Jawad Ali, Ahmad Shahrafidz Khalid, Eiad Yafi, Shahrulniza Musa · 5 authors
Internet of Things (IoT) occupies a vital aspect of our everyday lives. IoT networks composed of smart-devices which communicate and transfer the information without the physical intervention of humans. Due to such proliferation and autonomous nature of IoT systems make these devices threatened and prone to a severe kind of threats. In this paper, we introduces a behavior capturing, and verification procedures in blockchain supported smart-IoT systems that can be able to show the trust-level confidence to outside networks. We defined a custom \emph{Behavior Monitor} and implement on a selected node that can extract the activity of each device and analyzes the behavior using deep machine learning strategy. Besides, we deploy Trusted Execution Technology (TEE) which can be used to provide a secure execution environment (enclave) for sensitive application code and data on the blockchain. Finally, in the evaluation phase we analyze various IoT devices data that is infected by Mirai attack. The evaluation results show the strength of our proposed method in terms of accuracy and time required for detection.
Le Su, Dinil Mon Divakaran, Sze Ling Yeo, Jiqiang Lu · 5 authors
With the rapid deployment of IoT devices, there is an increasing concern on the security and privacy of the devices. We are now witnessing newer and higher intensity attacks that exploit IoT devices. Although security-by-design is important and necessary, the effectiveness and sustainability of the buildin security defense may still be questionable. This has created new opportunities for third-party security service providers to enter the market. In this work, we leverage the distributed ledger technology (DLT) to propose a solution for distributing IoT security functions. We design the system architecture and describe the different types of operations to be executed. Our system also allows for reputation scoring that further adds credibility to the security functions distributed in the network.
Although the launch of Internet Protocol version six (IPv6) addressed the issue of IPv4's address depletion, but also mandated the use of Internet Control Message Protocol version six (ICMPv6) messages in newly introduced features such as the Neighbor Discovery Protocol (NDP). This has exacerbated existing network attacks including ICMPv6-based Denial of Service (DoS) attacks and its variant form Distributed Denial of Service (DDoS) attack. Intrusion Detection Systems (IDS) aimed at tackling security issues raised by ICMPv6-based DoS and DDoS attacks have been reviewed by researchers and a general classification of existing IDSs was proposed as anomaly-based and signature-based. However, it is incredibly hard to see the overall picture of IDSs based on Machine Learning (ML) techniques with such a classification, as there is a lack of a more detailed view of the ML approach, classifiers, feature selection techniques, datasets, and different evaluation metrics. Nevertheless, recent developments in this relatively new field have not been covered such as ML-based IDSs using flow-based traffic representation. Therefore, this article specifically reviews and classifies IDSs based on ML techniques to detect ICMPv6-based DoS and DDoS attacks as single and hybrid classifiers. In addition, blockchain applicability in Collaborative IDS (CIDS) architecture based on the ensemble framework has been proposed as a solution to one of the open challenges for ICMPv6-based DoS and DDoS attacks detection problem. Moreover, this review also provides a classification of ICMPv6 vulnerabilities to DoS and DDoS attacks which would provide a reference resource for future researchers in this domain. To the best of the author's knowledge, this is the first review paper specifically focusing on IDSs based on ML techniques in this domain, as well as blockchain applicability as a possible research direction has been proposed to attract researcher's focus on building ensemble learning-based IDS models.
The Onion Router (Tor) is one of the major network systems that provide anonymous communication and censorship circumvention. Tor enables its users to surf the Internet, chat, and send messages anonymously; however, cyber attackers also exploit the system for circumventing criminal activity detection. Recently, various approaches that prevent or mitigate abuse of Tor have been proposed in the literature. This paper, which presents one of the approaches, addresses an IP traceback problem. In our model, onion routers that voluntarily participate in attacker tracing detect attack packets (packets carrying an attacker's code or data) recorded in the log files by sharing necessary information with an attacked server over an Ethereum blockchain network. The detection algorithm in this paper uses the statistics of packet travel and relay times and outputs attack-packet candidates. The proposed method attaches a reliability degree to each candidate, which is based on the upper bounds of its Type I and II error rates. A smart contract running on the blockchain network ranks the detection results from onion routers according to the reliability degrees.
The inseparable internet requirements and the endless stream of cyber-attacks have led to strong demand for trusted IP addresses. However, the existing collaborative DNS security schemes have the defects of low credibility and imperfect incentive mechanism. Enlightened by the Consortium blockchain technology, we propose a novel DNS Cache Resources Trusted Sharing Model, which can improve the credibility of DNS resolution results by establishing a complete chain of trust. Firstly, the consortium blockchain is introduced as the carrier of the peer-to-peer network to reduce the impact of illegal access and complicity tampering on the DNS cache credibility; Secondly, the evaluation index of the node credibility in the DNS cache sharing model is proposed, and the trust-based incentive mechanism is designed to reduce the impact of free-riding behavior and on the trusted performance of the system. The two indicators of node abnormal behavior similarity and roundtrip time between nodes are used to comprehensively evaluate the degree of recommendation of the node and serve as the basis for dynamic scheduling; Finally, we use the stochastic distributed decentralized storage mechanism to solve the problem of low efficiency in the consortium blockchain. The simulation results show that the model has certain advantages in ensuring the credibility of domain name resolution results, and maintains the ideal efficiency while ensuring trust.
Abstract Web-based cryptocurrency mining attacks, also known as cryptojacking, become increasingly popular. A large number of diverse platforms (e.g., Windows, Linux, Android, and iOS) and devices (e.g., PC, smartphones, tablets, and even critical infrastructures) are widely impacted. Although a variety of detection approaches were recently proposed, it is challenging to apply these approaches to attack prevention directly. Instead, in this paper, we present a novel generic and accurate defense solution, called “MinerGate”, against cryptojacking attacks. To achieve the goal, MinerGate is designed as an extension of network gateways or proxies to protect all devices behind it. When attacks are identified, MinerGate can enforce security rules on victim devices, such as stopping the execution of related JavaScript code and alerting victims. Compared to prior approaches, MinerGate does not require any modification of browsers or apps to collect the runtime features. Instead, MinerGate focuses on the semantics of mining payloads (usually written in WebAssembly/asm.js), and semantic-based features. In our evaluation, we first verify the correctness of MinerGate by testing MinerGate in a real environment. Then, we check MinerGate’s performance and confirm MinerGate introduces relatively low overhead. Last, we verify the accuracy of MinerGate. For this purpose, we collect the largest WebAssembly/asm.js related code with ground truth to build our experiment dataset. By comparing prior approaches and MinerGate on the dataset, we find MinerGate achieves better accuracy and coverage (i.e., 99% accuracy and 98% recall). Our dataset will be available online, which should be helpful for more solid understanding of cryptojacking attacks.
Jan 1, 2020·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Vikram Kanth, Ashley McaAbee, Murali Tummala, John McEachen
As the threat of cyber attack grows ever larger, new approaches to security are required. While there are several different types of intrusion detection systems (IDS), collaborative IDS (CIDS) offers particular promise in identifying distributed, coordinated attacks that might otherwise elude detection. Even for CIDS, there are unresolved issues associated with trusting participants and aggregating data. Blockchain technology appears capable of addressing those issues if practical implementation strategies can be developed. To that end, we implement an Ethereum blockchain-based CIDS leveraging pluggable authentication modules. Our system is specifically crafted to detect doorknob rattling attacks by immutably recording login activity in a blockchain-protected ledger.
Nuclear Power Plants (NPPs) are physically isolated from external networks and have different operational environments than conventional information technology (IT) systems. Accordingly, NPPs were regarded as safe from external cyber-attacks. However, it was later determined that isolated networks are not safe from cyber-attacks. Malicious data injection attacks on Programmable Logic Controllers (PLCs) deployed in the safety system of NPPs are critical to nuclear facilities, as they were in the Stuxnet attack. It is necessary to monitor the integrity of PLC data and protect the PLCs from cyber threats such as modification of deployed logic or setpoints. To address this problem, this paper proposes a novel system for monitoring data integrity of PLCs using blockchain technologies. Considering the NPP environment, we developed a private blockchain system to monitor the data integrity of PLCs. The new concept that is Proof of Monitoring (PoM) for data integrity of PLCs was proposed to overcome the limitation for applying the private blockchain to the cybersecurity of NPPs. Additionally, we developed an integrity monitoring system for the Reactor Protection System (RPS)-a safety system in NPPs-using the developed blockchain. It can detect cyber-attacks (such as false code injection attacks on PLCs) and monitor which PLC integrity has been compromised in real-time. A validation experiment using a false data injection attack on PLCs was performed on the developed system, and the results confirmed that the developed system successfully monitored the modification of data in the PLCs.
Condominium network refers to intra-organization networks, where smart buildings or apartments are connected and share resources over the network. Secured communication platform or channel has been highlighted as a key requirement for a reliable condominium which can be ensured by the utilization of the advanced techniques and platforms like Software-Defined Network (SDN), Network Function Virtualization (NFV) and Blockchain (BC). These technologies provide a robust, and secured platform to meet all kinds of challenges, such as safety, confidentiality, flexibility, efficiency, and availability. This work suggests a distributed, scalable IoT-SDN with Blockchain-based NFV framework for a smart condominium (DistB-Condo) that can act as an efficient secured platform for a small community. Moreover, the Blockchain-based IoT-SDN with NFV framework provides the combined benefits of leading technologies. It also presents an optimized Cluster Head Selection (CHS) algorithm for selecting a Cluster Head (CH) among the clusters that efficiently saves energy. Besides, a decentralized and secured Blockchain approach has been introduced that allows more prominent security and privacy to the desired condominium network. Our proposed approach has also the ability to detect attacks in an IoT environment. Eventually, this article evaluates the performance of the proposed architecture using different parameters (e.g., throughput, packet arrival rate, and response time). The proposed approach outperforms the existing OF-Based SDN. DistB-Condo has better throughput on average, and the bandwidth (Mbps) much higher than the OF-Based SDN approach in the presence of attacks. Also, the proposed model has an average response time of 5% less than the core model.
Over the past twenty years, the number of devices connected to the Internet grew exponentially. Botnets benefited from this rise to increase their size and the magnitude of their attacks. However, they still have a weak point in their Command & Control (C&C) system, which is often based on centralized services or require a complex infrastructure to keep operating without being taken down by authorities. The recent spread of blockchain technologies may give botnets a powerful tool to make them very hard to disrupt. Recent research showed how it is possible to embed C&C messages in Bitcoin transactions, making them nearly impossible to block. Nevertheless, transactions have a cost and allow very limited amounts of data to be transmitted. Because of that, only messages from the botmaster to the bots are sent via Bitcoin, while bots are assumed to communicate through external channels. Furthermore, for the same reason, Bitcoin-based messages are sent in clear. In this paper we show how, using Bitcoin Testnet, it is possible to overcome these limitations and implement a cost-free, bidirectional, and encrypted C&C channel between the botmaster and the bots. We propose a communication protocol and analyze its viability in real life. Our results show that this approach would enable a botmaster to build a robust and hard-to-disrupt C&C system at virtually no cost, thus representing a realistic threat for which countermeasures should be devised.
E-voting is the process of conducting the voting process through online. The voters can cast their votes from different locations and these votes are collected and recorded electronically. Therefore, there is a need for a system to provide control and security to the whole procedure. Blockchain, a distributed ledger technology can be integrated to provide a decentralized system. Blockchain uses distributed ledger technology (DLT) to avoid forged voting option & non-repudiation and one time login of the user is also ensured. By integrating the above techniques, a secure user authentication for e-voting supported blockchain in p2p network is projected. This system would increase the safety by avoiding the forgery of votes. Similarly, the blockchain are often integrated to a spread of voting situations and a few alternative applications.
Open access
2 source records
Blockchain Technology Applications and Security
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Anita A. Lahane, Junaid Patel, Talif Pathan, Prathmesh Potdar
Election could be a important event during a trendy democracy however massive sections of society round the world don’t trust their election system that is major concern for the democracy. Even the world’s largest democracies like Republic of India, us, and Japan still suffer from a blemished legal system. Vote rigging, hacking of the EVM (Electronic vote machine), election manipulation, and booth capturing square measure the key problems within the current electoral system. during this system, we tend to square measure work the problems|the problems within the election vote systems and attempting to propose the E-voting model which might resolve these issues. The system can highlight a number of the popular blockchain frameworks that provide blockchain as a service and associated electronic E-voting system that is predicated on blockchain that addresses all limitations severally, it additionally preserve participant’s obscurity whereas still being hospitable public examination. Building Associate in Nursing electronic electoral system that satisfies the legal necessities of legislators has been a challenge for an extended time. Distributed ledger technologies is Associate in Nursing exciting technological advancement within the info technology world. Blockchain technologies supply Associate in Nursing infinite vary of applications cashing in on sharing economies. Blockchain could be a unquiet technology of current era and guarantees to enhance the resilience of e-voting systems. this technique presents a shot to leverage edges of blockchain like cryptological foundations and transparency to attain an efficient theme for e-voting. The projected theme conforms to the elemental necessities for e-voting schemes and achieves end-to-end verifiability. The system presents in-depth analysis of the theme that with success demonstrates its effectiveness to attain Associate in Nursing end-to-end verifiable e-voting theme.
Open access
Internet Traffic Analysis and Secure E-voting
Network Security and Intrusion Detection
Advanced Steganography and Watermarking Techniques
Privacy-focused crypto-currencies, such as Zcash or Monero, aim to provide strong cryptographic guarantees for transaction confidentiality and unlinkability.In this paper, we describe side-channel attacks that let remote adversaries bypass these protections.We present a general class of timing side-channel and traffic-analysis attacks on receiver privacy.These attacks enable an active remote adversary to identify the (secret) payee of any transaction in Zcash or Monero.The attacks violate the privacy goals of these crypto-currencies by exploiting side-channel information leaked by the implementation of different system components.Specifically, we show that a remote party can link all transactions that send funds to a user, by measuring the response time of that user's P2P node to certain requests.The timing differences are large enough that the attacks can be mounted remotely over a WAN.We responsibly disclosed the issues to the affected projects, and they have patched the vulnerabilities.We further study the impact of timing side-channels on the zero-knowledge proof systems used in these cryptocurrencies.We observe that in Zcash's implementation, the time to generate a zero-knowledge proof depends on secret transaction data, and in particular on the amount of transacted funds.Hence, an adversary capable of measuring proof generation time could break transaction confidentiality, despite the proof system's zero-knowledge property.Our attacks highlight the dangers of side-channel leakage in anonymous crypto-currencies, and the need to systematically protect them against such attacks.
Matteo Signorini, Matteo Pontecorvi, Waël Kanoun, Roberto Di Pietro
Anomaly detection tools play a role of paramount importance in protecting networks and systems from unforeseen attacks, usually by automatically recognizing and filtering out anomalous activities. Over the years, different approaches have been designed, all focused on lowering the false positive rate. However, no proposal has addressed attacks specifically targeting blockchain-based systems. In this paper, we present BAD: Blockchain Anomaly Detection. This is the first solution, to the best of our knowledge, that is tailored to detect anomalies in blockchain-based systems. BAD is a complete framework, relying on several components leveraging, at its core, blockchain meta-data in order to collect potentially malicious activities. BAD enjoys some unique features: (i) it is distributed (thus avoiding any central point of failure); (ii) it is tamper-proof (making it impossible for a malicious software to remove or to alter its own traces); (iii) it is trusted (any behavioral data is collected and verified by the majority of the network); and, (iv) it is private (avoiding any third party to collect/analyze/store sensitive information). Our proposal is described in detail and validated via both experimental results and analysis, that highlight the quality and viability of our Blockchain Anomaly Detection solution.
This paper reviews the background and related studies in the areas of cloud systems, intrusion detection and blockchain applications against cyber attacks. This work aims to discuss collaborative anomaly detection systems for discovering insider and outsider attacks from cloud centres, including the technologies of virtualisation and containerisation, along with trusting intrusion detection and cloud systems using blockchain. Moreover, the ability to detect such malicious attacks is critical for conducting necessary mitigation, at an early stage, to minimise the impact of disruption and restore cloud operations and their live migration processes. This paper presents an overview of cloud architecture and categorises potential state-of-the-art security events based on their occurrence at different cloud deployment models. Network Intrusion Detection Systems (NIDS) in the cloud, involving types of classification and common detection approaches, are also described. Collaborative NIDSs for cloud-based blockchain applications are also explained to demonstrate how blockchain can address challenges related to data privacy and trust management. A summary of the research challenges and future research directions in these fields is also explained.
Bruno Rodrigues, Trendafilov Spasen, Eder J. Scheid, Burkhard Stiller
Distributed Denial-of-Service (DDoS) attacks remains as one of the major causes of concerns for service providers around the world. This paper introduces SC-FLARE, a Smart Contract (SC) based cooperative signaling protocol built on top of a Ethereum Proof-of-Authority Blockchain (BC) for the sharing of attack information, the exchange of incentives, and the tracking of reputation in a fully distributed and automated fashion. By making use of BC and SC, SC-FLARE provide the required collaborative platform without the burden to maintain, design, and develop special registries and gossip protocols for a cooperative defense.
Pavlos Papadopoulos, Nikolaos Pitropakis, William J. Buchanan, Owen Lo · 5 authors
The Domain Name System (DNS) was created to resolve the IP addresses of the web servers to easily remembered names. When it was initially created, security was not a major concern; nowadays, this lack of inherent security and trust has exposed the global DNS infrastructure to malicious actors. The passive DNS data collection process creates a database containing various DNS data elements, some of which are personal and need to be protected to preserve the privacy of the end users. To this end, we propose the use of distributed ledger technology. We use Hyperledger Fabric to create a permissioned blockchain, which only authorized entities can access. The proposed solution supports queries for storing and retrieving data from the blockchain ledger, allowing the use of the passive DNS database for further analysis, e.g. for the identification of malicious domain names. Additionally, it effectively protects the DNS personal data from unauthorized entities, including the administrators that can act as potential malicious insiders, and allows only the data owners to perform queries over these data. We evaluated our proposed solution by creating a proof-of-concept experimental setup that passively collects DNS data from a network and then uses the distributed ledger technology to store the data in an immutable ledger, thus providing a full historical overview of all the records.
Cryptocurrencies have been a target for cybercriminal activities because of the pseudo-anonymity and privacy they offer. Researchers have been actively working on analyzing and developing innovative defensive mechanisms to prevent these activities. A significant challenge facing researchers is collecting datasets to train defensive systems to detect and analyze these cyberattacks. Our aims in this systematic review are to explore and aggregate the state of the art threats that have emerged with cryptocurrencies and the defensive mechanisms that have been proposed. We also discuss the threats type, scale, and how efficient the defensive mechanisms are in providing early detection and prevention. We also list out the resources that have been used to collect datasets, and we identify the publicly available ones. In this study, we extracted 1,221 articles from four top scientific and engineering databases and libraries in Computer Science: IEEE Xplore, ACM Digital Library, Elsevier's Scopus, and Crarivate's Web of Science. We defined inclusion, exclusion, and quality of assessment criteria, and after a detailed review process, 66 publications were included in the final review. Our analysis revealed that the literature contains a significant amount of research to detect and analyze several attack types, such as the high yield investment programs and pump and dump. These attacks have been used to steal millions of USD, abuse millions of connected devices, and have created even more significant loss in denial of services and productivity losses. We have found that the researchers use various sources to collect training datasets. Many authors have made their dataset publicly available. We have created a list of these datasets, which we have made available along with other supplementary websites, tools, and libraries that can be used in the data collection and analysis process.
This paper describes a simulation study on security attacks over Distributed Ledger Technologies (DLTs). We specifically focus on attacks at the underlying peer-to-peer layer of these systems, that is in charge of disseminating messages containing data and transaction to be spread among all participants. In particular, we consider the Sybil attack, according to which a malicious node creates many Sybils that drop messages coming from a specific attacked node, or even all messages from honest nodes. Our study shows that the selection of the specific dissemination protocol, as well as the amount of connections each peer has, have an influence on the resistance to this attack.
Blaž Podgorelec, Muhamed Turkanović, Sašo Karakatič
The basis of blockchain-related data, stored in distributed ledgers, are digitally signed transactions. Data can be stored on the blockchain ledger only after a digital signing process is performed by a user with a blockchain-based digital identity. However, this process is time-consuming and not user-friendly, which is one of the reasons blockchain technology is not fully accepted. In this paper, we propose a machine learning-based method, which introduces automated signing of blockchain transactions, while including also a personalized identification of anomalous transactions. In order to evaluate the proposed method, an experiment and analysis were performed on data from the Ethereum public main network. The analysis shows promising results and paves the road for a possible future integration of such a method in dedicated digital signing software for blockchain transactions.
Ahmet Kurt, Enes Erdin, Mumin Cebe, Kemal Akkaya · 5 authors
While various covert botnets were proposed in the past, they still lack complete anonymization for their servers/botmasters or suffer from slow communication between the botmaster and the bots. In this paper, we propose a new generation hybrid botnet that covertly and efficiently communicates over Bitcoin Lightning Network (LN), called LNBot. LN is a payment channel network operating on top of Bitcoin network for faster Bitcoin transactions with negligible fees. Exploiting various anonymity features of LN, we designed a scalable two-layer botnet which completely anonymize the identity of the botmaster. In the first layer, the botmaster sends commands anonymously to the C&C servers through LN transactions. Specifically, LNBot allows botmaster's commands to be sent in the form of surreptitious multihop LN payments, where the commands are encoded with ASCII or Huffman encoding to provide covert communications. In the second layer, C&C servers further relay those commands to the bots they control in their mini-botnets to launch any type of attacks to victim machines. We implemented a proof-of-concept on the actual LN and extensively analyzed the delay and cost performance of LNBot. Our analysis show that LNBot achieves better scalibility compared to the other similar blockchain botnets with negligible costs. Finally, we also provide and discuss a list of potential countermeasures to detect LNBot activities and minimize its impacts.