Hiding in Plain Sight: A Longitudinal Study of Combosquatting Abuse

Domain squatting is a common adversarial practice where attackers register domain names that are purposefully similar to popular domains. In this work, we study a specific type of domain squatting called "combosquatting," in which attackers register domains that combine a popular trademark with one or more phrases (e.g., betterfacebook[.]com, youtube-live[.]com). We perform the first large-scale, empirical study of combosquatting by analyzing more than 468 billion DNS records---collected from passive and active DNS data sources over almost six years. We find that almost 60% of abusive combosquatting domains live for more than 1,000 days, and even worse, we observe increased activity associated with combosquatting year over year. Moreover, we show that combosquatting is used to perform a spectrum of different types of abuse including phishing, social engineering, affiliate abuse, trademark abuse, and even advanced persistent threats. Our results suggest that combosquatting is a real problem that requires increased scrutiny by the security community.Comment: ACM CCS 1

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Code Renewability for Native Software Protection

Software protection aims at safeguarding assets embedded in software by preventing and delaying reverse engineering and tampering attacks. This paper presents an architecture and supporting tool flow to renew parts of native applications dynamically. Renewed and diversified code and data belonging to either the original application or to linked-in protections are delivered from a secure server to a client on demand. This results in frequent changes to the software components when they are under attack, thus making attacks harder. By supporting various forms of diversification and renewability, novel protection combinations become available, and existing combinations become stronger. The prototype implementation is evaluated on a number of industrial use cases

Avoiding the internet of insecure industrial things

Security incidents such as targeted distributed denial of service (DDoS) attacks on power grids and hacking of factory industrial control systems (ICS) are on the increase. This paper unpacks where emerging security risks lie for the industrial internet of things, drawing on both technical and regulatory perspectives. Legal changes are being ushered by the European Union (EU) Network and Information Security (NIS) Directive 2016 and the General Data Protection Regulation 2016 (GDPR) (both to be enforced from May 2018). We use the case study of the emergent smart energy supply chain to frame, scope out and consolidate the breadth of security concerns at play, and the regulatory responses. We argue the industrial IoT brings four security concerns to the fore, namely: appreciating the shift from offline to online infrastructure; managing temporal dimensions of security; addressing the implementation gap for best practice; and engaging with infrastructural complexity. Our goal is to surface risks and foster dialogue to avoid the emergence of an Internet of Insecure Industrial Things

R-Locker: Thwarting Ransomware Action through a Honey le-based Approach

Ransomware has become a pandemic nowadays. Although some proposals exist to fight against this increasing type of extorsion, most of them are prevention like and rely on the assumption that early detection is not so effective once the victim is infected. This paper presents a novel approach intended not just to early detect ransomware but to completly thwart its action. For that, a set of honeyfiles are deployed around the target environment in order to catch the ransomware. Instead of being normal archives, honeyfiles are FIFO like, so that the ransomware is blocked once it starts reading the file. In addition to frustrate its action, our honeyfile solution is able to automatically launch countermeasures to solve the infection. Moreover, as it does not require previous training or knowledge, the approach allows fighting against unknown, zero-day ransomware related attacks. As a proof of concept, we have developed the approach for Unix platforms. The tool, named R-Locker, shows excellent performance both from the perspective of its accuracy as well as in terms of complexity and resource consumption. In addition, it has no special needs or privileges and does not affect the normal operation of the overall environment

Detecting semantic social engineering attacks with the weakest link: Implementation and empirical evaluation of a human-as-a-security-sensor framework

The notion that the human user is the weakest link in information security has been strongly, and, we argue, rightly contested in recent years. Here, we take a step further showing that the human user can in fact be the strongest link for detecting attacks that involve deception, such as application masquerading, spearphishing, WiFi evil twin and other types of semantic social engineering. Towards this direction, we have developed a human-as-a-security-sensor framework and a practical implementation in the form of Cogni-Sense, a Microsoft Windows prototype application, designed to allow and encourage users to actively detect and report semantic social engineering attacks against them. Experimental evaluation with 26 users of different profiles running Cogni-Sense on their personal computers for a period of 45 days has shown that human sensors can consistently outperform technical security systems. Making use of a machine learning based approach, we also show that the reliability of each report, and consequently the performance of each human sensor, can be predicted in a meaningful and practical manner. In an organisation that employs a human-as-a-security-sensor implementation, such as Cogni-Sense, an attack is considered to have been detected if at least one user has reported it. In our evaluation, a small organisation consisting only of the 26 participants of the experiment would have exhibited a missed detection rate below 10%, down from 81% if only technical security systems had been used. The results strongly point towards the need to actively involve the user not only in prevention through cyber hygiene and user-centric security design, but also in active cyber threat detection and reporting