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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 against adversarial attacks. Indeed, some people may need to hide specific data to AI-based digital forensics tools, thus manipulating the content so that the AI system does not recognize the offensive/prohibited content and marks it at as suspicious to the analyst. This could be seen as an anti-forensics attack scenario. For this reason, we analyzed two of the most important forensics tools employing AI for data classification: Magnet AI, used by Magnet Axiom, and Excire Photo AI, used by X-Ways Forensics. We made preliminary tests using about $200$ images, other $100$ sent in $3$ chats about pornography and teenage nudity, drugs and weapons to understand how the tools label them. Moreover, we loaded some deepfake images (images generated by AI forging real ones) of some actors to understand if they would be classified in the same category as the original images. From our preliminary study, we saw that the AI algorithm is not robust enough, as we expected since these topics are still open research problems. For example, some sexual images were not categorized as nudity, and some deepfakes were categorized as the same real person, while the human eye can see the clear nudity image or catch the difference between the deepfakes. Building on these results and other state-of-the-art works, we provide some suggestions for improving how digital forensics analysis tool leverage AI and their robustness against adversarial attacks or different scenarios than the trained one.

The last years have seen an increase in Man-at-the-End (MATE) attacks against software applications, both in number and severity. However, software protection, which aims at mitigating MATE attacks, is dominated by fuzzy concepts and security-through-obscurity. This paper presents a rationale for adopting and standardizing the protection of software as a risk management process according to the NIST SP800-39 approach. We examine the relevant constructs, models, and methods needed for formalizing and automating the activities in this process in the context of MATE software protection. We highlight the open issues that the research community still has to address. We discuss the benefits that such an approach can bring to all stakeholders. In addition, we present a Proof of Concept (PoC) decision support system that instantiates many of the discussed construct, models, and methods and automates many activities in the risk analysis methodology for the protection of software. Despite being a prototype, the PoC's validation with industry experts indicated that several aspects of the proposed risk management process can already be formalized and automated with our existing toolbox and that it can actually assist decision-making in industrially relevant settings., Comment: Preprint submitted to Computers & Security. arXiv admin note: substantial text overlap with arXiv:2011.07269

The last years have seen an increase of Man-at-the-End (MATE) attacks against software applications, both in number and severity. However, MATE software protections are dominated by fuzzy concepts and techniques, with security-through-obscurity omnipresent in the field. This paper presents a rationale for adopting and standardizing the protection of software as a risk management process according to the NIST SP800-39 approach. We examine the relevant aspects of formalizing and automating the activities in this process in the context of MATE software protection. We highlight the open issues that the research community still has to address. We discuss the benefits that such an approach can bring to all stakeholders. In addition, we present a Proof of Concept (PoC) of a decision support system that automates many activities in the risk analysis methodology towards the protection of software applications. Despite still being a prototype, the PoC validation with industry experts indicated that several aspects of the proposed risk management process can already be formalized and automated with our existing toolbox, and that it can actually assist decision making in industrially relevant settings

Obfuscation techniques are a general category of software protections widely adopted to prevent malicious tampering of the code by making applications more difficult to understand and thus harder to modify. Obfuscation techniques are divided in code and data obfuscation, depending on the protected asset. While preliminary empirical studies have been conducted to determine the impact of code obfuscation, our work aims at assessing the effectiveness and efficiency in preventing attacks of a specific data obfuscation technique - VarMerge. We conducted an experiment with student participants performing two attack tasks on clear and obfuscated versions of two applications written in C. The experiment showed a significant effect of data obfuscation on both the time required to complete and the successful attack efficiency. An application with VarMerge reduces by six times the number of successful attacks per unit of time. This outcome provides a practical clue that can be used when applying software protections based on data obfuscation., Comment: Post-print, SCAM 2016

In recent years, ethical issues in the networking field are getting moreimportant. In particular, there is a consistent debate about how Internet Service Providers (ISPs) should collect and treat network measurements. This kind of information, such as flow records, carry interesting knowledge from multiple points of view: research, traffic engineering and e-commerce can benefit from measurements retrievable through inspection of network traffic. Nevertheless, in some cases they can carry personal information about the users exposed to monitoring, and so generates several ethical issues. Modern web is very different from the one we could experience few years ago; web services converged to few protocols (i.e., HyperText Transfer Protocol (HTTP) and HTTPS) and always bigger share of encrypted traffic. The aim of this work is to provide an insight about which information is still visible to ISPs in the modern web and to what extent it carries personal information. We show ethical issues deriving by this new situation and provide general guidelines and best-practices to cope with the collection of network traffic measurements., Comment: 9 pages, 3 figures