that produce adversarial malware samples in which only few features are modified. This can be achieved, e.g., by injecting a small set of fake permissions and...

During the past four years, Flash malware has become one of the most insidious threats to detect, with almost 600 critical vulnerabilities targeting Adobe Flash Player disclosed in the wild. Research has shown that machine learning can be successfully used to detect Flash malware by leveraging static analysis to extract information from the structu...

Malware still constitutes a major threat in the cybersecurity landscape, also due to the widespread use of infection vectors such as documents. These infection vectors hide embedded malicious code to the victim users, facilitating the use of social engineering techniques to infect their machines. Research showed that machine-learning algorithms pro...

PowerShell is nowadays a widely-used technology to administrate and manage Windows-based operating systems. However, it is also extensively used by malware vectors to execute payloads or drop additional malicious contents. Similarly to other scripting languages used by malware, PowerShell attacks are challenging to analyze due to the extensive use...

Ransomware constitutes a significant threat to the Android operating system. It can either lock or encrypt the target devices, and victims are forced to pay ransoms to restore their data. Hence, the prompt detection of such attacks has a priority in comparison to other malicious threats. Previous works on Android malware detection mainly focused on...

PowerShell is nowadays a widely-used technology to administrate and manage Windows-based operating systems. However, it is also extensively used by malware vectors to execute payloads or drop additional malicious contents. Similarly to other scripting languages used by malware, PowerShell attacks are challenging to analyze due to the extensive use...

Malware still constitutes a major threat in the cybersecurity landscape, also due to the widespread use of infection vectors such as documents and other media formats. These infection vectors hide embedded malicious code to the victim users, thus facilitating the use of social engineering techniques to infect their machines. In the last decade, mac...

Ransomware constitutes a major threat for the Android operating system. It can either lock or encrypt the target devices, and victims may be forced to pay ransoms to restore their data. Despite previous works on malware detection, little has been done to specifically identify Android malware as ransomware. This is crucial, as ransomware requires im...

Machine-learning models have been recently used for detecting malicious Android applications, reporting impressive performances on benchmark datasets, even when trained only on features statically extracted from the application, such as system calls and permissions. However, recent findings have highlighted the fragility of such in-vitro evaluation...

During the past two years, Flash malware has become one of the most insidious threats to detect, with almost 600 critical vulnerabilities targeting Adobe Flash Player disclosed in the wild. Research has shown that machine learning can be successfully used to tackle this increasing variability and sophistication of Flash malware, by simply leveragin...

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 scenario, an adversary may attempt to evade a deployed system at test time by carefully manipulating attack samples. In this work, we present a simple but effective gradie...

Over the last decade, malicious software (or malware, for short) has shown an increasing sophistication and proliferation, fueled by a flourishing underground economy, in response to the increasing complexity of modern defense mechanisms. PDF documents are among the major vectors used to convey malware, thanks to the flexibility of their structure...

Over the last decade, malicious software (or malware, for short) has shown an increasing sophistication and proliferation, fueled by a flourishing underground economy, in response to the increasing complexity of modern defense mechanisms. PDF documents are among the major vectors used to convey malware, thanks to the flexibility of their structure...

To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for malware detection. However, its security against well-crafted attacks has not only been recently questioned, but it has been shown that machine learning exhibits inherent vulnerabilities that can b...

To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for malware detection. However, its security against well-crafted attacks has not only been recently questioned, but it has been shown that machine learning exhibits inherent vulnerabilities that can b...

Ransomware has become a serious and concrete threat for mobile platforms and in particular for Android. In this paper, we propose R-PackDroid, a machine learning system for the detection of Android ransomware. Differently to previous works, we leverage information extracted from system API packages, which allow to characterize applications without...

We present AdversariaLib, an open-source python library for the security evaluation of machine learning (ML) against carefully-targeted attacks. It supports the implementation of several attacks proposed thus far in the literature of adversarial learning, allows for the evaluation of a wide range of ML algorithms, runs on multiple platforms, and ha...

The recent past has shown that Android smartphones became the most popular target for malware authors. Malware families offer a variety of features that allow, among the others, to steal arbitrary data and to cause significant monetary losses. This circumstances led to the development of many different analysis methods that are aimed to assess the...

Client fingerprinting techniques enhance classical cookie-based user tracking to increase the robustness of tracking techniques. A unique identifier is created based on characteristic attributes of the client device, and then used for deployment of personalized advertisements or similar use cases. Whereas fingerprinting performs well for highly cus...

Due to its popularity and open-source nature, An-droid is the mobile platform that has been targeted the most by malware that aim to steal personal information or to control the users' devices. More specifically, mobile botnets are malware that allow an attacker to remotely control the victims' devices through different channels like HTTP, thus cre...

In order to effectively evade anti-malware solutions, Android malware authors are progressively resorting to automatic obfuscation strategies. Recent works have shown, on small-scale experiments, the possibility of evading anti-malware engines by applying simple obfuscation transformations on previously detected malware samples. In this paper, we p...

During the past years, malicious PDF files have become a serious threat for the security of modern computer systems. They are characterized by a complex structure and their variety is considerably high. Several solutions have been academically developed to mitigate such attacks. However, they leveraged on information that were extracted from either...

Malicious PDF files still constitute a serious threat to the systems security. New reader vulnerabilities have been discovered, and research has shown that current state of the art approaches can be easily bypassed by exploiting weaknesses caused by erroneous parsing or incomplete information extraction. In this work, we present a novel machine lea...

JavaScript is a dynamic programming language adopted in a variety of applications, including web pages, PDF Readers, widget engines, network platforms, office suites. Given its widespread presence throughout different software platforms, JavaScript is a primary tool for the development of novel -rapidly evolving- malicious exploits. If the classica...

Support Vector Machines (SVMs) are among the most popular classification techniques adopted in security applications like malware detection, intrusion detection, and spam filtering. However, if SVMs are to be incorporated in real-world security systems, they must be able to cope with attack patterns that can either mislead the learning algorithm (p...

PDF files have proved to be excellent malicious-code bearing vectors. Thanks to their flexible logical structure, an attack can be hidden in several ways, and easily deceive protection mechanisms based on file-type filtering. Recent work showed that malicious PDF files can be accurately detected by analyzing their logical structure, with excellent...

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 scenario, an adversary may attempt to evade a deployed system at test time by carefully manipulating attack samples. In this work, we present a simple but effective gradie...

Malicious PDF files have been used to harm computer security during the past two-three years, and modern antivirus are proving to be not completely effective against this kind of threat. In this paper an innovative technique, which combines a feature extractor module strongly related to the structure of PDF files and an effective classifier, is pre...