Defacement Detection with Passive Adversaries

A novel approach to defacement detection is proposed in this paper, addressing explicitly the possible presence of a passive adversary. Defacement detection is an important security measure for Web Sites and Applications, aimed at avoiding unwanted modifications that would result in significant reputational damage. As in many other anomaly detection contexts, the algorithm used to identify possible defacements is obtained via an Adversarial Machine Learning process. We consider an exploratory setting, where the adversary can observe the detector’s alarm-generating behaviour, with the purpose of devising and injecting defacements that will pass undetected. It is then necessary to make to learning process unpredictable, so that the adversary will be unable to replicate it and predict the classifier’s behaviour. We achieve this goal by introducing a secret key—a key that our adversary does not know. The key will influence the learning process in a number of different ways, that are precisely defined in this paper. This includes the subset of examples and features that are actually used, the time of learning and testing, as well as the learning algorithm’s hyper-parameters. This learning methodology is successfully applied in this context, by using the system with both real and artificially modified Web sites. A year-long experimentation is also described, referred to the monitoring of the new Web Site of a major manufacturing company

The World of Defacers: Looking through the Lens of Their Activities on Twitter

Many web-based attacks have been studied to understand how web hackers behave, but web site defacement attacks (malicious content manipulations of victim web sites) and defacers’ behaviors have received less attention from researchers. This paper fills this research gap via a computational data-driven analysis of a public database of defacers and defacement attacks and activities of 96 selected defacers who were active on Twitter. We conducted a comprehensive analysis of the data: an analysis of a friendship graph with 10,360 nodes, an analysis on how sentiments of defacers related to attack patterns, and a topical modelling based analysis to study what defacers discussed publicly on Twitter. Our analysis revealed a number of key findings: a modular and hierarchical clustering method can help discover interesting sub-communities of defacers; sentiment analysis can help categorize behaviors of defacers in terms of attack patterns; and topic modelling revealed some focus topics (politics, country-specific topics, and technical discussions) among defacers on Twitter and also geographic links of defacers sharing similar topics. We believe that these findings are useful for a better understanding of defacers' behaviors, which could help design and development of better solutions for detecting defacers and even preventing impeding defacement attacks

Identifying and Preventing Large-scale Internet Abuse

The widespread access to the Internet and the ubiquity of web-based services make it easy to communicate and interact globally. Unfortunately, the software and protocols implementing the functionality of these services are often vulnerable to attacks. In turn, an attacker can exploit them to compromise, take over, and abuse the services for her own nefarious purposes. In this dissertation, we aim to better understand such attacks, and we develop methods and algorithms to detect and prevent them, which we evaluate on large-scale datasets.First, we detail Meerkat, a system to detect a visible way in which websites are being compromised, namely website defacements. They can inflict significant harm on the websites’ operators through the loss of sales, the loss in reputation, or because of legal ramifications. Meerkat requires no prior knowledge about the websites’ content or their structure, but only the Uniform Resource Identifier (URI) at which they can be reached. By design, Meerkat mimics how a human analyst decides if a website was defaced when viewing it in a browser, by using computer vision techniques. Thus, it tackles the problem of detecting website defacements through their attention-seeking nature, their goal and purpose, rather than code or data artifacts that they might exhibit. In turn, it is much harder for an attacker to evade our system, as she needs to change her modus operandi. When Meerkat detects a website as defaced, the website can automatically be put into maintenance mode or restored to a known good state.An attacker, however, is not limited to abuse a compromised website in a way that is visible to the website’s visitors. Instead, she can misuse the website to infect its visitors with malicious software (malware). Although malware is well studied, identifying malicious websites remains a major challenge in today’s Internet. Second, we introduce Delta, a novel, purely static analysis approach that extracts change-related features between two versions of the same website, uses machine learning to derive a model of website changes, detects if an introduced change was malicious or benign, identifies the underlying infection vector based on clustering, and generates an identifying signature. Furthermore, due to the way Delta clusters campaigns, it can uncover infection campaigns that leverage specific vulnerable applications as a distribution channel, and it can greatly reduce the human labor necessary to uncover the application responsible for a service’s compromise.Third, we investigate the practicality and impact of domain takeover attacks, which an attacker can similarly abuse to spread misinformation or malware, and we present a defense on how such takeover attacks can be rendered toothless. Specifically, the new elasticity of Internet resources, in particular Internet protocol (IP) addresses in the context of Infrastructure-as-a-Service cloud service providers, combined with previously made protocol assumptions can lead to security issues. In Cloud Strife, we show that this dynamic component paired with recent developments in trust-based ecosystems (e.g., Transport Layer Security (TLS) certificates) creates so far unknown attack vectors. For example, a substantial number of stale domain name system (DNS) records points to readily available IP addresses in clouds, yet, they are still actively attempted to be accessed. Often, these records belong to discontinued services that were previously hosted in the cloud. We demonstrate that it is practical, and time and cost-efficient for attackers to allocate the IP addresses to which stale DNS records point. Further considering the ubiquity of domain validation in trust ecosystems, an attacker can impersonate the service by obtaining and using a valid certificate that is trusted by all major operating systems and browsers, which severely increases the attackers’ capabilities. The attacker can then also exploit residual trust in the domain name for phishing, receiving and sending emails, or possibly distributing code to clients that load remote code from the domain (e.g., loading of native code by mobile apps, or JavaScript libraries by websites). To prevent such attacks, we introduce a new authentication method for trust-based domain validation that mitigates staleness issues without incurring additional certificate requester effort by incorporating existing trust into the validation process.Finally, the analyses of Delta, Meerkat, and Cloud Strife have made use of large-scale measurements to assess our approaches’ impact and viability. Indeed, security research in general has made extensive use of exhaustive Internet-wide scans over the recent years, as they can provide significant insights into the state of security of the Internet (e.g., if classes of devices are behaving maliciously, or if they might be insecure and could turn malicious in an instant). However, the address space of the Internet’s core addressing protocol (Internet Protocol version 4; IPv4) is exhausted, and a migration to its successor (Internet Protocol version 6; IPv6), the only accepted long-term solution, is inevitable. In turn, to better understand the security of devices connected to the Internet, in particular Internet of Things devices, it is imperative to include IPv6 addresses in security evaluations and scans. Unfortunately, it is practically infeasible to iterate through the entire IPv6 address space, as it is 296 times larger than the IPv4 address space. Without enumerating hosts prior to scanning, we will be unable to retain visibility into the overall security of Internet-connected devices in the future, and we will be unable to detect and prevent their abuse or compromise. To mitigate this blind spot, we introduce a novel technique to enumerate part of the IPv6 address space by walking DNSSEC-signed IPv6 reverse zones. We show (i) that enumerating active IPv6 hosts is practical without a preferential network position contrary to common belief, (ii) that the security of active IPv6 hosts is currently still lagging behind the security state of IPv4 hosts, and (iii) that unintended default IPv6 connectivity is a major security issue

Network-based APT profiler

Constant innovation in attack methods presents a significant problem for the security community which struggles to remain current in attack prevention, detection and response. The practice of threat hunting provides a proactive approach to identify and mitigate attacks in real-time before the attackers complete their objective. In this research, I present a matrix of adversary techniques inspired by MITRE’s ATT&CK matrix. This study allows threat hunters to classify the actions of advanced persistent threats (APTs) according to network-based behaviors

The effects of security protocols on cybercrime at Ahmadu Bello University, Zaria, Nigeria.

Masters Degree. University of KwaZulu-Natal, Durban.The use of Information Communication Technology (ICT) within the educational sector is increasing rapidly. University systems are becoming increasingly dependent on computerized information systems (CIS) in order to carry out their daily routine. Moreover, CIS no longer process staff records and financial data only, as they once did. Nowadays, universities use CIS to assist in automating the overall system. This automation includes the use of multiple databases, data detail periodicity (i.e. gender, race/ethnicity, enrollment, degrees granted, and program major), record identification (e.g. social security number ‘SSN’), linking to other databases (i.e. linking unit record data with external databases such as university and employment data). The increasing demand and exposure to Internet resources and infrastructure by individuals and universities have made IT infrastructure easy targets for cybercriminals who employ sophisticated attacks such as Advanced Persistent Threats, Distributed Denial of Service attacks and Botnets in order to steal confidential data, identities of individuals and money. Hence, in order to stay in business, universities realise that it is imperative to secure vital Information Systems from easily being exploited by emerging and existing forms of cybercrimes. This study was conducted to determine and evaluate the various forms of cybercrimes and their consequences on the university network at Ahmadu Bello University, Zaria. The study was also aimed at proposing means of mitigating cybercrimes and their effects on the university network. Hence, an exploratory research design supported by qualitative research approach was used in this study. Staff of the Institute of Computing, Information and Communication technology (ICICT) were interviewed. The findings of the study present different security measures, and security tools that can be used to effectively mitigate cybercrimes. It was found that social engineering, denial of service attacks, website defacement were among the types of cybercrimes occurring on the university network. It is therefore recommended that behavioural approach in a form of motivation of staff behaviour, salary increases, and cash incentive to reduce cybercrime perpetrated by these staff

Resistance through the Temporality, Placement, and Modification of Street Art in Scotland’s Streets

ACKNOWLEDGEMENTSSpecial thanks to my wife, Jodi Le Bigre, for her patience and collaboration in my documentary efforts. For the Lockdown Lore Collection Project, I am particularly indebted to my colleagues at the Elphinstone Institute, Universi-ty of Aberdeen: Alison Sharman, Simon Gall, Carley Williams, Sheila Young, Frances Wilkins, and Thomas A. McKean.Peer reviewedPublisher PD

Political Expression in Web Defacements

The idea of influencing public opinion through digital media is ubiquitous, yet little is known about its origins. This thesis investigates the use of political communication through hacked websites. It is at the same time an exploratory description of the research tools and methods needed to find and retrieve such material. The dissertation frames political expression through hacking as interference with the strata of digital communication and positions it within a larger history of on- and offline activist practices. The methodological section describes the difficulties of finding and accessing defaced pages, which are almost exclusively held by community-based archives. Based on already available and added metadata, the dataset of defacements is surveyed and topics, periods of high activity and prominent defacer groups are identified. Modes of expression are tracked to give insight to possible defacer motivation. This survey then serves as the basis for the following analysis of two emblematic clusters of activity: The Kashmir conflict and the 9/11 attacks. In a close reading of selected defacements, communication strategies and general types of defacements are described, thereby showcasing the diversity of defacer standpoints and strategies which runs counter to the common uniform depiction of hackers. The notion of defacements as forced injection of material into a public sphere is discussed throughout these close readings and leads to the final analytical section discussing the relation between defacements and WikiLeaks. After reflecting on the themes that unite this dissertation, the conclusion reflects on the preservation and availability of source material on defaced pages. The author expresses the hope that both the research methodology as well as the applied analyses will promote the understanding of web defacements as a resource for inquests into online political expression