Dr. Luca Caviglione

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Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

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30 December 2020 in IEEE Access

Journal Article

Tight Arms Race: Overview of Current Malware Threats and Trends in Their Detection

Luca Caviglione

Michał Choraś

Igino Corona

Artur Janicki

Wojciech Mazurczyk

Katarzyna Wasielewska

Cyber attacks are currently blooming, as the attackers reap significant profits from them and face a limited risk when compared to committing the “classical” crimes. One of the major components that leads to the successful compromising of the targeted system is malicious software. It allows using the victim’s machine for various nefarious purposes, e.g., making it a part of the botnet, mining cryptocurrencies, or holding hostage the data stored there. At present, the complexity, proliferation, and variety of malware pose a real challenge for the existing countermeasures and require their constant improvements. That is why, in this paper we first perform a detailed meta-review of the existing surveys related to malware and its detection techniques, showing an arms race between these two sides of a barricade. On this basis, we review the evolution of modern threats in the communication networks, with a particular focus on the techniques employing information hiding. Next, we present the bird’s eye view portraying the main development trends in detection methods with a special emphasis on the machine learning techniques. The survey is concluded with the description of potential future research directions in the field of malware detection.

22 December 2015 in IEEE Transactions on Information Forensics and Security

Journal Article

Seeing the Unseen: Revealing Mobile Malware Hidden Communications via Energy Consumption and Artificial Intelligence

Luca Caviglione

Mauro Gaggero

Jean-Francois Lalande

Wojciech Mazurczyk

Marcin Urbanski

Modern malware uses advanced techniques to hide from static and dynamic analysis tools. To achieve stealthiness when attacking a mobile device, an effective approach is the use of a covert channel built by two colluding applications to exchange data locally. Since this process is tightly coupled with the used hiding method, its detection is a challenging task, also worsened by the very low transmission rates. As a consequence, it is important to investigate how to reveal the presence of malicious software using general indicators, such as the energy consumed by the device. In this perspective, this paper aims to spot malware covertly exchanging data using two detection methods based on artificial intelligence tools, such as neural networks and decision trees. To verify their effectiveness, seven covert channels have been implemented and tested over a measurement framework using Android devices. Experimental results show the feasibility and effectiveness of the proposed approach to detect the hidden data exchange between colluding applications.

14 April 2015 in IEEE Security & Privacy

Journal Article

Information Hiding as a Challenge for Malware Detection

Wojciech Mazurczyk

Luca Caviglione

Malware increasingly uses information-hiding techniques to hide its existence and communication attempts. Having a better understanding of this technique could help mitigate and prevent cyberattacks.

27 August 2014 in IEEE Communications Surveys & Tutorials

Journal Article

Steganography in Modern Smartphones and Mitigation Techniques

Wojciech Mazurczyk

Luca Caviglione

By offering sophisticated services and centralizing a huge volume of personal data, modern smartphones changed the way we socialize, entertain and work. To this aim, they rely upon complex hardware/software frameworks leading to a number of vulnerabilities, attacks and hazards to profile individuals or gather sensitive information. However, the majority of works evaluating the security degree of smartphones neglects steganography, which can be mainly used to: i) exfiltrate confidential data via camouflage methods, and ii) conceal valuable or personal information into innocent looking carriers. Therefore, this paper surveys the state of the art of steganographic techniques for smartphones, with emphasis on methods developed over the period 2005 to the second quarter of 2014. The different approaches are grouped according to the portion of the device used to hide information, leading to three different covert channels, i.e., local, object and network. Also, it reviews the relevant approaches used to detect and mitigate steganographic attacks or threats. Lastly, it showcases the most popular software applications to embed secret data into carriers, as well as possible future directions.

12 July 2018 in IEEE Communications Letters

Journal Article

IEEE 802.15.4 Air-Ground UAV Communications in Smart Farming Scenarios

Smart farming is one of the most promising applications showing the benefits of using unmanned aerial vehicles (UAVs). Thus, precision agriculture in rural areas may largely benefit from low-cost and easy-to-deploy vehicles able to exchange data with ground sensors for monitoring and controlling automated cultivations. In this letter, we describe, both analytically and empirically, a real testbed implementing IEEE 802.15.4-based communications between an UAV and fixed ground sensors. In our scenario, we found that aerial mobility limits the actual IEEE 802.15.4 transmission range among the UAV and the ground nodes to approximately 1/3 of the nominal one. We also provide considerations to design the deployment of sensors in precision agriculture scenarios.

1 December 2015 in Pervasive and Mobile Computing

Journal Article

A survey on energy-aware security mechanisms

Alessio Merlo

Mauro Migliardi

Luca Caviglione

About Me

Luca Caviglione is a Senior Research Scientist at the Institute for Applied Mathematics and Information Technologies of the National Research Council of Italy. He holds a Ph.D. in Electronic and Computer Engineering from the University of Genoa, Italy. His research interests include optimization of large-scale computing frameworks, traffic analysis, and network security. He is an author or co-author of more than 150 academic publications, and several patents in the field of p2p and energy-aware computing. He has been involved in Research Projects and Network of Excellences funded by the ESA, the EU and the MIUR. Currently he is the Principal Investigator for IMATI of the project “Secure Intelligent Methods for Advanced Recognition of Malware and Stegomalware” (SIMARGL – call H2020-SU-ICT-2018, grant no. 833042). He is a Work Group Leader of the Italian IPv6 Task Force, a contract Professor in the field of networking/security and a Professional Engineer. From 2016 he is an Associate Editor of the International Journal of Computers and Applications, Taylor&Francis. He is the head of the IMATI Research Unit of the National Inter-University Consortium for Telecommunications and part of the Steering Committee of the Criminal Use of Information Hiding initiative.

Dr. Luca Caviglione

Dr. Luca Caviglione

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About Me