Biblio

With the advent of information and communication technology, the digital space is becoming a playing ground for criminal activities. Criminals typically prefer darkness or a hidden place to perform their illegal activities in a real-world while sometimes covering their face to avoid being exposed and getting caught. The same applies in a digital world where criminals prefer features which provide anonymity or hidden features to perform illegal activities. It is from this spirit the Darkweb is attracting all kinds of criminal activities conducted over the Internet such as selling drugs, illegal weapons, child pornography, assassination for hire, hackers for hire, and selling of malicious exploits, to mention a few. Although the anonymity offered by Darkweb can be exploited as a tool to arrest criminals involved in cybercrime, an in-depth research is needed to advance criminal investigation on Darkweb. Analysis of illegal activities conducted in Darkweb is in its infancy and faces several challenges like lack of standard operating procedures. This study proposes progressive standard operating procedures (SOPs) for Darkweb forensics investigation. We provide the four stages of SOP for Darkweb investigation. The proposed SOP consists of the following stages; identification and profiling, discovery, acquisition and preservation, and the last stage is analysis and reporting. In each stage, we consider the objectives, tools and expected results of that particular stage. Careful consideration of this SOP revealed promising results in the Darkweb investigation.

This paper dives into the growing world of IoT botnets that have taken the world by storm in the past five years. Though alone an IP camera cannot produce enough traffic to be considered a DDoS. But a botnet that has over 150,000 connected IP cameras can generate as much as 1 Tbps in traffic. Botnets catch many by surprise because their attacks and infections may not be as apparent as a DDoS, some other cases include using these cameras and printers for extracting information or quietly mine cryptocurrency at the IoT device owner's expense. Here we analyze damages on IoT hacking and define botnet architecture. An overview of Mirai botnet and cryptojacking provided to better understand the IoT botnets.

Blockchain technology has made it possible to store and send digital currencies. Bitcoin wallets and marketplaces have made it easy for nontechnical users to use the protocol. Since its inception, the price of Bitcoin is going up and the number of nodes in the network has increased drastically. The increasing popularity of Bitcoin has made exchanges and individual nodes a target for an attack. Understanding the Bitcoin protocol better helps security engineers to harden the network and helps regular users secure their hot wallets. In this paper, Bitcoin protocol is presented with description of the mining process which secures transactions. In addition, the Bitcoin algorithms and their security are described with potential vulnerabilities in the protocol and potential exploits for attackers. Finally, we propose some security solutions to help mitigate attacks on Bitcoin exchanges and hot wallets.

Ransomware groups represent a significant cyber threat to Western states. Most high-end ransomware actors reside in territorial safe-haven jurisdictions and prove to be resistant to traditional law enforcement activities. This has prompted public sector and cybersecurity industry leaders to perceive ransomware as a national security threat requiring a whole-of-government approach, including cyber operations. In this paper, we investigate whether cyber operations or the threat of cyber operations influence the ransomware ecosystem. Subsequently, we assess the vectors of influence and characteristics of past operations that have disrupted the ecosystem. We describe the specifics of the ransomware-as-a-service system and provide three case studies (DarkSide/BlackMatter, REvil, Conti) highly representative of the current ecosystem and the effect cyber operations have on it. Additionally, we present initial observations about the influence of cyber operations on the system, including best practices from cyber operations against non-state groups. We conclude that even professional, highly skilled, and top-performing ransomware groups can be disrupted through cyber operations. In fact, cyber operations can even bypass some limits imposed on law enforcement operations. Even when ransomware groups rebrand or resurface after a hiatus, we suggest their infrastructure (both technical, human, and reputational) will still suffer mid-to long-term disruption. Although cyber operations are unlikely to be a silver bullet, they are an essential tool in the whole-of-government and multinational efforts and may even grow in importance in the next several years.1‘Releasing the hounds’ is a term for offensive cyber operations aimed at disrupting global ransomware gangs, especially those conducted by militaries or intelligence agencies. First use is found in Patrick Gray and Adam Boileau, ‘Feature Podcast: Releasing the Hounds with Bobby Chesney’, Risky Business, 28 May 2020, https://risky.biz/HF6/.

The evolving and new age cybersecurity threats has set the information security industry on high alert. This modern age cyberattacks includes malware, phishing, artificial intelligence, machine learning and cryptocurrency. Our research highlights the importance and role of Software Quality Assurance for increasing the security standards that will not just protect the system but will handle the cyber-attacks better. With the series of cyber-attacks, we have concluded through our research that implementing code review and penetration testing will protect our data's integrity, availability, and confidentiality. We gathered user requirements of an application, gained a proper understanding of the functional as well as non-functional requirements. We implemented conventional software quality assurance techniques successfully but found that the application software was still vulnerable to potential issues. We proposed two additional stages in software quality assurance process to cater with this problem. After implementing this framework, we saw that maximum number of potential threats were already fixed before the first release of the software.

We propose DecCert, a decentralized public key infrastructure designed as a smart contract that solves the problem of identity attestation on public blockchains. Our system allows an individual to bind an identity to a public blockchain address. Once a claim of identity is made by an individual, other users can choose to verify the attested identity based on the evidence presented by an identity claim maker by staking cryptocurrency in the DecCert smart contract. Increasing levels of trust are naturally built based upon the amount staked and the duration the collateral is staked for. This mechanism replaces the usual utilization of digital signatures in a traditional hierarchical certificate authority model or the web of trust model to form a publicly verifiable decentralized stake of trust model. We also present a novel solution to the certificate revocation problem and implement our solution on the Ethereum blockchain. Further, we show that our design solves Zooko’s triangle as defined for public key infrastructure deployments.

In-browser cryptomining uses the computational power of a website's visitors to mine cryptocurrency, i.e., to create new coins. With the rise of ready-to-use mining scripts distributed by service providers (e.g., Coinhive), it has become trivial to turn a website into a cryptominer by copying and pasting the mining script. Both legitimate webpage owners who want to raise an extra revenue under users' explicit consent and malicious actors who wish to exploit the computational power of the users' computers without their consent have started to utilize this emerging paradigm of cryptocurrency operations. In-browser cryptomining, though mostly abused by malicious actors in practice, is indeed a promising funding model that can be utilized by website owners, publishers, or non-profit organizations for legitimate business purposes, such as to collect revenue or donations for humanitarian projects, inter alia. However, our analysis in this paper shows that in practice, regardless of their being legitimate or not, all in-browser mining scripts are treated the same as malicious cryptomining samples (aka cryptojacking) and blacklisted by browser extensions or antivirus programs. Indeed, there is a need for a better understanding of the in-browser cryptomining ecosystem. Hence, in this paper, we present an in-depth empirical analysis of in-browser cryptomining processes, focusing on the samples explicitly asking for user consent, which we call permissioned cryptomining. To the best of our knowledge, this is the first study focusing on the permissioned cryptomining samples. For this, we created a dataset of 6269 unique web sites containing cryptomining scripts in their source codes to characterize the in-browser cryptomining ecosystem by differentiating permissioned and permissionless cryptomining samples. We believe that (1) this paper is the first attempt showing that permissioned in-browser cryptomining could be a legitimate and viable monetization tool if implemented responsibly and without interrupting the user, and (2) this paper will catalyze the widespread adoption of legitimate crvptominina with user consent and awareness.

Lightning Network (LN) addresses the scalability problem of Bitcoin by leveraging off-chain transactions. Nevertheless, it is not possible to run LN on resource-constrained IoT devices due to its storage, memory, and processing requirements. Therefore, in this paper, we propose an efficient and secure protocol that enables an IoT device to use LN's functions through a gateway LN node. The idea is to involve the IoT device in LN operations with its digital signature by replacing original 2-of-2 multisignature channels with 3-of-3 multisignature channels. Our protocol enforces the LN gateway to request the IoT device's cryptographic signature for all operations on the channel. We evaluated the proposed protocol by implementing it on a Raspberry Pi for a toll payment scenario and demonstrated its feasibility and security.

Bitcoin is a representative cryptocurrency system using a permissionless peer-to-peer (P2P) network as its communication infrastructure. A number of attacks against Bitcoin have been discovered over the past years, including the Eclipse and EREBUS Attacks. In this paper, we present a new attack against Bitcoin’s P2P networking, dubbed ConMan because it leverages connection manipulation. ConMan achieves the same effect as the Eclipse and EREBUS Attacks in isolating a target (i.e., victim) node from the rest of the Bitcoin network. However, ConMan is different from these attacks because it is an active and deterministic attack, and is more effective and efficient. We validate ConMan through proof-of-concept exploitation in an environment that is coupled with real-world Bitcoin node functions. Experimental results show that ConMan only needs a few minutes to fully control the peer connections of a target node, which is in sharp contrast to the tens of days that are needed by the Eclipse and EREBUS Attacks. Further, we propose several countermeasures against ConMan. Some of them would be effective but incompatible with the design principles of Bitcoin, while the anomaly detection approach is positively achievable. We disclosed ConMan to the Bitcoin Core team and received their feedback, which confirms ConMan and the proposed countermeasures.

Because Bitcoin P2P networking is permissionless by the application requirement, it is vulnerable against networking threats based on identity/credential manipulations such as Sybil and spoofing attacks. The current Bitcoin implementation keeps track of its peer's networking misbehaviors through ban score. In this paper, we investigate the security problems of the ban-score mechanism and discover that the ban score is not only ineffective against the Bitcoin Message-based DoS attacks but also vulnerable to a Defamation attack. In the Defamation attack, the network adversary can exploit the ban-score mechanism to defame innocent peers.

In this paper, we propose a novel protocol to represent the human factor on a blockchain environment. Our approach allows single or groups of humans to propose data in blocks which cannot be validated automatically but need human knowledge and collaboration to be validated. Only if human-based consensus on the correctness and trustworthiness of the data is reached, the new block is appended to the blockchain. This human approach significantly extends the possibilities of blockchain applications on data types apart from financial transaction data.

Homomorphic encryption allows users to perform mathematical operations on open data in encrypted form by performing homomorphically appropriate operations on encrypted data without knowing the decryption function (key). Nowadays such possibilities for cryptoalgorithm are very important in many areas such as data storage, cloud computing, cryptocurrency, and mush more. In 2009 a system of fully homomorphic encryption was constructed, in the future, many works were done based on it. In this work, is performed the implementation of ideal lattices for constructing homomorphic operations over ciphertexts. The idea, presented in this work, allows to separate relations between homomorphic and security parts of a lattice-based homomorphic encryption system.

This paper discusses securities and cryptocurrency trading using artificial intelligence (AI) in the sense that it focuses on performing Exploratory Data Analysis (EDA) on selected technical indicators before proceeding to modelling, and then to develop more practical models by introducing new reward loss function that maximizes the returns during training phase. The results of EDA reveal that the complex patterns within the data can be better captured by discriminative classification models and this was endorsed by performing back-testing on two securities using Artificial Neural Network (ANN) and Random Forests (RF) as discriminative models against their counterpart Na\"ıve Bayes as a generative model. To enhance the learning process, the new reward loss function is utilized to retrain the ANN with testing on AAPL, IBM, BRENT CRUDE and BTC using auto-trading strategy that serves as the intelligent unit, and the results indicate this loss superiorly outperforms the conventional cross-entropy used in predictive models. The overall results of this work suggest that there should be larger focus on EDA and more practical losses in the research of machine learning modelling for stock market prediction applications.

In this century, the demand for energy is increasing daily, and the need for energy resources has become urgent and inevitable. New ways of generating energy, such as renewable resources that depend on many sources, including the sun and wind energy will contribute to the future of humankind largely and effectively. These renewable sources are facing major challenges that cannot be ignored which also require more researches on appropriate solutions . This has led to the emergence of a new type of network user called prosumer, which causes new challenges such as the intermittent nature of renewable. Smart grids have emerged as a solution to integrate these distributed energy sources. It also provides a mechanism to maintain safety and security for power supply networks. The main idea of smart grids is to facilitate local production and consumption By customers and consumers.Distributed ledger technology (DLT) or Block-chain technology has evolved dramatically since 2008 that coincided with the birth of its first application Bitcoin, which is the first cryptocurrency. This innovation led to sparked in the digital revolution, which provides decentralization, security, and democratization of information storage and transfer systems across numerous sectors/industries. Block-chain can be applied for the sake of the durability and safety of energy systems. In this paper, we will propose a new distributed framework that provides protection based on block-chain technology for energy systems to enhance self-defense capability against those cyber-attacks.

Nowadays, blockchain is very common and widely used in various fields. The properties of blockchain-based algorithms such as being decentralized and uncontrolled by institutions and governments, are the main reasons that has attracted many applications. The security and the scalability limitations are the main challenges for the development of these systems. Using second layer network is one of the various methods proposed to improve the scalability of these systems. This network can increase the total number of transactions per second by creating extra channels between the nodes that operate in a different layer not obligated to be on consensus ledger. In this paper, the optimal structure for the second layer network has been presented. In the proposed structure we try to distribute the parameters of the second layer network as symmetrically as possible. To prove the optimality of this structure we first introduce the maximum scalability bound, and then calculate it for the proposed structure. This paper will show how the second layer method can improve the scalability without any information about the rate of transactions between nodes.

In the dawn of crypto-currencies the most talked currency is Bitcoin. Bitcoin is widely flourished digital currency and an exchange trading commodity implementing peer-to-peer payment network. No central athourity exists in Bitcoin. The users in network or pool of bitcoin need not to use real names, rather they use pseudo names for managing and verifying transactions. Due to the use of pseudo names bitcoin is apprehended to provide anonymity. However, the most transparent payment network is what bitcoin is. Here all the transactions are publicly open. To furnish wholeness and put a stop to double-spending, Blockchain is used, which actually works as a ledger for management of Bitcoins. Blockchain can be misused to monitor flow of bitcoins among multiple transactions. When data from external sources is amalgamated with insinuation acquired from the Blockchain, it may result to reveal user's identity and profile. In this way the activity of user may be traced to an extent to fraud that user. Along with the popularity of Bitcoins the number of adversarial attacks has also gain pace. All these activities are meant to exploit anonymity and privacy in Bitcoin. These acivities result in loss of bitcoins and unlawful profit to attackers. Here in this paper we tried to present analysis of major attacks such as malicious attack, greater than 52% attacks and block withholding attack. Also this paper aims to present analysis and improvements in Bitcoin's anonymity and privacy.

We investigate what we call the "Bitcoin Generator Scam" (BGS), a simple system in which the scammers promise to "generate" new bitcoins using the ones that were sent to them. A typical offer will suggest that, for a small fee, one could receive within minutes twice the amount of bitcoins submitted. BGS is clearly not a very sophisticated attack. The modus operandi is simply to put up some web page on which to find the address to send the money and wait for the payback. The pages are then indexed by search engines, and ready to find for victims looking for free bitcoins. We describe here a generic system to find and analyze scams such as BGS. We have trained a classifier to detect these pages, and we have a crawler searching for instances using a series of search engines. We then monitor the instances that we find to trace payments and bitcoin addresses that are being used over time. Unlike most bitcoin-based scam monitoring systems, we do not rely on analyzing transactions on the blockchain to find scam instances. Instead, we proactively find these instances through the web pages advertising the scam. Thus our system is able to find addresses with very few transactions, or even none at all. Indeed, over half of the addresses that have eventually received funds were detected before receiving any transactions. The data for this paper was collected over four months, from November 2019 to February 2020. We have found more than 1,300 addresses directly associated with the scam, hosted on over 500 domains. Overall, these addresses have received (at least) over 5 million USD to the scam, with an average of 47.3 USD per transaction.

Cryptojacking is the exploitation of victims' computer resources to mine for cryptocurrency using malicious scripts. It had become popular after 2017 when attackers started to exploit legal mining scripts, especially Coinhive scripts. Coinhive was actually a legal mining service that provided scripts and servers for in-browser mining activities. Nevertheless, over 10 million web users had been victims every month before the Coinhive shutdown that happened in Mar 2019. This paper explores the new era of the cryptojacking world after Coinhive discontinued its service. We aimed to see whether and how attackers continue cryptojacking, generate new malicious scripts, and developed new methods. We used a capable cryptojacking detector named CMTracker that proposed by Hong et al. in 2018. We automatically and manually examined 2770 websites that had been detected by CMTracker before the Coinhive shutdown. The results revealed that 99% of sites no longer continue cryptojacking. 1% of websites still run 8 unique mining scripts. By tracking these mining scripts, we detected 632 unique cryptojacking websites. Moreover, open-source investigations (OSINT) demonstrated that attackers still use the same methods. Therefore, we listed the typical patterns of cryptojacking. We concluded that cryptojacking is not dead after the Coinhive shutdown. It is still alive, but not as attractive as it used to be.

Illicitly hijacking visitors' computational resources for mining cryptocurrency via compromised websites is a consolidated activity.Previous works mainly focused on large-scale analysis of the cryptojacking ecosystem, technical means to detect browser-based mining as well as economic incentives of cryptojacking. So far, no one has studied if certain technical characteristics of a website can increase (decrease) the likelihood of being compromised for cryptojacking campaigns.In this paper, we propose to address this unanswered question by conducting a case-control study with cryptojacking websites obtained crawling the web using Minesweeper. Our preliminary analysis shows some association for certain website characteristics, however, the results obtained are not statistically significant. Thus, more data must be collected and further analysis must be conducted to obtain a better insight into the impact of these relations.

The use of public key cryptosystems ranges from securely encrypting bitcoin transactions and creating digital signatures for non-repudiation. The cryptographic systems security of public key depends on the complexity in solving mathematical problems. Quantum computers pose a threat to the current day algorithms used. This research presents analysis of two Hash-based Signature Schemes (MSS and W-OTS) and provides a comparative analysis of them. The comparisons are based on their efficiency as regards to their key generation, signature generation and verification time. These algorithms are compared with two classical algorithms (RSA and ECDSA) used in bitcoin transaction security. The results as shown in table II indicates that RSA key generation takes 0.2012s, signature generation takes 0.0778s and signature verification is 0.0040s. ECDSA key generation is 0.1378s, signature generation takes 0.0187s, and verification time for the signature is 0.0164s. The W-OTS key generation is 0.002s. To generate a signature in W-OTS, it takes 0.001s and verification time for the signature is 0.0002s. Lastly MSS Key generation, signature generation and verification has high values which are 16.290s, 17.474s, and 13.494s respectively. Based on the results, W-OTS is recommended for bitcoin transaction security because of its efficiency and ability to resist quantum computer attacks on the bitcoin network.

Blockchains - with their inherent properties of transaction transparency, distributed consensus, immutability and cryptographic verifiability - are increasingly seen as a means to underpin innovative products and services in a range of sectors from finance through to energy and healthcare. Discussions, too often, make assertions that the trustless nature of blockchain technologies enables and actively promotes their suitability - there being no need to trust third parties or centralised control. Yet humans need to be able to trust systems, and others with whom the system enables transactions. In this paper, we highlight that understanding this need for trust is critical for the development of blockchain-based systems. Through an online study with 125 users of the most well-known of blockchain based systems - the cryptocurrency Bitcoin - we uncover that human and institutional aspects of trust are pervasive. Our analysis highlights that, when designing future blockchain-based technologies, we ought to not only consider computational trust but also the wider eco-system, how trust plays a part in users engaging/disengaging with such eco-systems and where design choices impact upon trust. From this, we distill a set of guidelines for software engineers developing blockchain-based systems for societal applications.

Internet is a common method of trading business today. The usage of cryptocurrencies has increased these days and it has become a trend to utilize them. Cryptocurrency exchange servicers provide different smartphone apps that unfortunately may become the target of malicious attacks. This paper focuses on how it achieves highest security and proposes the multiple layered security analyses method for cryptocurrency exchange servicers.

On each cryptocurrency transaction, a high-level security is needed to protect user data as well as data on the transaction. At this stage, it takes the appropriate algorithm in securing transactions with more efficient processing time. The Elliptic Curve Cryptography (ECC) is one of the cryptography algorithms which has high-level security, and ECC is often compared with the Rivest, Shamir, and Adleman (RSA) algorithm because it has a security level that is almost the same but has some differences that make ECC is superior compared to the RSA algorithm, so that the ECC algorithm can optimize cryptocurrency security in the transaction process. The purpose of this study is to simulate the bitcoin transactions using cryptography algorithms. This study uses the ECC algorithm as the algorithm ECDH and ECDSA key exchange as the algorithm for signing and verifying. The comparison results of ECC and RSA processing time is 1:25, so the ECC is more efficient. The total processing time of ECC is 0,006 seconds and RSA is 0,152 seconds. The researcher succeeded to implement the ECC algorithm as securing algorithms in mining process of 3 scenarios, normal, failed, and fake bitcoin transactions.

This research analyzes a seemingly malicious behavior known as a block withholding (BWH) attack between pools of cryptocurrency miners in Bitcoin-like systems featuring blockchain distributed databases. This work updates and builds on a seminal paper, The Miner's Dilemma, which studied a simplified scenario and showed that a BWH attack can be rational behavior that is profitable for the attacker. The new research presented here provides an in-depth profit analysis of a more complex and realistic BWH attack scenario, which includes mutual attacks between multiple, non-uniform Bitcoin mining pools. As a result of mathematical analysis and MATLAB modeling, this paper illustrates the Nash equilibrium conditions of a system of independent mining pools with varied mining rates and computes the equilibrium rates of mutual BWH attack. The analysis method quantifies the additional profit the largest pools extract from the system at the expense of the smaller pools. The results indicate that while the presence of BWH is a net negative for smaller pools, they must participate in BWH to maximize their remaining profits, and the results quantify the attack rates the smaller pools must maintain. Also, the smallest pools maximize profit by not attacking at all-that is, retaliation is not a rational move for them.

Modern cybercrimes have exponentially grown over the last one decade. Ransomware is one of the types of malware which is the result of sophisticated attempt to compromise the modern computer systems. The governments and large corporations are investing heavily to combat this cyber threat against their critical infrastructure. It has been observed that over the last few years that Industrial Control Systems (ICS) have become the main target of Ransomware due to the sensitive operations involved in the day to day processes of these industries. As the technology is evolving, more and more traditional industrial systems are replaced with advanced industry methods involving advanced technologies such as Internet of Things (IoT). These technology shift help improve business productivity and keep the company's global competitive in an overflowing competitive market. However, the systems involved need secure measures to protect integrity and availability which will help avoid any malfunctioning to their operations due to the cyber-attacks. There have been several cyber-attack incidents on healthcare, pharmaceutical, water cleaning and energy sector. These ICS' s are operated by remote control facilities and variety of other devices such as programmable logic controllers (PLC) and sensors to make a network. Cyber criminals are exploring vulnerabilities in the design of these ICS's to take the command and control of these systems and disrupt daily operations until ransomware is paid. This paper will provide critical analysis of the impact of Ransomware threat on SCADA systems.