Related papers: Demystifying Cryptocurrency Mining Attacks: A Semi…
Ransomware is considered as a significant threat for most enterprises since the past few years. In scenarios wherein users can access all files on a shared server, one infected host can lock the access to all shared files. We propose a tool…
The incremental diffusion of machine learning algorithms in supporting cybersecurity is creating novel defensive opportunities but also new types of risks. Multiple researches have shown that machine learning methods are vulnerable to…
Soon after its introduction in 2009, Bitcoin has been adopted by cyber-criminals, which rely on its pseudonymity to implement virtually untraceable scams. One of the typical scams that operate on Bitcoin are the so-called Ponzi schemes.…
In this paper, we examine the recent trend towards in-browser mining of cryptocurrencies; in particular, the mining of Monero through Coinhive and similar code- bases. In this model, a user visiting a website will download a JavaScript code…
This article considers a short survey of basic methods of social networks analysis, which are used for detecting cyber threats. The main types of social network threats are presented. Basic methods of graph theory and data mining, that…
In the wake of the arrival of digital media, the Internet, the web, and online social media, a flood of new cyber security research questions have emerged. There is a lot of money being lost around the world because of cyber-attacks. As a…
Given the increased growing of Internet of Things networks and their presence in critical aspects of human activities, the security of devices connected to these networks becomes critical. Machine Learning approaches are becoming prominent…
In-browser cryptojacking involves hijacking the CPU power of a website's visitor to perform CPU-intensive cryptocurrency mining, and has been on the rise, with 8500% growth during 2017. While some websites advocate cryptojacking as a…
Threats from the internet, particularly malicious software (i.e., malware) often use cryptographic algorithms to disguise their actions and even to take control of a victim's system (as in the case of ransomware). Malware and other threats…
The cybersecurity threat landscape has lately become overly complex. Threat actors leverage weaknesses in the network and endpoint security in a very coordinated manner to perpetuate sophisticated attacks that could bring down the entire…
Blockchains and cryptocurrencies disrupted the conversion of energy into a medium of exchange. Numerous applications for blockchains and cryptocurrencies are now envisioned for purposes ranging from inventory control to banking…
Phishing is an increasingly sophisticated form of cyberattack that is inflicting huge financial damage to corporations throughout the globe while also jeopardizing individuals' privacy. Attackers are constantly devising new methods of…
Utilizing graph analytics and learning has proven to be an effective method for exploring aspects of crypto economics such as network effects, decentralization, tokenomics, and fraud detection. However, the majority of existing research…
Cyber security can be enhanced through application of machine learning by recasting network attack data into an image format, then applying supervised computer vision and other machine learning techniques to detect malicious specimens.…
Cybersecurity attacks are growing both in frequency and sophistication over the years. This increasing sophistication and complexity call for more advancement and continuous innovation in defensive strategies. Traditional methods of…
Blockchain technology transformed the digital sphere by providing a transparent, secure, and decentralized platform for data security across a range of industries, including cryptocurrencies and supply chain management. Blockchain's…
This thesis presents techniques to investigate transactions in uncharted cryptocurrencies and services. Cryptocurrencies are used to securely send payments online. Payments via the first cryptocurrency, Bitcoin, use pseudonymous addresses…
Network intrusion detection systems play a vital role in protecting networks by detecting malicious network traffic which can then be investigated by a cybersecurity operations centre. State-of-the-art approaches utilise supervised machine…
Application of deep learning to enhance the accuracy of intrusion detection in modern computer networks were studied in this paper. The identification of attacks in computer networks is divided in to two categories of intrusion detection…
Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies in this information age. Data mining technologies extract hidden…