Remote attestation (RA) is emerging as a promising security mechanism that establishes trust in IoT devices by detecting the malware presence. Typically, RA consists of computing a hash over the device’s memory and is executed as anatomicprocedure to guarantee the reliability of the attestation evidence. However, in real-world situations, such as those involving real-time systems, energy-harvesting devices, or mission-critical operations, the IoT device may not be able to complete the attestation procedure due to various factors like task scheduling, limited battery life, or higher priority tasks. In such scenarios where flexibility, adaptability, and security are paramount, enablinginterruptibilityof RA is crucial. This paper presents a novel approach called ITERATOR which leverages hash-based storage to enable interruptible RA without any additional hardware requirements. Our proposal transforms the device attestation procedure from the traditional approach of memory hash computation to a lookup operation in a hash-based storage, namely, Cuckoo filter. The ITERATOR protocol divides the device’s memory into blocks associated with a Cuckoo filter bucket. This approach allows the device to perform RA in multiple rounds, ensuring secure interruptible attestation. We perform software simulations of ITERATOR, demonstrating its high effectiveness in detecting the malware presence. Due to its interruptible design, ITERATOR cannot guarantee 100% detection in a single attestation round; however, repeated rounds make long-term evasion by malware highly unlikely. In particular, the experiments showed that the probability of evading the detection ranges between 37% and less than 1%, depending on the protocol configuration. Moreover, we validate ITERATOR’s efficiency through two hardware proof-of-concept implementations that rely on ESP32 and FPGA platforms. The FPGA implementation shows the high efficiency of the protocol, with 34.3ns to attest a single memory block.

Graphical security models constitute a well-known, user-friendly way to represent the security of a system. These classes of models are used by security experts to identify vulnerabilities and assess the security of a system. The manual construction of these models can be tedious, especially for large enterprises. Consequently, the research community is trying to address this issue by proposing methods for the automatic generation of such models. In this work, we present a survey illustrating the current status of the automatic generation of two popular kinds of graphical security models: Attack Trees and Attack Graphs. The goal of this survey is to present the current methodologies used in the field, compare them, and present the challenges and future directions to the research community.

The Internet of Things (IoT) is evolving our society; however, the growing adoption of IoT devices in many scenarios brings security and privacy implications. Current security solutions are either unsuitable for every IoT scenario or provide only partial security. This paper presents AntibIoTic 2.0, a distributed security system that relies on Fog computing to secure IoT devices, including legacy ones. The system is composed of a backbone, made of core Fog nodes and Cloud server, a Fog node acting at the edge as the gateway of the IoT network, and a lightweight agent running on each IoT device. The proposed system offers fine-grained, host-level security coupled with network-level protection, while its distributed nature makes it scalable, versatile, lightweight, and easy to deploy, also for legacy IoT deployments. AntibIoTic 2.0 can also publish anonymized and aggregated data and statistics on the deployments it secures, to increase awareness and push cooperations in the area of IoT security. This manuscript recaps and largely expands previous works on AntibIoTic, providing an enhanced design of the system, an extended proof-of-concept that proves its feasibility and shows its operation, and an experimental evaluation that reports the low computational overhead it causes.

The Internet of Things (IoT) revolutionised the way devices, and human beings, cooperate and interact. The interconnectivity and mobility brought by IoT devices led to extremely variable networks, as well as unpredictable information flows. In turn, security proved to be a serious issue for the IoT, far more serious than it has been in the past for other technologies. We claim that IoT devices need detailed descriptions of their behaviour to achieve secure default configurations, sufficient security configurability, and self-configurability. In this article, we propose S×C4IoT, a framework that addresses these issues by combining two paradigms: Security by Contract (S×C) and Fog computing. First, we summarise the necessary background such as the basic S×C definitions. Then, we describe how devices interact within S×C4IoT and how our framework manages the dynamic evolution that naturally result from IoT devices life-cycles. Furthermore, we show that S×C4IoT can allow legacy S×C-noncompliant devices to participate with an S×C network, we illustrate two different integration approaches, and we show how they fit into S×C4IoT. Last, we implement the framework as a proof-of-concept. We show the feasibility of S×C4IoT and we run different experiments to evaluate its impact in terms of communication and storage space overhead.

Distributed real-time systems often rely on time-triggered communication and task execution to guarantee end-to-end latency and time-predictable computation. Such systems require a reliable synchronized network time to be shared among end-systems. The IEEE 1588 Precision Time Protocol (PTP) enables such clock synchronization throughout an Ethernet-based network. While security was not addressed in previous versions of the IEEE 1588 standard, in its most recent iteration (IEEE 1588-2019), several security mechanisms and recommendations were included describing different measures that can be taken to improve system security and safety. One proposal to improve security and reliability is to add redundancy to the network through modifications in the topology. However, this recommendation omits implementation details and leaves the question open of how it affects synchronization quality. This work investigates the quality impact and security properties of redundant PTP deployment and proposes an observation window-based multi-domain, PTP end-system, design to increase fault-tolerance and security. We implement the proposed design inside a discrete-event network simulator and evaluate its clock synchronization quality using two test-case network topologies with simulated faults.

Internet of Things (IoT) devices have enveloped our surroundings and have been increasingly deployed in many domains. Even though the IoT has generated unprecedented opportunities, the poorly secured design of IoT devices makes them an easy target for cyber attacks. Aimed at securing IoT devices, Remote Attestation (RA) is a security technique that identifies threat presence in IoT systems. Typically, RA is an atomic procedure that requires uninterrupted connectivity to execute. However, in energy harvesting context where intermittent IoT devices go into sleep mode immediately after regular operations, the atomic property is difficult to achieve. In this paper, we propose RESERVE, a novel lightweight RA protocol designed specifically for Intermittent IoT devices. RESERVE aims to improve the security of intermittent systems by detecting malware presence during online mode and guaranteeing with some probability software legitimacy during offline mode. In particular, RESERVE ensures trustworthiness by organizing the device's software into modules, and after regular operation each device attests as many modules as fit in its energy budget.

With the widespread use of smartphones and wearable health sensors, a plethora of mobile health (mHealth) applications to track well-being, run human behavioral studies, and clinical trials have emerged in recent years. However, the design, development, and deployment of mHealth applications is challenging in many ways. To address these challenges, several generic mobile sensing frameworks have been researched in the past decade. Such frameworks assist developers and researchers in reducing the complexity, time, and cost required to build and deploy health-sensing applications. The main goal of this article is to provide the reader with an overview of the state-of-the-art of health-focused generic mobile and wearable sensing frameworks. This review gives a detailed analysis of functional and non-functional features of existing frameworks, the health studies they were used in, and the stakeholders they support. Additionally, we also analyze the historical evolution, uptake, and maintenance after the initial release. Based on this analysis, we suggest new features and opportunities for future generic mHealth sensing frameworks.

An increasing interest is growing around the idea of microservices and the promise of improving scalability when compared to monolithic systems. Several companies are evaluating pros and cons of a complex migration. In particular, financial institutions are positioned in a difficult situation due to the economic climate and the appearance of agile competitors that can navigate in a more flexible legal framework and started their business since day one with more agile architectures and without being bounded to outdated technological standard. In this paper, we present a real world case study in order to demonstrate how scalability is positively affected by re-implementing a monolithic architecture (MA) into a microservices architecture (MSA). The case study is based on theFX Coresystem, a mission critical system of Danske Bank, the largest bank in Denmark and one of the leading financial institutions in Northern Europe. The technical problem that has been addressed and solved in this paper is the identification of a repeatable migration process that can be used to convert a real world Monolithic architecture into a Microservices architecture in the specific setting of financial domain, typically characterized by legacy systems and batch-based processing on heterogeneous data sources.

Summary Disbursement registration has always been a cumbersome, opaque, and inefficient process, up to the point that most businesses perform cash‐flow evaluations only on a quarterly basis. We believe that automatic cash‐flow evaluations can actively mitigate these issues. In this paper, we present BitFlow, a blockchain‐based architecture that provides complete cash‐flow transparency and diminishes the probability of undetected frauds through the BitKrone, a non‐volatile cryptocurrency that maps to the Danish Krone (DKK). We show that confidentiality can be effectively achieved on a permissionless blockchain using Zero‐Knowledge proofs, ensuring verifiable transfers and automatic evaluations. Furthermore, we discuss several experiments to evaluate our proposal, in particular, the impact that confidential transactions have on the whole system, in terms of responsiveness and from an economical expenditure perspective.

The Internet of Things (IoT) has been one of the key disruptive technologies over the last few years, with its promise of optimizing and automating current manual tasks and evolving existing services. From the security perspective, the increasing adoption of IoT devices in all aspects of our society has exposed businesses and consumers to a number of threats, such as Distributed Denial of Service (DDoS) attacks. To tackle this IoT security problem, we proposed AntibIoTic 1.0 [1]. However, this solution has some limitations that make it difficult (when not impossible) to be implemented in a legal and controlled manner. Along the way, Fog computing was born: a novel paradigm that aims at bridging the gap between IoT and Cloud computing, providing a number of benefits, including security. As a result, in this paper, we present AntibIoTic 2.0, an anti-malware that relies upon Fog computing to secure IoT devices and to overcome the main issues of its predecessor (AntibIoTic 1.0). First, we present AntibIoTic 1.0 and its main problem. Then, after introducing Fog computing, we present AntibIoTic 2.0, showing how it overcomes the main issues of its predecessor by including Fog computing in its design.

The rise of connectivity, digitalization, robotics, and artificial intelligence (AI) is rapidly changing our society and shaping its future development. During this technological and societal revolution, security has been persistently neglected, yet a hacked robot can act as an insider threat in organizations, industries, public spaces, and private homes. In this paper, we perform a structured security assessment of Pepper, a commercial humanoid robot. Our analysis, composed by an automated and a manual part, points out a relevant number of security flaws that can be used to take over and command the robot. Furthermore, we suggest how these issues could be fixed, thus, avoided in the future. The very final aim of this work is to push the rise of the security level of IoT products before they are sold on the public market.

Android smartphones have become a vital component of the daily routine of millions of people, running a plethora of applications available in the official and alternative marketplaces. Although there are many security mechanisms to scan and filter malicious applications, malware is still able to reach the devices of many end-users. In this paper, we introduce the SafeDroid v2.0 framework, that is a flexible, robust, and versatile open-source solution for statically analysing Android applications, based on machine learning techniques. The main goal of our work, besides the automated production of fully sufficient prediction and classification models in terms of maximum accuracy scores and minimum negative errors, is to offer an out-of-the-box framework that can be employed by the Android security researchers to efficiently experiment to find effective solutions: the SafeDroid v2.0 framework makes it possible to test many different combinations of machine learning classifiers, with a high degree of freedom and flexibility in the choice of features to consider, such as dataset balance and dataset selection. The framework also provides a server, for generating experiment reports, and an Android application, for the verification of the produced models in real-life scenarios. An extensive campaign of experiments is also presented to show how it is possible to efficiently find competitive solutions: the results of our experiments confirm that SafeDroid v2.0 can reach very good performances, even with highly unbalanced dataset inputs and always with a very limited overhead.

The Internet of Things (IoT) revolution has not only carried the astonishing promise to interconnect a whole generation of traditionally “dumb” devices, but also brought to the Internet the menace of billions of badly protected and easily hackable objects. Not surprisingly, this sudden flooding of fresh and insecure devices fueled older threats, such as Distributed Denial of Service (DDoS) attacks. In this paper, we first propose an updated and comprehensive taxonomy of DDoS attacks, together with a number of examples on how this classification maps to real-world attacks. Then, we outline the current situation of DDoS-enabled malwares in IoT networks, highlighting how recent data support our concerns about the growing in popularity of these malwares. Finally, we give a detailed analysis of the general framework and the operating principles of Mirai, the most disruptive DDoS-capable IoT malware seen so far.

The Internet of Things (IoT) revolution promises to make our lives easier by providing cheap and always connected smart embedded devices, which can interact on the Internet and create added values for human needs.But all that glitters is not gold.Indeed, the other side of the coin is that, from a security perspective, this IoT revolution represents a potential disaster.This plethora of IoT devices that flooded the market were very badly protected, thus an easy prey for several families of malwares that can enslave and incorporate them in very large botnets.This, eventually, brought back to the top Distributed Denial of Service (DDoS) attacks, making them more powerful and easier to achieve than ever.This paper aims at provide an up-to-date picture of DDoS attacks in the specific subject of the IoT, studying how these attacks work and considering the most common families in the IoT context, in terms of their nature and evolution through the years.It also explores the additional offensive capabilities that this arsenal of IoT malwares has available, to mine the security of Internet users and systems.We think that this up-to-date picture will be a valuable reference to the scientific community in order to take a first crucial step to tackle this urgent security issue.

Fault-tolerant event detection is fundamental to wireless sensor network applications. Existing approaches usually adopt neighborhood collaboration for better detection accuracy, while need more energy consumption due to communication. Focusing on energy efficiency, this paper makes an improvement to a hybrid algorithm for dynamic event region detection, such as real-time tracking of chemical leakage regions. Considering the characteristics of the moving away dynamic events, we propose a return back condition for the hybrid algorithm from distributed neighborhood collaboration, in which a node makes its detection decision based on decisions received from its spatial and temporal neighbors, to local non-communicative decision making. The simulation results demonstrate that the improved algorithm does not degrade the detection accuracy of the original algorithm, while it has better energy efficiency with the number of messages exchanged in the network decreased.

Auction mechanisms are nowadays widely used in electronic commerce Web sites for buying and selling items among different users. The increasing importance of auction protocols in the negotiation phase is not limited to online marketplaces. In fact, the wide applicability of auctions as resource‐allocation and negotiation mechanisms have also led to a great deal of interest in auctions within the agent community. A challenging issue for agents operating in open Multiagent Systems (such as the emerging semantic Web infrastructure) concerns the specification of declarative communication rules which could be published and shared allowing agents to dynamically engage well‐known and trusted negotiation protocols. To cope with real‐world applications, these rules should also specify fault tolerant patterns of interaction, enabling negotiating agents to interact with each other tolerating failures, for instance terminating an auction process even if some bidding agents dynamically crash. In this paper, we propose an approach to specify fault tolerant auction protocols in open and dynamic environments by means of communication rules dealing with crash failures of agents. We illustrate these concepts considering a case study about the specification of an English Auction protocol which tolerate crashes of bidding agents and we discuss its properties.

Security-by-Contract (S×C) is a paradigm providing security assurances for mobile applications. In this work, we present an extension of S×C enriched with an automatic trust management infrastructure. Indeed, we enhance the already existing architecture by adding new modules and configurations for contracts managing. At deploy-time, our system decides the run-time configuration depending on the credentials of contract provider. Roughly, the run-time environment can both enforce a security policy and monitor the declared contract. According to the actual behaviour of the running program our architecture updates the trust level associated with the contract provider. The main advantage of this method is an automatic management of the level of trust of software and contract releasers.

The security-by-contract (SxC) framework has been recently proposed to address the trust relationship problem of the current security model adopted for mobile devices. The key idea of SxC (similar to the one of model-carrying code) is to augment mobile code with a claim on its security behavior (a contract,) that could be matched against a mobile platform policy before downloading the code. The rational is that, thanks to SxC, a digital signature does not just certify the origin of the code but also bind together the code with a contract. In this paper we address one of the key issue of the SxC paradigm, namely the contract-policy matching problem, proposing a prototype for matching policies with security claims of mobile applications. This result can be considered a key step towards the achievement of the SxC main goal: provide a semantics for digital signatures on mobile code, thus being a step in the transition from trusted code to trustworthy code.