Lampis Alevizos, Mahmoud Hashem Eiza, Vinh‐Thong Ta, Qi Shi · 5 authors
In a world where organisations are embracing new IT working models such as Bring Your Own Device (BYOD) and remote working, the traditional mindset of defending the network perimeter is no longer sufficient. Zero Trust Architecture (ZTA) has recently emerged as a new security model in which the breach mindset dominates the threat model. By default, the ZTA considers any endpoint (i.e., device), user, or application to be untrusted until proven otherwise. Nonetheless, once proven by the endpoint, using Advanced Persistent Threats (APT), attackers can still take over an authenticated and authorised session via that endpoint. Therefore, they can perform several user/device centric malicious activities in addition to lateral movement rendering the endpoint as the Achilles heel of ZTA. To effectively deter APT attack capabilities on the endpoints, this work proposes a Blockchain-enabled Intrusion Detection and Prevention System (BIDPS) that augments ZTA onto endpoints. The BIDPS aims to achieve two core outcomes: first, detect and prevent attackers’ techniques and tactics as per MITRE’s ATT&CK enterprise matrix earlier than the lateral movement stage, and secondly, strip trust out of the endpoint itself and place it on-chain, thus creating an immutable system of explicit trust. To evaluate the effectiveness of the BIDPS, a testbed was built where techniques of over ten APTs attacks were launched against the endpoint. BIDPS has proven a high rate of success defending against the launched attacks owing to its Blockchain’s immutability, fortifying the detection/prevention processes.
Due to the monetary value of Bitcoin, the most influential digital cryptocurrency in the world, Bitcoin has naturally become a valuable target of attacks, resulting in the emergence of many attack strategies on it. Among those attack strategies, selfish mining and block withholding attacks are two typical ones and attackers can obtain higher revenues under certain conditions than with an honest mining strategy. However, the combination of them will be a new type and more serious attack, which has not been analyzed in depth. In this paper, we propose GenSelfHolding, a general combined attack model with one selfish mining pool and random multiple honest pools on Bitcoin. Based on Markov chain, a general state transition graph and a general state distribution probability are presented to describe the internal features of our model. A general principle is then provided to calculate the attacker’s revenue. In addition, we give a detailed proof of the unique stable distribution of state transition probabilities. Such proof is an essential prerequisite for us to further present stable attacker revenue expressions under two specific scenarios, the GenSelfHolding model with two/three honest mining pools. Simulation results validate that the revenues of the attacker in these two specific models can reach up to 40% higher than those of classic selfish attackers in some cases.
Antonio Cabrera, Encarnación Castillo, Antonio Escobar-Molero, José Antonio Álvarez Bermejo · 6 authors
Hardware Security Modules (HSM) serve as a hardware based root of trust that offers physical protection while adding a new security layer in the system architecture. When combined with decentralized access technologies as Blockchain, HSM offers robustness and complete reliability enabling secured end-to-end mechanisms for authenticity, authorization and integrity. This work proposes an efficient integration of HSM and Blockchain technologies focusing on, mainly, public-key cryptography algorithms and standards, that result crucial in order to achieve a successful combination of the mentioned technologies to improve the overall security in Industrial IoT systems. To prove the suitability of the proposal and the interaction of an IoT node and a Blockchain network using HSM a proof of concept is developed. Results of time performance analysis of the prototype reveal how promising the combination of HSMs in Blockchain environments is.
Open access
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
Ibrahim Aliyu, Sélinde van Engelenburg, Muhammed Bashir Mu’azu, Jinsul Kim · 5 authors
The internet-of-Vehicle (IoV) can facilitate seamless connectivity between connected vehicles (CV), autonomous vehicles (AV), and other IoV entities. Intrusion Detection Systems (IDSs) for IoV networks can rely on machine learning (ML) to protect the in-vehicle network from cyber-attacks. Blockchain-based Federated Forests (BFFs) could be used to train ML models based on data from IoV entities while protecting the confidentiality of the data and reducing the risks of tampering with the data. However, ML models created this way are still vulnerable to evasion, poisoning, and exploratory attacks using adversarial examples. This paper investigates the impact of various possible adversarial examples on the BFF-IDS. We proposed integrating a statistical detector to detect and extract unknown adversarial samples. By including the unknown detected samples into the dataset of the detector, we augment the BFF-IDS with an additional model to detect original known attacks and the new adversarial inputs. The statistical adversarial detector confidently detected adversarial examples at the sample size of 50 and 100 input samples. Furthermore, the augmented BFF-IDS (BFF-IDS(AUG)) successfully mitigates the adversarial examples with more than 96% accuracy. With this approach, the model will continue to be augmented in a sandbox whenever an adversarial sample is detected and subsequently adopt the BFF-IDS(AUG) as the active security model. Consequently, the proposed integration of the statistical adversarial detector and the subsequent augmentation of the BFF-IDS with detected adversarial samples provides a sustainable security framework against adversarial examples and other unknown attacks.
The emergence of the Internet of Things (IoT) technology has caused a powerful transition in the cyber threat landscape. As a result, organisations have had to find new ways to better manage the risks associated with their infrastructure. In response, a significant amount of research has focused on developing efficient Cyber Threat Intelligence (CTI) sharing platforms. However, most existing solutions are highly centralised and do not provide a way to exchange information in a distributed way. In this chapter, we subsequently seek to evaluate how blockchain technology can be used to address a number of limitations present in existing CTI sharing platforms. To determine the role of blockchain-based sharing moving forward, we present a number of general CTI sharing challenges, and discuss how blockchain can bring opportunities to address these challenges in a secure and efficient manner. Finally, we discuss a list of relevant works and note some unique future research questions.
Syed Muhammad Sajjad, Muhammad Rafiq Mufti, Muhammad Yousaf, Waqar Aslam · 9 authors
DDoS (distributed denial of service) attacks have drastically effected the functioning of Internet‐based services in recent years. Following the release of the Mirai botnet source code on GitHub, the scope of these exploitations has grown. The attackers have been able to construct and launch variations of the Mirai botnet thanks to the open‐sourcing of the Mirai code. These variants make the signature‐based detection of these attacks challenging. Moreover, DDoS attacks are typically detected and mitigated reactively, making DDoS mitigation solutions very expensive. This paper presents a proactive IoT botnet detection system that detects the anomalies in the behavior of the IoT device and mitigates the DDoS botnet exploitation at the source end, which makes our proposal a low‐cost solution. Further, this paper uses a collaborative trust relationship‐based threat intelligence‐sharing mechanism to prevent other IoT devices from being compromised by the detected botnet. The researchers have evaluated the collaborative threat intelligence sharing mechanism using Ethereum Virtual Machine and Hyperledger. The performance of our proposed system can detect 97% of the Mirai botnet attack activities. Furthermore, our collaborative threat intelligence sharing mechanism based on the Ethereum Virtual Machine showed more scalability.
Leonardo Alt, Martin Blicha, Antti E. J. Hyvärinen, Natasha Sharygina
Abstract Formally verifying smart contracts is important due to their immutable nature, usual open source licenses, and high financial incentives for exploits. Since 2019 the Ethereum Foundation’s Solidity compiler ships with a model checker. The checker, called SolCMC, has two different reasoning engines and tracks closely the development of the Solidity language. We describe SolCMC’s architecture and use from the perspective of developers of both smart contracts and tools for software verification, and show how to analyze nontrivial properties of real life contracts in a fully automated manner.
Abstract With the rapid development of the blockchain, smart contract technology has been widely applied. The number of smart contracts has grown at a high rate and nearly at an average of thousands per day. However, the correctness and security of the smart contract itself are facing huge problems. The well-known DAO vulnerability, and Parity multi-signature wallet’ vulnerabilities have leaded to a hundreds of millions dollars loss, and they are both caused by the security problems of smart contracts. Once the smart contract vulnerability is exploited, it is very likely to bring the loss of cryptocurrencies, the disorder of the financial order and other catastrophic consequences. Therefore the security of smart contracts is imminent. This project has designed and implemented a vulnerability detection system of Ethereum smart contract. The system uses the assembly instruction sequences of the smart contract to generate the control flow graph, then performs symbolic execution and vulnerability constraint solving over the control flow. The system can detect some common types of vulnerabilities, such as the integer overflow and underflow vulnerability, reentry vulnerability and unchecked call return value vulnerability. It has a high accuracy of detection result, and gives support for export vulnerability report.
With the proliferation of the blockchain technology ecosystems such as mining pools, crypto exchanges, full Bitcoin nodes, wallets, and pool protocol servers in recent years, the denial of service (DoS) attack vector has become more prevalent, and the attacks are targeted to the peer-to-peer networks and blockchain users. Despite blockchain enhancing security with decentralized design, secured distributed storage, and privacy, it is still vulnerable to new attack threats. If an attempted DoS is successful on blockchain, the impact is most likely massive given the fact that it is predominantly used for finance applications. An extensive account of the current state-of-the-art for possible DoS and corresponding mitigation techniques is not discussed in the existing research. This paper analyzes and categorizes the existing state-of-the-art DoS attack methods, detection techniques, and mitigation solutions targeting blockchain peer-to-peer networks as well as conventional network crypto exchanges. The review of the prior research shows that the blockchain ecosystem can be a target to successfully perform DoS attacks in the future, and technological advancements in blockchain are needed to mitigate potential attacks.
Dor Bitan, Ran Canetti, Shafi Goldwasser, Rebecca Wexler
The use of hidden investigative software to collect evidence of crimes presents courts with a recurring dilemma: On the one hand, there is often clear public interest in keeping the software hidden to preserve its effectiveness in fighting crimes. On the other hand, criminal defendants have rights to inspect and challenge the full evidence against them, including law enforcement's investigative methods. In fact, in the U.S. adversarial legal system, the defendant's rights to scrutinize the government's tools are crucial to the truth-seeking process and to keeping law enforcement conduct lawful and constitutional. Presently, courts balance these conflicting interests on a case-by-case basis through evidentiary privilege law, often voicing their frustration with the challenging dilemma they face. We demonstrate how judicious use of a sophisticated cryptographic tool called Zero Knowledge Proofs (ZKPs) could help to mitigate this dilemma: Based on actual court cases where evidence was collected using a modified version of a peer-to-peer software, we demonstrate how law enforcement could, in these cases, augment their investigative software with a ZKP-based mechanism that would allow them to later provide full responses to challenges made by a defense expert -- and allow a defense expert to independently verify law enforcement claims -- while keeping the software hidden. We demonstrate the technical feasibility of our mechanism via a proof-of-concept implementation. We also propose legal analysis that justifies its use, discusses its merits, and considers the legal implications that the very existence of such a mechanism might have, even in cases where it has not been used. Our proof-of-concept may also extend to other verification dilemmas in the legal landscape.
Jacco O.G. Krijnen, Manuel M. T. Chakravarty, Gabriele Keller, Wouter Swierstra
Compiler correctness is an old problem, but with the emergence of smart contracts on blockchains that problem presents itself in a new light. Smart contracts are self-contained pieces of software that control (valuable) assets in an adversarial environment; once committed to the blockchain, these smart contracts cannot be modified. Smart contracts are typically developed in a high-level contract language and compiled to low-level virtual machine code before being committed to the blockchain. For a smart contract user to trust a given piece of low-level code on the blockchain, they must convince themselves that (a) they are in possession of the matching source code and (b) that the compiler has correctly translated the source code to the given low-level code. Classic approaches to compiler correctness tackle the second point. We argue that translation certification also squarely addresses the first. We describe the proof architecture of a translation certification framework and demonstrate how we can model the compilation pipeline as a sequence of translation relations. We give a detailed account of such relations for most passes of the Plutus Tx compiler, which we formalised in Coq. This approach facilitates a modular verification methodology and is robust in the face of an evolving compiler implementation.
In recent years, permisionless blockchains have received a lot of attention both from industry and academia, where substantial effort has been spent to develop consensus protocols that are secure under the assumption that less than half (or a third) of a given resource (e.g., stake or computing power) is controlled by corrupted parties. The security proofs of these consensus protocols usually assume the availability of a network functionality guaranteeing that a block sent by an honest party is received by all honest parties within some bounded time. To obtain an overall protocol that is secure under the same corruption assumption, it is therefore necessary to combine the consensus protocol with a network protocol that achieves this property under that assumption. In practice, however, the underlying network is typically implemented by flooding protocols that are not proven to be secure in the setting where a fraction of the considered total weight can be corrupted. This has led to many so-called eclipse attacks on existing protocols and tailor-made fixes against specific attacks. To close this apparent gap, we present the first practical flooding protocol that provably delivers sent messages to all honest parties after a logarithmic number of steps. We prove security in the setting where all parties are publicly assigned a positive weight and the adversary can corrupt parties accumulating up to a constant fraction of the total weight. This can directly be used in the proof-of-stake setting, but is not limited to it. To prove the security of our protocol, we combine known results about the diameter of Erdős–Rényi graphs with reductions between different types of random graphs. We further show that the efficiency of our protocol is asymptotically optimal. The practicality of our protocol is supported by extensive simulations for different numbers of parties, weight distributions, and corruption strategies. The simulations confirm our theoretical results and show that messages are delivered quickly regardless of the weight distribution, whereas protocols that are oblivious of the parties’ weights completely fail if the weights are unevenly distributed. Furthermore, the average message complexity per party of our protocol is within a small constant factor of such a protocol.