Blockchain Papers

Francisco Assis Moreira do Nascimento, Fabiano Hessel

No abstract is available for this record.

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.

Darshi Patel, Dhiren B. Patel, Dhiren B. Patel, Dhiren B. Patel

No abstract is available for this record.

Valeh Farzaliyev, Jan Willemson, Jaan Kristjan Kaasik

Abstract Mix‐networks were first proposed by Chaum in the late 1970s–early 1980s as a general tool for building anonymous communication systems. Classical mix‐net implementations rely on standard public key primitives (e.g., ElGamal encryption) that will become vulnerable when a sufficiently powerful quantum computer will be built. Thus, there is a need to develop quantum‐resistant mix‐nets. This article focuses on the application case of electronic voting where the number of votes to be mixed may reach hundreds of thousands or even millions. We propose an improved architecture for lattice‐based post‐quantum mix‐nets featuring more efficient zero‐knowledge proofs while maintaining established security assumptions. Our current implementation scales up to 100,000 votes, still leaving a lot of room for future optimisation.

Reza Soltani, Lovina Saxena, Rohit Joshi, Srinivas Sampalli

Routing in wireless sensor networks (WSNs) are based on multi-hop communication in which the messages pass through multiple sensor nodes, and hence routing algorithms must rely on trust relationships between neighboring nodes. The open access nature of WSNs leads to the possibility of nodes becoming compromised and consequently being turned into malicious objects. One such attack on WSNs is the Sybil attack, in which an attacker can take control of a legitimate node or enter a malicious node into the network and create fake identities. Consequently, they can change the behavior of the WSN, such as its routing schema to cause loops or wrong directions to manipulate data and consume the energy of the network, or even target cluster heads. In this paper, we present a novel technique based on IOTA Tangle, a distributed ledger technology, for the detection and prevention of Sybil attacks by protecting routing data. A transaction history on IOTA is maintained for detecting malicious node injection, and IOTA currency is used as a reputation score to prevent malicious nodes and protect the routing table. Even if an attacker gains access to the network, all routing data can be tracked in IOTA Tangle that will alert the base station about this attack. The technique has been simulated and evaluated using a proof-of-concept prototype.

T.L. Kayathri, N. Kumaresan, R. Vijayabhasker

The Border Gateway Protocol (BGP) helps to exchange the information over the internet. However, BGP is susceptible to malicious attacks and misconfigurations meanwhile BGP does not focus on providing security during routing information advertisement. The secure BGP environment provides constant routing services on the internet, but existing works does not provide an optimal solution for BGP router security. To overcome these issues, we proposed decentralized low complexity framework for providing security to BGP attacks using deep learning and blockchain technologies. The proposed SDBGPChain (SDN based BGP using dendrimer tree blockchain) model whereas the SDN provides network management, flexibility and scalability for BGP environment, the proposed work includes three processes such as entity authentication, low complexity BGP attack detection and prevention, and deep learning-based route update validation. Initially, users and BGP routers are authenticated using Enhanced Blowfish and Elliptical Curve Cryptography (EB-ECC) which generated the unique key using EB algorithm and the unique is encrypted by enhanced ECC for improving security. Every Autonomous System (AS) is constructed as a graph structure using Directed Acyclic Graph (DAG) which improves the scalability and interoperability of the network. Secondly, we perform BGP attack detection using Dual Agent based Twin Actor Twin Delayed Deep Deterministic Policy Gradient (DA-T2TD3) algorithm by performing both proactive and reactive methods. Finally, we perform route update validation by Gated Recurrent Unit (GRU) by considering update message tuples which validate the updates by identifying misconfigurations and errors in the updated messages. Here, updated messages are passed to the blockchain for validation using the DiemBFT consensus algorithm which improves high security. The simulation of the proposed SDBGPChain model is conducted by OMNET++ simulation tool, and the performance of this work is evaluated based on various performance metrics which proved that the proposed work achieved superior performance compared to state-of-the-art works.

Jiale Yang, Guozi Sun, Rongyu Xiao, Hansen He

As the most successful cryptocurrency, bitcoin has become the primary target of attackers. The security risks existing in bitcoin network (P2P networks) may pose serious threats to itself. It has been proved that network attackers of the autonomous system level could isolate a specific set of bitcoin nodes using prefix hijacking attacks; since this attack achieves bitcoin partition by deleting all data packets of the victim node, it is easy to be discovered by the victim node, and cannot maintain a long‐term connection (the partition will disappear after canceling the BGP hijacking) (Apostolaki M et al. (2017)). This paper proposes a new attack scheme—eclipse attack method based on BGP hijacking (BHE). The attack can occupy the network connection of the victim node, and only need to delete part of the TCP handshaking packets of the victim node during the attack, and it makes the attack more hidden and can occupy the network connection of the victim node for a long time. The innovation of the BHE attack is that it can control the peering decision of the victim node by controlling the victim node’s internal peer database (new table and tried table) and preventing the victim node from establishing a good connection. It enables the attacker to occupy all network connections of the victim node and become its natural network middleman. We verify the feasibility of the BHE attack through experimental evaluation and demonstrate that an attacker who can launch BGP hijacking may occupy all connections of the victim node within 20 minutes (ignoring the time of traffic diversion). To reduce the attack’s impact, the paper provides some countermeasures that can use in practice according to the basic characteristics of the attack.

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.

Mayank Raikwar, Danilo Gligoroski

Denial of Service (DoS) attacks are a growing threat in network services. The frequency and intensity of DoS attacks are rapidly increasing day by day. The immense financial potential of the Cryptocurrency market is a prevalent target of the DoS attack. The DoS attack events are kept on happening in cryptocurrencies and the blockchain ecosystem. To the best of our knowledge, there has not been any study on the DoS attack on the blockchain ecosystem. In this paper, we identify ten entities in the blockchain ecosystem and we scrutinize the DoS attacks on them. We also present the DoS mitigation techniques applicable to the blockchain services. Additionally, we propose a DoS mitigation technique by the use of verifiable delay function (VDF).

Ke Ye, Meng Shen, Zhenbo Gao, Liehuang Zhu

No abstract is available for this record.

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.

Richard Plný, Karel Hynek, Tomáš Čejka

No abstract is available for this record.

VILMA MATTILA, PRATIK GAURI, PRATEEK DWIVEDI, DHANRAJ DADHICH · 5 authors

With the growing interest in blockchain in both academic research and industry, the security and privacy of blockchains have attracted huge interest, even though only a small part of the blockchain platforms can achieve the set of abovementioned security goals in practice. Leveraging from the state-of-the-art security paradigms, we propose 5irechain protective covering which has the ability to continuously identify, map, scan, assess, and grade the risk portfolio of all the assets, vendors, and acquisitions of a company giving a hackers perspective to the company. The dashboard gives visibility of not just only the web2 infrastructure in place, but also covers the web3 space and allows 5ire to monitor all of its nodes and their activities including historical data, tracking large wallets, monitoring bot activity, detecting transaction stats and volume along with the ability to block possible large scale attacks.

Arzu Özkan, Umutcan Korkmaz, Cemal Dak, Enis Karaarslan

Disaster and emergency management are under the responsibility of many organizations and there are serious coordination problems in post-disaster crisis management. This paper proposes a decentralized non-governmental organization resource management system for disasters (NGO-RMSD / STK-AKYS). This system is based on blockchain technology and it will enable the non-governmental organizations (NGO) and public institutions to manage and coordinate the resources in a trusted environment in the case of disasters. A proof of concept implementation is developed by using the Quorum blockchain framework which is more energy-efficient than crypto currency-based blockchain solutions. Smart contracts are developed for the autonomous working of the system. These smart contacts are used for the verification of the needs of the one who is in need, delivering resources to the right people, and identifying the urgent needs. The system aims to reach more disaster victims in a more timely manner. NGO-RMSD is designed according to the needs of the NGOs in the field. The application is shared with the free software license and further development with the community is aimed.

Surya Bhushan Kumar, Ranjan Kumar Mandal, Kuntal Mukherjee, Rajiv Kumar Dwivedi

No abstract is available for this record.

Zhuoming Gu, Dan Lin, Jiajing Wu

No abstract is available for this record.

Wilson S. Melo, Lucas S. Dos Santos, Lucila M. S. Bento, Paulo R. Nascimento · 6 authors

The monitoring and protection of critical infrastructures, especially the ones involving physical assets (e.g., dams, nuclear energy facilities, governmental buildings), constitute a challenging problem. The failure and collapse of these infrastructures can cause untold consequences. Recent works have proposed blockchains as a tool to improve monitoring systems in different critical infrastructures. However, most previous works lack on presenting a more in-depth discussion about how to implement these solutions. In this paper, we develop a practical approach. We propose a comprehensive framework that describes how to implement a blockchain-based system to monitor and protect critical infrastructures. We implement our framework in two distinct blockchain platforms: Ethereum and Hyperledger Fabric. We compare both implementations and discuss their differences in terms of performance, easiness of development, security, privacy, complexity, and costs. We believe that our results can be valuable for professionals interested in applying blockchain-based solutions to protect critical infrastructures.

Sathish Kumar, Norman Ahmed, Anastasios N. Bikos

No abstract is available for this record.

Aulia Arif Wardana, Grzegorz Kołaczek, Parman Sukarno

No abstract is available for this record.

Jie Cai, Bin Li, Jiale Zhang, Xiaobing Sun · 5 authors

Smart contract security has drawn extensive attention in recent years because of the enormous economic losses caused by vulnerabilities. Even worse, fixing bugs in a deployed smart contract is difficult, so developers must detect security vulnerabilities in a smart contract before deployment. Existing smart contract vulnerability detection efforts heavily rely on fixed rules defined by experts, which are inefficient and inflexible.To overcome the limitations of existing vulnerability detection approaches, we propose a GNN based approach for smart contract vulnerability detection. First, we construct a graph representation for a smart contract function with syntactic and semantic features by combining abstract syntax tree (AST), control flow graph (CFG), and program dependency graph (PDG). To further strengthen the presentation ability of our approach, we perform program slicing to normalize the graph and eliminate the redundant information unrelated to vulnerabilities. Then, we use a Bidirectional Gated Graph Neural-Network model with hybrid attention pooling to identify potential vulnerabilities in smart contract functions.

Arkan Hammoodi Hasan Kabla, Mohammed Anbar, Selvakumar Manickam, Taief Alaa Al-Amiedy · 7 authors

Ethereum attracts more investors, researchers, and even scammers for many reasons; this is the first platform that enables the new Decentralized Applications (DApps) to run on top of the blockchain network. However, the rich semantics and applications of DApps inevitably introduce many security issues that have grabbed significant attention from industry and academics due to their destructive impact on DApps in recent years. Therefore, there is a vital need to study the applicability of Intrusion Detection System in detecting Ethereum-based attacks. Hence, this paper is among the first comprehensive review that studies the applicability of IDS in detecting Ethereum-based attacks. In addition, this paper lists all the potential attacks on Ethereum passing through the vulnerabilities that cause those attacks and ending with the consequences of each attack. Besides, this paper analyses all the IDS-based related works of Ethereum attacks detection since the Ethereum platform was launched in 2015. Finally, this paper discusses the open issues regarding vulnerabilities and attacks, challenges, and future directions.

Arkan Hammoodi Hasan Kabla, Mohammed Anbar, Selvakumar Manickam, Shankar Karupayah

Recently, the rapid flourish of blockchain technology in the financial field has attracted many cybercriminals’ attention to launch blockchain-based attacks such as Ponzi schemes, Scam wallets, and phishing scams. Currently, Ethereum is the most prominent blockchain-based platform and the first that supports smart contracts. However, the number of phishing scam accounts are reportedly more than 50% of all cybercrimes in Ethereum. In contrast, this paper proposes a detection mechanism called Ethereum Phishing Scam Detection (Eth-PSD) that attempts to detect phishing scam-related transactions using a novel machine learning-based approach. Eth-PSD tackles some of the limitations in the existing works, such as the use of imbalanced datasets, complex feature engineering, and lower detection accuracy. We also investigated the aspects of constructing a new updated and balanced dataset that can be used for evaluating Eth-PSD effectively. Our experimental results indicate that Eth-PSD could efficiently detect the phishing scam on Ethereum with a detection accuracy of 98.11%, with a very low False Positive Rate of 0.01. Taken together, Eth-PSD showed a superior advantage compared to the existing works in reducing the dimensionality of the dataset by feature engineering and achieved an overall detection accuracy with an improvement of at least 6% compared to other existing solutions from the related work.

Shahid Hussain Danwar, Javed Ahmed Mahar, Aneela Kiran

Election allows the voter of a country to select the most suitable group of candidates to run the government. Election in Pakistan is simply paper-based method but some certain political and socio-economic issues turn that simple process in complicated and disputes once. Solutions of such problems are consisting of many methods including the e-voting system. The e-voting system facilitates the voters to cast their votes by electronic means with very easy and convenient way. This also allows maintaining the security and secrecy of the voter along with election process. Electronic voting reduces the human-involvement throughout the process from start to the end. Such system is not established yet in Pakistan. Hence, every election is disputed always. In this paper we proposed the framework of an e-voting system and simulation with the use of blockchain ledger technology. The proposed framework owns the capacity to deal with ballots in Pakistan. The novelty of the framework is that the e-voting system is linked to National Database and Registration Authority (NADRA) database which assures voter's validation. The fundamental requirements were kept in consideration during the performance evaluation of the system. The results are processed and depicted specially with reference to the number of voters and voting stations, real time of vote casting, network bandwidth and controlling principles. The results support the decision makers and guide them in the foundation and customization of an e-voting system in Pakistan.

Zeinab Shahbazi, Yung-Cheol Byun

Information sharing is one of the huge topics in social media platform regarding the daily news related to events or disasters happens in nature or its human-made. The automatic urgent need identification and sharing posts and information delivery with a short response are essential tasks in this area. The key goal of this research is developing a solution for management of disasters and emergency response using social media platforms as a core component. This process focuses on text analysis techniques to improve the process of authorities in terms of emergency response and filter the information using the automatically gathered information to support the relief efforts. Specifically, we used state-of-art Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) based on supervised and unsupervised learning using social media datasets to extract real-time content related to the emergency events to comfort the fast response in a critical situation. Similarly, the blockchain framework used in this process for trust verification of the detected events and eliminating the single authority on the system. The main reason of using the integrated system is to improve the system security and transparency to avoid sharing the wrong information related to an event in social media.