Information Leakage Attacks and Countermeasures

The scientific community has been consistently working on the pervasive problem of information leakage, uncovering numerous attack vectors, and proposing various countermeasures. Despite these efforts, leakage incidents remain prevalent, as the complexity of systems and protocols increases, and sophisticated modeling methods become more accessible to adversaries. This work studies how information leakages manifest in and impact interconnected systems and their users. We first focus on online communications and investigate leakages in the Transport Layer Security protocol (TLS). Using modern machine learning models, we show that an eavesdropping adversary can efficiently exploit meta-information (e.g., packet size) not protected by the TLS’ encryption to launch fingerprinting attacks at an unprecedented scale even under non-optimal conditions. We then turn our attention to ultrasonic communications, and discuss their security shortcomings and how adversaries could exploit them to compromise anonymity network users (even though they aim to offer a greater level of privacy compared to TLS). Following up on these, we delve into physical layer leakages that concern a wide array of (networked) systems such as servers, embedded nodes, Tor relays, and hardware cryptocurrency wallets. We revisit location-based side-channel attacks and develop an exploitation neural network. Our model demonstrates the capabilities of a modern adversary but also presents an inexpensive tool to be used by auditors for detecting such leakages early on during the development cycle. Subsequently, we investigate techniques that further minimize the impact of leakages found in production components. Our proposed system design distributes both the custody of secrets and the cryptographic operation execution across several components, thus making the exploitation of leaks difficult

Blockchain based AI-enabled Industry 4.0 CPS Protection against Advanced Persistent Threat

Industry 4.0 is all about doing things in a concurrent, secure, and fine-grained manner. IoT edge-sensors and their associated data play a predominant role in today\u27s industry ecosystem. Breaching data or forging source devices after injecting advanced persistent threats (APT) damages the industry owners\u27 money and loss of operators\u27 lives. The existing challenges include APT injection attacks targeting vulnerable edge devices, insecure data transportation, trust inconsistencies among stakeholders, incompliant data storing mechanisms, etc. Edge-servers often suffer because of their lightweight computation capacity to stamp out unauthorized data or instructions, which in essence, makes them exposed to attackers. When attackers target edge servers while transporting data using traditional PKI-rendered trusts, consortium blockchain (CBC) offers proven techniques to transfer and maintain those sensitive data securely. With the recent improvement of edge machine learning, edge devices can filter malicious data at their end which largely motivates us to institute a Blockchain and AI aligned APT detection system. The unique contributions of the paper include efficient APT detection at the edge and transparent recording of the detection history in an immutable blockchain ledger. In line with that, the certificateless data transfer mechanism boost trust among collaborators and ensure an economical and sustainable mechanism after eliminating existing certificate authority. Finally, the edge-compliant storage technique facilitates efficient predictive maintenance. The respective experimental outcomes reveal that the proposed technique outperforms the other competing systems and models

Blockchain-enabled cybersecurity provision for scalable heterogeneous network: A comprehensive survey

Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance, transportation, healthcare, education, and supply chain management. Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges. However, the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes. There is the biggest challenge of data integrity and scalability, including significant computing complexity and inapplicable latency on regional network diversity, operating system diversity, bandwidth diversity, node diversity, etc., for decision-making of data transactions across blockchain-based heterogeneous networks. Data security and privacy have also become the main concerns across the heterogeneous network to build smart IoT ecosystems. To address these issues, today’s researchers have explored the potential solutions of the capability of heterogeneous network devices to perform data transactions where the system stimulates their integration reliably and securely with blockchain. The key goal of this paper is to conduct a state-of-the-art and comprehensive survey on cybersecurity enhancement using blockchain in the heterogeneous network. This paper proposes a full-fledged taxonomy to identify the main obstacles, research gaps, future research directions, effective solutions, and most relevant blockchain-enabled cybersecurity systems. In addition, Blockchain based heterogeneous network framework with cybersecurity is proposed in this paper to meet the goal of maintaining optimal performance data transactions among organizations. Overall, this paper provides an in-depth description based on the critical analysis to overcome the existing work gaps for future research where it presents a potential cybersecurity design with key requirements of blockchain across a heterogeneous network

Fog Computing

Everything that is not a computer, in the traditional sense, is being connected to the Internet. These devices are also referred to as the Internet of Things and they are pressuring the current network infrastructure. Not all devices are intensive data producers and part of them can be used beyond their original intent by sharing their computational resources. The combination of those two factors can be used either to perform insight over the data closer where is originated or extend into new services by making available computational resources, but not exclusively, at the edge of the network. Fog computing is a new computational paradigm that provides those devices a new form of cloud at a closer distance where IoT and other devices with connectivity capabilities can offload computation. In this dissertation, we have explored the fog computing paradigm, and also comparing with other paradigms, namely cloud, and edge computing. Then, we propose a novel architecture that can be used to form or be part of this new paradigm. The implementation was tested on two types of applications. The first application had the main objective of demonstrating the correctness of the implementation while the other application, had the goal of validating the characteristics of fog computing.Tudo o que não é um computador, no sentido tradicional, está sendo conectado à Internet. Esses dispositivos também são chamados de Internet das Coisas e estão pressionando a infraestrutura de rede atual. Nem todos os dispositivos são produtores intensivos de dados e parte deles pode ser usada além de sua intenção original, compartilhando seus recursos computacionais. A combinação desses dois fatores pode ser usada para realizar processamento dos dados mais próximos de onde são originados ou estender para a criação de novos serviços, disponibilizando recursos computacionais periféricos à rede. Fog computing é um novo paradigma computacional que fornece a esses dispositivos uma nova forma de nuvem a uma distância mais próxima, onde “Things” e outros dispositivos com recursos de conectividade possam delegar processamento. Nesta dissertação, exploramos fog computing e também comparamos com outros paradigmas, nomeadamente cloud e edge computing. Em seguida, propomos uma nova arquitetura que pode ser usada para formar ou fazer parte desse novo paradigma. A implementação foi testada em dois tipos de aplicativos. A primeira aplicação teve o objetivo principal de demonstrar a correção da implementação, enquanto a outra aplicação, teve como objetivo validar as características de fog computing

Advances in Information Security and Privacy

With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue

Tackling the Challenges of Information Security Incident Reporting: A Decentralized Approach

Information security incident under-reporting is unambiguously a business problem, as identified by a variety of sources, such as ENISA (2012), Symantec (2016), Newman (2018) and more. This research project identified the underlying issues that cause this problem and proposed a solution, in the form of an innovative artefact, which confronts a number of these issues. This research project was conducted according to the requirements of the Design Science Research Methodology (DSRM) by Peffers et al (2007). The research question set at the beginning of this research project, probed the feasible formation of an incident reporting solution, which would increase the motivational level of users towards the reporting of incidents, by utilizing the positive features offered by existing solutions, on one hand, but also by providing added value to the users, on the other. The comprehensive literature review chapter set the stage, and identified the reasons for incident underreporting, while also evaluating the existing solutions and determining their advantages and disadvantages. The objectives of the proposed artefact were then set, and the artefact was designed and developed. The output of this development endeavour is “IRDA”, the first decentralized incident reporting application (DApp), built on “Quorum”, a permissioned blockchain implementation of Ethereum. Its effectiveness was demonstrated, when six organizations accepted to use the developed artefact and performed a series of pre-defined actions, in order to confirm the platform’s intended functionality. The platform was also evaluated using Venable et al’s (2012) evaluation framework for DSR projects. This research project contributes to knowledge in various ways. It investigates blockchain and incident reporting, two domains which have not been extensively examined and the available literature is rather limited. Furthermore, it also identifies, compares, and evaluates the conventional, reporting platforms, available, up to date. In line with previous findings (e.g Humphrey, 2017), it also confirms the lack of standard taxonomies for information security incidents. This work also contributes by creating a functional, practical artefact in the blockchain domain, a domain where, according to Taylor et al (2019), most studies are either experimental proposals, or theoretical concepts, with limited practicality in solving real-world problems. Through the evaluation activity, and by conducting a series of non-parametric significance tests, it also suggests that IRDA can potentially increase the motivational level of users towards the reporting of incidents. This thesis describes an original attempt in utilizing the newly emergent blockchain technology, and its inherent characteristics, for addressing those concerns which actively contribute to the business problem. To the best of the researcher’s knowledge, there is currently no other solution offering similar benefits to users/organizations for incident reporting purposes. Through the accomplishment of this project’s pre-set objectives, the developed artefact provides a positive answer to the research question. The artefact, featuring increased anonymity, availability, immutability and transparency levels, as well as an overall lower cost, has the potential to increase the motivational level of organizations towards the reporting of incidents, thus improving the currently dismaying statistics of incident under-reporting. The structure of this document follows the flow of activities described in the DSRM by Peffers et al (2007), while also borrowing some elements out of the nominal structure of an empirical research process, including the literature review chapter, the description of the selected research methodology, as well as the “discussion and conclusion” chapter