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Giampaolo Bella

Publications and source records attributed to Giampaolo Bella.

At least 19 recordsLinked to original sources

Poster: Machine Learning for Vulnerability Detection as Target Oracle in Automated Fuzz Driver Generation

In vulnerability detection, machine learning has been used as an effective static analysis technique, although it suffers from a significant rate of false positives. Contextually, in vulnerability discovery, fuzzing has been used as an effective dynamic analysis technique, although it requires manually writing fuzz drivers. Fuzz drivers usually target a limited subset of functions in a library that must be chosen according to certain criteria, e.g., the depth of a function, the number of paths. These criteria are verified by components called target oracles. In this work, we propose an automated fuzz driver generation workflow composed of: (1) identifying a likely vulnerable function by leveraging a machine learning for vulnerability detection model as a target oracle, (2) automatically generating fuzz drivers, (3) fuzzing the target function to find bugs which could confirm the vulnerability inferred by the target oracle. We show our method on an existing vulnerability in libgd, with a plan for large-scale evaluation.

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To See or Not to See: A Privacy Threat Model for Digital Forensics in Crime Investigation

Digital forensics is a cornerstone of modern crime investigations, yet it raises significant privacy concerns due to the collection, processing, and storage of digital evidence. Despite that, privacy threats in digital forensics crime investigations often remain underexplored, thereby leading to potential gaps in forensic practices and regulatory compliance, which may then escalate into harming the freedoms of natural persons. With this clear motivation, the present paper applies the SPADA methodology for threat modelling with the goal of incorporating privacy-oriented threat modelling in digital forensics. As a result, we identify a total of 298 privacy threats that may affect digital forensics processes through crime investigations. Furthermore, we demonstrate an unexplored feature on how SPADA assists in handling domain-dependency during threat elicitation. This yields a second list of privacy threats that are universally applicable to any domain. We then present a comprehensive and systematic privacy threat model for digital forensics in crime investigation. Moreover, we discuss some of the challenges about validating privacy threats in this domain, particularly given the variability of legal frameworks across jurisdictions. We ultimately propose our privacy threat model as a tool for ensuring ethical and legally compliant investigative practices.

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Not Sure Your Car Withstands Cyberwarfare

Data and derived information about target victims has always been key for successful attacks, both during historical wars and modern cyber wars. Ours turns out to be an era in which modern cars generate a plethora of data about their drivers, and such data could be extremely attractive for offenders. This paper seeks to assess how well modern cars protect their drivers' data. It pursues its goal at a requirement level by analysing the gaps of the privacy policies of chief automakers such as BMW and Mercedes with respect to the General Data Protection Regulation (GDPR). It is found that both brands are still imprecise about how they comply with a number of GDPR articles, hence compliance often results non-verifiable. Most importantly, while BMW exhibits slightly broader compliance, both brands still fail to comply with a number of relevant articles of the regulation. An interpretation of these findings is a non-negligible likelihood that your car may turn against you should cyberwarfare break out.

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The IoT Breaches your Household Again

Despite their apparent simplicity, devices like smart light bulbs and electrical plugs are often perceived as exempt from rigorous security measures. However, this paper challenges this misconception, uncovering how vulnerabilities in these seemingly innocuous devices can expose users to significant risks. This paper extends the findings outlined in previous work, introducing a novel attack scenario. This new attack allows malicious actors to obtain sensitive credentials, including the victim's Tapo account email and password, as well as the SSID and password of her local network. Furthermore, we demonstrate how these findings can be replicated, either partially or fully, across other smart devices within the same IoT ecosystem, specifically those manufactured by Tp-Link. Our investigation focused on the Tp-Link Tapo range, encompassing smart bulbs (Tapo L530E, Tapo L510E V2, and Tapo L630), a smart plug (Tapo P100), and a smart camera (Tapo C200). Utilizing similar communication protocols, or slight variants thereof, we found that the Tapo L530E, Tapo L510E V2, and Tapo L630 are susceptible to complete exploitation of all attack scenarios, including the newly identified one. Conversely, the Tapo P100 and Tapo C200 exhibit vulnerabilities to only a subset of attack scenarios. In conclusion, by highlighting these vulnerabilities and their potential impact, we aim to raise awareness and encourage proactive steps towards mitigating security risks in smart device deployment.

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Behind the (Digital Crime) Scenes: An MSC Model

Criminal investigations are inherently complex as they typically involve interactions among various actors like investigators, prosecutors, and defendants. The pervasive integration of technology in daily life adds an extra layer of complexity, especially in crimes that involve a digital element. The establishment of digital forensics as a foundational discipline for extracting digital evidence further exacerbates the complex nature of criminal investigations, leading to the proliferation of multiple scenarios. Recognising the need to structure standard operating procedures for the handling of digital evidence, the representation of digital forensics as a protocol emerges as a valuable opportunity to identify security and privacy threats. In this paper, we delineate the protocols that compose digital forensics within a criminal case, formalise them as message sequence charts (MSCs), and identify their functional requirements.

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An Ontological Approach to Compliance Verification of the NIS 2 Directive

Cybersecurity, which notoriously concerns both human and technological aspects, is becoming more and more regulated by a number of textual documents spanning several pages, such as the European GDPR Regulation and the NIS Directive. This paper introduces an approach that leverages techniques of semantic representation and reasoning, hence an ontological approach, towards the compliance check with the security measures that textual documents prescribe. We choose the ontology instrument to achieve two fundamental objectives: domain modelling and resource interrogation. The formalisation of entities and relations from the directive, and the consequent improved structuring with respect to sheer prose is dramatically helpful for any organisation through the hard task of compliance verification. The semantic approach is demonstrated with two articles of the new European NIS 2 directive.

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Blockchains through ontologies: the case study of the Ethereum ERC721 standard in OASIS (Extended Version)

Blockchains are gaining momentum due to the interest of industries and people in \emph{decentralized applications} (Dapps), particularly in those for trading assets through digital certificates secured on blockchain, called tokens. As a consequence, providing a clear unambiguous description of any activities carried out on blockchains has become crucial, and we feel the urgency to achieve that description at least for trading. This paper reports on how to leverage the \emph{Ontology for Agents, Systems, and Integration of Services} ("\ONT{}") as a general means for the semantic representation of smart contracts stored on blockchain as software agents. Special attention is paid to non-fungible tokens (NFTs), whose management through the ERC721 standard is presented as a case study.

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The Ontology for Agents, Systems and Integration of Services: OASIS version 2

Semantic representation is a key enabler for several application domains, and the multi-agent systems realm makes no exception. Among the methods for semantically representing agents, one has been essentially achieved by taking a behaviouristic vision, through which one can describe how they operate and engage with their peers. The approach essentially aims at defining the operational capabilities of agents through the mental states related with the achievement of tasks. The OASIS ontology -- An Ontology for Agent, Systems, and Integration of Services, presented in 2019 -- pursues the behaviouristic approach to deliver a semantic representation system and a communication protocol for agents and their commitments. This paper reports on the main modeling choices concerning the representation of agents in OASIS 2, the latest major upgrade of OASIS, and the achievement reached by the ontology since it was first introduced, in particular in the context of ontologies for blockchains.

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Up-to-date Threat Modelling for Soft Privacy on Smart Cars

Physical persons playing the role of car drivers consume data that is sourced from the Internet and, at the same time, themselves act as sources of relevant data. It follows that citizens' privacy is potentially at risk while they drive, hence the need to model privacy threats in this application domain. This paper addresses the privacy threats by updating a recent threat-modelling methodology and by tailoring it specifically to the soft privacy target property, which ensures citizens' full control on their personal data. The methodology now features the sources of documentation as an explicit variable that is to be considered. It is demonstrated by including a new version of the de-facto standard LINDDUN methodology as well as an additional source by ENISA which is found to be relevant to soft privacy. The main findings are a set of 23 domain-independent threats, 43 domain-specific assets and 525 domain-dependent threats for the target property in the automotive domain. While these exceed their previous versions, their main value is to offer self-evident support to at least two arguments. One is that LINDDUN has evolved much the way our original methodology already advocated because a few of our previously suggested extensions are no longer outstanding. The other one is that ENISA's treatment of privacy aboard smart cars should be extended considerably because our 525 threats fall in the same scope.

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Smart Bulbs can be Hacked to Hack into your Household

The IoT is getting more and more pervasive. Even the simplest devices, such as a light bulb or an electrical plug, are made "smart" and controllable by our smartphone. This paper describes the findings obtained by applying the PETIoT kill chain to conduct a Vulnerability Assessment and Penetration Testing session on a smart bulb, the Tapo L530E by Tp-Link, currently best seller on Amazon Italy. We found that four vulnerabilities affect the bulb, two of High severity and two of Medium severity according to the CVSS v3.1 scoring system. In short, authentication is not well accounted for and confidentiality is insufficiently achieved by the implemented cryptographic measures. In consequence, an attacker who is nearby the bulb can operate at will not just the bulb but all devices of the Tapo family that the user may have on her Tapo account. Moreover, the attacker can learn the victim's Wi-Fi password, thereby escalating his malicious potential considerably. The paper terminates with an outline of possible fixes.

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A behaviouristic approach to representing processes and procedures in the OASIS 2 ontology

Foundational ontologies devoted to the effective representation of processes and procedures are not widely investigated at present, thereby limiting the practical adoption of semantic approaches in real scenarios where the precise instructions to follow must be considered. Also, the representation ought to include how agents should carry out the actions associated with the process, whether or not agents are able to perform those actions, the possible roles played as well as the related events. The OASIS ontology provides an established model to capture agents and their interactions but lacks means for representing processes and procedures carried out by agents. This motivates the research presented in this article, which delivers an extension of the OASIS 2 ontology to combine the capabilities for representing agents and their behaviours with the full conceptualization of processes and procedures. The overarching goal is to deliver a foundational OWL ontology that deals with agent planning, reaching a balance between generality and applicability, which is known to be an open challenge.

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An automated method for the ontological representation of security directives

Large documents written in juridical language are difficult to interpret, with long sentences leading to intricate and intertwined relations between the nouns. The present paper frames this problem in the context of recent European security directives. The complexity of their language is here thwarted by automating the extraction of the relevant information, namely of the parts of speech from each clause, through a specific tailoring of Natural Language Processing (NLP) techniques. These contribute, in combination with ontology development principles, to the design of our automated method for the representation of security directives as ontologies. The method is showcased on a practical problem, namely to derive an ontology representing the NIS 2 directive, which is the peak of cybersecurity prescripts at the European level. Although the NLP techniques adopted showed some limitations and had to be complemented by manual analysis, the overall results provide valid support for directive compliance in general and for ontology development in particular.

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Towards Grammatical Tagging for the Legal Language of Cybersecurity

Legal language can be understood as the language typically used by those engaged in the legal profession and, as such, it may come both in spoken or written form. Recent legislation on cybersecurity obviously uses legal language in writing, thus inheriting all its interpretative complications due to the typical abundance of cases and sub-cases as well as to the general richness in detail. This paper faces the challenge of the essential interpretation of the legal language of cybersecurity, namely of the extraction of the essential Parts of Speech (POS) from the legal documents concerning cybersecurity. The challenge is overcome by our methodology for POS tagging of legal language. It leverages state-of-the-art open-source tools for Natural Language Processing (NLP) as well as manual analysis to validate the outcomes of the tools. As a result, the methodology is automated and, arguably, general for any legal language following minor tailoring of the preprocessing step. It is demonstrated over the most relevant EU legislation on cybersecurity, namely on the NIS 2 directive, producing the first, albeit essential, structured interpretation of such a relevant document. Moreover, our findings indicate that tools such as SpaCy and ClausIE reach their limits over the legal language of the NIS 2.

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A Threat Model for Soft Privacy on Smart Cars

Modern cars are getting so computerised that ENISA's phrase "smart cars" is a perfect fit. The amount of personal data that they process is very large and, yet, increasing. Hence, the need to address citizens' privacy while they drive and, correspondingly, the importance of privacy threat modelling (in support of a respective risk assessment, such as through a Data Protection Impact Assessment). This paper addresses privacy threats by advancing a general modelling methodology and by demonstrating it specifically on soft privacy, which ensures citizens' full control on their personal data. By considering all relevant threat agents, the paper applies the methodology to the specific automotive domain while keeping threats at the same level of detail as ENISA's. The main result beside the modelling methodology consists of both domain-independent and automotive domain-dependent soft privacy threats. While cybersecurity has been vastly threat-modelled so far, this paper extends the literature with a threat model for soft privacy on smart cars, producing 17 domain-independent threats that, associated with 41 domain-specific assets, shape a novel set of domain-dependent threats in automotive.

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How to Model Privacy Threats in the Automotive Domain

This paper questions how to approach threat modelling in the automotive domain at both an abstract level that features no domain-specific entities such as the CAN bus and, separately, at a detailed level. It addresses such questions by contributing a systematic method that is currently affected by the analyst's subjectivity because most of its inner operations are only defined informally. However, this potential limitation is overcome when candidate threats are identified and left to everyone's scrutiny. The systematic method is demonstrated on the established LINDDUN threat modelling methodology with respect to 4 pivotal works on privacy threat modelling in automotive. As a result, 8 threats that the authors deem not representable in LINDDUN are identified and suggested as possible candidate extensions to LINDDUN. Also, 56 threats are identified providing a detailed, automotive-specific model of threats.

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PETIoT: PEnetration Testing the Internet of Things

Attackers may attempt exploiting Internet of Things (IoT) devices to operate them unduly as well as to gather personal data of the legitimate device owners'. Vulnerability Assessment and Penetration Testing (VAPT) sessions help to verify the effectiveness of the adopted security measures. However, VAPT over IoT devices, namely VAPT targeted at IoT devices, is an open research challenge due to the variety of target technologies and to the creativity it may require. Therefore, this article aims at guiding penetration testers to conduct VAPT sessions over IoT devices by means of a new cyber Kill Chain (KC) termed PETIoT. Several practical applications of PETIoT confirm that it is general, while its main novelty lies in the combination of attack and defence steps. PETIoT is demonstrated on a relevant example, the best-selling IP camera on Amazon Italy, the TAPO C200 by TP-Link, assuming an attacker who sits on the same network as the device's in order to assess all the network interfaces of the device. Additional knowledge is generated in terms of three zero-day vulnerabilities found and practically exploited on the camera, one of these with High severity and the other two with Medium severity by the CVSS standard. These are camera Denial of Service (DoS), motion detection breach and video stream breach. The application of PETIoT culminates with the proof-of-concept of a home-made fix, based on an inexpensive Raspberry Pi 4 Model B device, for the last vulnerability. Ultimately, our responsible disclosure with the camera vendor led to the release of a firmware update that fixes all found vulnerabilities, confirming that PetIoT has valid impact in real-world scenarios.

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Evaluating the Fork-Awareness of Coverage-Guided Fuzzers

Fuzz testing (or fuzzing) is an effective technique used to find security vulnerabilities. It consists of feeding a software under test with malformed inputs, waiting for a weird system behaviour (often a crash of the system). Over the years, different approaches have been developed, and among the most popular lies the coverage-based one. It relies on the instrumentation of the system to generate inputs able to cover as much code as possible. The success of this approach is also due to its usability as fuzzing techniques research approaches that do not require (or only partial require) human interactions. Despite the efforts, devising a fully-automated fuzzer still seems to be a challenging task. Target systems may be very complex; they may integrate cryptographic primitives, compute and verify check-sums and employ forks to enhance the system security, achieve better performances or manage different connections at the same time. This paper introduces the fork-awareness property to express the fuzzer ability to manage systems using forks. This property is leveraged to evaluate 14 of the most widely coverage-guided fuzzers and highlight how current fuzzers are ineffective against systems using forks.

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Multi-service Threats: Attacking and Protecting Network Printers and VoIP Phones alike

Printing over a network and calling over VoIP technology are routine at present. This article investigates to what extent these services can be attacked using freeware in the real world if they are not configured securely. In finding out that attacks of high impact, termed the Printjack and Phonejack families, could be mounted at least from insiders, the article also observes that secure configurations do not appear to be widely adopted. Users with the necessary skills may put existing security measures in place with printers, but would need novel measures, which the article prototypes, with phones in order for a pair of peers to call each other securely and without trusting anyone else, including sysadmins.

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