Category Archives: Academic papers

Three Paper Thursday: Subverting Neural Networks via Adversarial Reprogramming

This is a guest post by Alex Shepherd.

Five years after Szegedy et al. demonstrated the capacity for neural networks to be fooled by crafted inputs containing adversarial perturbations, Elsayed et al. introduced adversarial reprogramming as a novel attack class for adversarial machine learning. Their findings demonstrated the capacity for neural networks to be reprogrammed to perform tasks outside of their original scope via crafted adversarial inputs, creating a new field of inquiry for the fields of AI and cybersecurity.

Their discovery raised important questions regarding the topic of trustworthy AI, such as what the unintended limits of functionality are in machine learning models and whether the complexity of their architectures can be advantageous to an attacker. For this Three Paper Thursday, we explore the three most eminent papers concerning this emerging threat in the field of adversarial machine learning.

Adversarial Reprogramming of Neural Networks, Gamaleldin F. Elsayed, Ian Goodfellow, and Jascha Sohl-Dickstein, International Conference on Learning Representations, 2018.

In their seminal paper, Elsayed et al. demonstrated their proof-of-concept for adversarial reprogramming by successfully repurposing six pre-trained ImageNet classifiers to perform three alternate tasks via crafted inputs containing adversarial programs. Their threat model considered an attacker with white-box access to the target models, whose objective was to subvert the models by repurposing them to perform tasks they were not originally intended to do. For the purposes of their hypothesis testing, adversarial tasks included counting squares and classifying MNIST digits and CIFAR-10 images.
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Friendly neighbourhood cybercrime: online harm in the pandemic and the futures of cybercrime policing

As cybercrime researchers we’re often focused on the globalised aspects of online harms – how the Internet connects people and services around the world, opening up opportunities for crime, risk, and harm on a global scale. However, as we argue in open access research published this week in the Journal of Criminal Psychology in collaboration between the Cambridge Cybercrime Centre (CCC), Edinburgh Napier University, the University of Edinburgh, and Abertay University, as we have seen an enormous rise in reported cybercrime in the pandemic, we have paradoxically seen this dominated by issues with a much more local character. Our paper sketches a past: of cybercrime in a turbulent 2020, and a future: of the roles which state law enforcement might play in tackling online harm a post-pandemic world.

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An exploration of the cybercrime ecosystem around Shodan

By Maria Bada & Ildiko Pete

Internet of Things (IoT) solutions, which have permeated our everyday life, present a wide attack surface. They are present in our homes in the form of smart home solutions, and in industrial use cases where they provide automation. The potentially profound effects of IoT attacks have attracted much research attention. We decided to analyse the IoT landscape from a novel perspective, that of the hacking community. 

Our recent paper published at the 7th IEEE International Conference on Internet of Things: Systems, Management and Security (IOTSMS 2020) presents an analysis of underground forum discussions around Shodan, one of the most popular search engines of Internet facing devices and services. In particular, we explored the role Shodan plays in the cybercriminal ecosystem of IoT hacking and exploitation, the main motivations of using Shodan, and popular targets of exploits in scenarios where Shodan is used. 

To answer these questions, we followed a qualitative approach and performed a thematic analysis of threads and posts extracted from 19 underground forums presenting discussions from 2009 to 2020. The data were extracted from the CrimeBB dataset, collected and made available to researchers through a legal agreement by the Cambridge Cybercrime Centre (CCC). Specifically, the majority of posts we analysed stem from Hackforums (HF), one of the largest general purpose hacking forums covering a wide range of topics, including IoT. HF is also notable for being the platform where the source code of the Mirai malware was released in 2016 (Chen and Y. Luo, 2017). 

 The analysis revealed that Shodan provides easier access to targets and simplifies IoT hacking. This is demonstrated for example by discussions that centre around selling and buying Shodan exports, search results that can be readily used to target vulnerable devices and services. Forum members also expressed this view directly:

‘… Shodan and other tools, such as exploit-db make hacking almost like a recipe that you can follow.’

From the perspective of hackers a significant factor determining the utility of Shodan is if those targets can indeed be utilised. For example, whether all scanned hosts in scan results are active and whether they can be used for exploitation. Thus, the value of Shodan as a hacking tool is determined by its intended use cases.

The discussions were ripe with tutorials on various aspects of hacking, which provided a glimpse into the methodology of hacking in general, hacking IoT devices, and the role Shodan plays in IoT attacks.  The discussions show that Shodan and similar tools, such as Censys and Zoomeye, play a key role in passive information gathering and reconnaissance. The majority of users agree that Shodan provides value and is a useful tool and do suggest its use. They mention Shodan both in the context of searching for targets and exploiting devices or services with known vulnerabilities. As to the targets of information gathering and exploitation, we found multiple devices and services, including web cameras, industrial control systems, open databases, to mention a few.

Shodan is a versatile tool and plays a prominent role in various use cases. Since IoT devices can potentially expose personally identifiable information, such as health records, user names and passwords, members of underground forums actively discuss utilising Shodan for gathering such data. In particular, this can be achieved by exploiting open databases.

Members of forums discuss accessing remote devices for various reasons. In some cases, it is for fun, while more maliciously inclined actors can use such exploits to collect images and videos and use them in for example extortion use cases. Previous research has shown that camera systems represent easy targets for hackers. Accordingly, our findings highlight that these systems are one of the most popular targets, and they are widely discussed in the context of watching the video stream or listening to the audio stream of a compromised vulnerable cameras, or exposing someone through their camera recording. Users frequently discuss IP camera trolling, and we found posts sharing leaked video footage and websites that list hacked cameras. 

Shodan, and in particular the Shodan API can be used to automate scanning for devices which could be used to create a botnet:

…you don’t need fancy exploits to get bots just look for bad configurations on shodan.’

And finally, a major use case member discusses utilising Shodan in Distributed Reflection Denial of Service attacks, and specifically in the first step where Shodan can be used to gather a list of reflectors, for example, NTP servers.

 Discussions around selling or buying Shodan accounts show that forum members trade these accounts and associated assets due to Shodan’s credit model, which limits its use. To effectively utilise the output of Shodan queries, premium accounts are required as they provide the necessary scan, query and export credits.

Although Shodan and other search engines alike attract malicious actors, they are widely used by security professionals and for penetration testing to unveil IoT security issues. Raising awareness of vulnerabilities provides invaluable help in alleviating these issues. Shodan provides a variety of services, including Malware Hunter, which is a specialised Shodan crawler aimed at discovering malware command-and-control (CC) servers. The service is of great value to security professionals and in the fight against malware reducing its impact and ability to compromise targeted victims. This study contributes to IoT security research by highlighting the need for action towards securing the IoT ecosystem based on forum members’ discussions on underground forums. The findings suggest that more focus needs to be placed upon the security considerations while developing IoT devices, as a measure to prevent their malicious use.

Reference

F. Chen and Y. Luo, Industrial IoT Technologies and Applications: Second EAI International Conference, Industrial IoT 2017, Wuhu, China, March 25–26, 2017, Proceedings, ser. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2017.

Pushing the limits: acoustic side channels

How far can we go with acoustic snooping on data?

Seven years ago we showed that you could use a phone camera to measure the phone’s motion while typing and use that to recover PINs. Four years ago we showed that you could use interrupt timing to recover text entered using gesture typing. Last year we showed how a gaming app can steal your banking PIN by listening to the vibration of the screen as your finger taps it. In that attack we used the on-phone microphones, as they are conveniently located next to the screen and can hear the reverberations of the screen glass.

This year we wondered whether voice assistants can hear the same taps on a nearby phone as the on-phone microphones could. We knew that voice assistants could do acoustic snooping on nearby physical keyboards, but everyone had assumed that virtual keyboards were so quiet as to be invulnerable.

Almos Zarandy, Ilia Shumailov and I discovered that attacks are indeed possible. In Hey Alexa what did I just type? we show that when sitting up to half a meter away, a voice assistant can still hear the taps you make on your phone, even in presence of noise. Modern voice assistants have two to seven microphones, so they can do directional localisation, just as human ears do, but with greater sensitivity. We assess the risk and show that a lot more work is needed to understand the privacy implications of the always-on microphones that are increasingly infesting our work spaces and our homes.

Three Paper Thursday: Vēnī, Vīdī, Vote-y – Election Security

With the recent quadrennial instantiation of the US presidential election, discussions of election security have predictably resurged across much of the world. Indeed, news cycles in the US, UK, and EU abound with talking points surrounding the security of elections. In light of this context, we will use this week’s Three Paper Thursday to shed light on the technical challenges, solutions, and opportunities in designing secure election systems.

This post will focus on the technical security of election systems. That said, the topic of voter manipulation techniques such as disinformation campaigns, although out of scope here, is also an open area of research.

At first glance, voting may not seem like a challenging problem. If we are to consider a simple majority vote, surely a group of young schoolchildren could reach a consensus in minutes via hand-raising. Striving for more efficient vote tallying, though, perhaps we may opt to follow the IETF in consensus through humming. As we seek a solution that can scale to large numbers of voters, practical limitations will force us to select a multi-location, asynchronous process. Whether we choose in-person polling stations or mail-in voting, challenges quickly develop: how do we know a particular vote was counted, its contents kept secret, and the final tally correct?

National Academies of Sciences, Engineering, and Medicine (U.S.), Ed., Securing the vote: protecting American democracy, The National Academies Press (2018)

The first paper is particularly prominent due to its unified, no-nonsense, and thorough analysis. The report is specific to the United States, but its key themes apply generally. Written in response to accusations of international interference in the US 2016 presidential election, the National Academies provide 41 recommendations to strengthen the US election system.

These recommendations are extremely straightforward, and as such a reminder that adversaries most often penetrate large systems by targeting the “weakest link.” Among other things, the authors recommend creating standardized ballot data formats, regularly validating voter registration lists, evaluating the accessibility of ballot formats, ensuring access to absentee ballots, conducting appropriate audits, and providing adequate funding for elections.

It’s important to get the basics right. While there are many complex, stimulating proposals that utilize cutting-edge algorithms, cryptography, and distributed systems techniques to strengthen elections, many of these proposals are moot if the basic logistics are mishandled.

Some of these low-tech recommendations are, to the surprise of many passionate technologists, quite common among election security specialists. For example, requiring a paper ballot trail and avoiding internet voting based on current technology is also cited in our next paper.

Matthew Bernhard et al., Public Evidence from Secret Ballots, arXiv:1707.08619 (2017)

Governance aside, the second paper offers a comprehensive survey of the key technical challenges in election security and common tools used to solve them. The paper motivates the difficulty of election systems by attesting that all actors involved in an election are mutually distrustful, meaningful election results require evidence, and voters require ballot secrecy.

Ballot secrecy is more than a nicety; it is key to a properly functioning election system. Implemented correctly, ballot secrecy prevents voter coercion. If a voter’s ballot is not secret, or indeed if there is any way a voter can post-facto prove the casting a certain vote, malicious actors may pressure the voter to provide proof that they voted as directed. This can be insidiously difficult to prevent if not considered thoroughly.

Bernhard et al. discuss risk-limiting audits (RLAs) as an efficient yet powerful way to limit uncertainty in election results. By sampling and recounting a subset of votes, RLAs enable the use of statistical methods to increase confidence in a correct ballot count. Employed properly, RLAs can enable the high-probability validation of election tallies with effort inversely proportional to the expected margin. RLAs are now being used in real-world elections, and many RLA techniques exist in practice. 

Refreshingly, this paper establishes that blockchain-based voting is a bad idea. Blockchains inherently lack a central authority, so enforcing election rules would be a challenge. Furthermore, a computationally powerful adversary could control which votes get counted.

The paper also discusses high-level cryptographic tools that can be useful in elections. This leads us to our third and final paper.

Josh Benaloh, ElectionGuard Specification v0.95, Microsoft GitHub (2020)

Our final paper is slightly different from the others in this series; it’s a snapshot of a formal specification that is actively being developed, largely based on the author’s 1996 Yale doctoral thesis.

The specification describes ElectionGuard, a system being built by Microsoft to enable verifiable election results (disclaimer: the author of this post holds a Microsoft affiliation). It uses a combination of exponential ElGamal additively-homomorphic encryption, zero knowledge proofs, and Shamir’s secret sharing to conduct publicly-verifiable, secret-ballot elections.

When a voter casts a ballot, they are given a tracking code which can be used to verify the counting of the ballot’s votes via cryptographic proofs published with the final tally. Voters can achieve high confidence that their ballot represents a proper encryption of their desired votes by optionally spoiling an unlimited number of ballots triggering a decryption of the spoiled ballot at the time of voting. Encrypted ballots are homomorphically tallied in encrypted form by the election authorities, and the number of authorities that participate in tallying must meet the threshold set for the election to protect against malicious authorities.

The specification does not require that the system be used for exclusively internet-based or polling station-based elections; rather it is a framework for users to consume as they wish. Indeed, one of the draws to ElectionGuard is that it does not mandate a specific UI, ballot marking device, or even API. This flexibility allows election authorities to leverage the system in the manner that best fits their jurisdiction. The open source implementation can be found on GitHub.

There are many pieces of voting software available, but ElectionGuard is the new kid on the block that addresses many of the concerns raised in our earlier papers.

Key Themes

Designing secure election systems is difficult.

Often, election systems fall short on the basics; improper voting lists, postage issues, and poorly formatted ballots can disrupt elections as much as some adversaries. Ensuring that the foundational components of an election are handled well currently involves seemingly mundane but important things such as paper ballot trails, chains of custody, and voter ID verification.

High-tech election proposals are not new; indeed key insights into the use of cryptographic techniques in elections were being discussed in the academic literature well over two decades ago. That said, in recent years there has been an ostensibly increased investment in implementing cryptographic election systems, and although there remain many problems to be solved the future in this area looks promising.

Three Paper Thursday: Attacking Machine Vision Models In Real Life

This is a guest post by Alex Shepherd.

There is a growing body of research literature concerning the potential threat of physical-world adversarial attacks against machine-vision models. By applying adversarial perturbations to physical objects, machine-vision models may be vulnerable to images containing these perturbed objects, resulting in an increased risk of misclassification. The potential impacts could be significant and have been identified as risk areas for autonomous vehicles and military UAVs.

For this Three Paper Thursday, we examine the following papers exploring the potential threat of physical-world adversarial attacks, with a focus on the impact for autonomous vehicles.

Alexey Kurakin, Ian Goodfellow, and Samy Bengio. Adversarial examples in the physical world, arXiv:1607.02533 (2016)

In this seminal paper, Kurakin et al. report their findings of an experiment conducted using adversarial images taken from a phone camera as input for a pre-trained ImageNet Inceptionv3 image classification model. Methodology was based on a white-box threat model, with adversarial images crafted from the ImageNet validation dataset using the Inceptionv3 model.
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SHB Seminar

The SHB seminar on November 5th was kicked off by Tom Holt, who’s discovered a robust underground market in identity documents that are counterfeit or fraudulently obtained. He’s been scraping both websites and darkweb sites for data and analysing how people go about finding, procuring and using such credentials. Most vendors were single-person operators although many operate within affiliate programs; many transactions involved cryptocurrency; many involve generating pdfs that people can print at home and that are good enough for young people to drink alcohol. Curiously, open web products seem to cost twice as much as dark web products.

Next was Jack Hughes, who has been studying the contract system introduced by hackforums in 2018 and made mandatory the following year. This enabled him to analyse crime forum behaviour before and during the covid-19 era. How do new users become active, and build up trust? How does it evolve? He collected 200,000 transactions and analysed them. The contract mandate stifled growth quickly, leading to a first peak; covid caused a second. The market was already centralised, and became more so with the pandemic. However contracts are getting done faster, and the main activity is currency exchange: it seems to be working as a cash-out market.

Anita Lavorgna has been studying the discourse of groups who oppose public mask mandates. Like the antivaxx movement, this can draw in fringe groups and become a public-health issue. She collected 23654 tweets from February to June 2020. There’s a diverse range of voices from different places on the political spectrum but with a transversal theme of freedom from government interference. Groups seek strength in numbers and seek to ally into movements, leading to the mask becoming a symbol of political identity construction. Anita found very little interaction between the different groups: only 144 messages in total.

Simon Parkin has been working on how we can push back on bad behaviours online while they are linked with good behaviours that we wish to promote. Precision is hard as many of the desirable behaviours are not explicitly recognised as such, and as many behaviours arise as a combination of personal incentives and context. The best way forward is around usability engineering – making the desired behaviours easier.

Bruce Schneier was the final initial speaker, and his topic was covid apps. The initial rush of apps that arrived in March through June have known issues around false positives and false negatives. We’ve also used all sorts of other tools, such as analysis of Google maps to measure lockdown compliance. The third thing is the idea of an immunity passport, saying you’ve had the disease, or a vaccine. That will have the same issues as the fake IDs that Tom talked about. Finally, there’s compliance tracking, where your phone monitors you. The usual countermeasures apply: consent, minimisation, infosec, etc., though the trade-offs might be different for a while. A further bunch of issues concern home working and the larger attack surface that many firms have as a result of unfamiliar tools, less resistance to being tols to do things etc.

The discussion started on fake ID; Tom hasn’t yet done test purchases, and might look at fraudulently obtained documents in the future, as opposed to completely counterfeit ones. Is hackforums helping drug gangs turn paper into coin? This is not clear; more is around cashing out cybercrime rather than street crime. There followed discussion by Anita of how to analyse corpora of tweets, and the implications for policy in real life. Things are made more difficult by the fact that discussions drift off into other platforms we don’t monitor. Another topic was the interaction of fashion: where some people wear masks or not as a political statement, many more buy masks that get across a more targeted statement. Fashion is really powerful, and tends to be overlooked by people in our field. Usability research perhaps focuses too much on the utilitarian economics, and is a bit of a blunt instrument. Another example related to covid is the growing push for monitoring software on employees’ home computers. Unfortunately Uber and Lyft bought a referendum result that enables them to not treat their staff in California as employees, so the regulation of working hours at home will probably fall to the EU. Can we perhaps make some input into what that should look like? Another issue with the pandemic is the effect on information security markets: why should people buy corporate firewalls when their staff are all over the place? And to what extent will some of these changes be permanent, if people work from home more? Another thread of discussion was how the privacy properties of covid apps make it hard for people to make risk-management decisions. The apps appear ineffective because they were designed to do privacy rather than to do public health, in various subtle ways; giving people low-grade warnings which do not require any action appear to be an attempt to raise public awareness, like mask mandates, rather than an effective attempt to get exposed individuals to isolate. Apps that check people into venues have their own issues and appear to be largely security theatre. Security theatre comes into its own where the perceived risk is much greater than the actual risk; covid is the opposite. What can be done in this case? Targeted warnings? Humour? What might happen when fatigue sets in? People will compromise compliance to make their lives bearable. That can be managed to some extent in institutions like universities, but in society it will be harder. We ended up with the suggestion that the next SHB seminar should be in February, which should be the low point; after that we can look forward to things getting better, and hopefully to a meeting in person in Cambridge on June 3-4 2021.

How an Illicit Cybercrime Market Evolves: A Longitudinal Study

Online underground marketplaces are an essential part of the cybercrime economy. They often act as a cash-out market, enabling the trade in illicit goods and services between pseudonymous members. To understand their characteristics, previous research mostly uses vendor ratings, public feedback, sometimes private messages, friend status, and post content. However, most research lacks comprehensive (and important) data about transactions made by the forum members.

Our recent paper (original talk here) published at the Internet Measurement Conference (IMC’20) examines how an online illicit marketplace evolves over time (especially its performance as an infrastructure for trust), including a significant shift through the COVID-19 pandemic. This study draws insights from a novel, rich and powerful dataset containing hundreds of thousands contractual transactions made by members of HackForums — the most popular online cybercrime community. The data includes a two-year historical record of the contract system, originally adopted in June 2018 as an attempt to mitigate scams and frauds occurring between untrusted parties. As well as contractual arrangements, the dataset includes thousands of associated members, threads, posts on the forum, which provide additional context. To study the longitudinal maturation of this marketplace, we split the timespan into three eras: Set-up, Stable, and COVID-19. These eras are defined by two important external milestones: the enforcement of the new forum’s policy in March 2019, and the declaration of the global pandemic in March 2020.

We applied a range of analysis and statistical modelling approaches to outline the maturation of economic and social characteristics of the market since the day it was introduced. We find the market has centralised over time, with a small proportion of ‘power users’ involved in the majority of transactions. In term of trading activities, currency exchange and payments account for the largest proportion of both contracts and users involved, followed by giftcards and accounts/licenses. The other popular products include automated bots, hacking tutorials, remote access tools (RATs), and eWhoring packs. Contracts are settled faster over time, with the completion time dropping from around 70 hours in the early months to less than 10 hours during the COVID-19 Era in June 2020.

We quantitatively estimate a lower bound total trading value of over 6 million USD for public and private transactions. With regards to payment methods preferably used within the market, Bitcoin and PayPal dominate the others at all times in terms of both trading values and number of contracts involved. A subset of new members joining the market face the ‘cold start’ problem, which refers to the difficulties of how to establish and build up a reputation base while initially having no reputation. We find that the majority of these build up their profile by participating in low-level currency exchanges, while some instead establish themselves by offering products and services.

To examine the behaviours of members over time, we use Latent Transition Analysis to discover hidden groups among the forum’s members, including how members move between groups and how they change across the lifetime of the market. In the Set-up Era, we see users gradually shift to the new system with a large number of ‘small scale’ users involved in one-off transactions, and few ‘power-users’. In the Stable Era, we see a shift in the composition and scale of the market when contracts become compulsory, with a growth of ‘business-to-consumer’ trades by ‘power-users’. In the COVID-19 Era, the market further concentrates around already-existing ‘power-users’, who are party to multiple transactions with others.

Overall, the marketplace provides a range of trust capabilities to facilitate trade between pseudonymous parties with the control is becoming further centralised with administrators acting as third-party arbitrators. The platform is clearly being used as a cash-out market, with most trades involving the exchange of currencies. In term of the three eras, the big picture shows two significant rises in the market’s activities in response to two major events that happened at the beginning of Stable and COVID-19 eras. Particularly, we observe a stimulus (rather than transformation) in trading activities during the pandemic: the same kinds of transactions, users, and behaviours, but at increased volumes. By looking at the context of forum posts at that time, we see a period of mass boredom and economic change, when some members are no longer at school while others have become unemployed or are unable to go to work. A need to make money and the availability of time in their hand to do so may be a factor resulting in the increase of trading activities seen at this time.

Some limitations of our dataset include no ground truth verification, in which we have no way to verify if transactions actually proceed as set out in the contractual agreements. Furthermore, the dataset contains a large number of private contracts (around 88%), in which we only can observe minimal information. The dataset is available to academic researchers through the Cambridge Cybercrime Center‘s data-sharing agreements.

Three paper Thursday: COVID-19 and cybercrime

For a slightly different Three Paper Thursday, I’m pulling together some of the work done by our Centre and others around the COVID-19 pandemic and how it, and government responses to it, are reshaping the cybercrime landscape. 

The first thing to note is that there appears to be a nascent academic consensus emerging that the pandemic, or more accurately, lockdowns and social distancing, have indeed substantially changed the topology of crime in contemporary societies, leading to an increase in cybercrime and online fraud. The second is that this large-scale increase in cybercrime appears to be the result of a growth in existing cybercrime phenomena rather than the emergence of qualitatively new exploits, scams, attacks, or crimes. This invites reconsideration not only of our understandings of cybercrime and its relation to space, time, and materiality, but additionally to our understandings of what to do about it.

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Three Paper Thursday: Broken Hearts and Empty Wallets

This is a guest post by Cassandra Cross.

Romance fraud (also known as romance scams or sweetheart swindles) affects millions of individuals globally each year. In 2019, the Internet Crime Complaint Centre (IC3) (USA) had over US$475 million reported lost to romance fraud. Similarly, in Australia, victims reported losing over $AUD80 million and British citizens reported over £50 million lost in 2018. Given the known under-reporting of fraud overall, and online fraud more specifically, these figures are likely to only be a minority of actual losses incurred.

Romance fraud occurs when an offender uses the guise of a legitimate relationship to gain a financial advantage from their victim. It differs from a bad relationship, in that from the outset, the offender is using lies and deception to obtain monetary rewards from their partner. Romance fraud capitalises on the fact that a potential victim is looking to establish a relationship and exhibits an express desire to connect with someone. Offenders use this to initiate a connection and start to build strong levels of trust and rapport.

As with all fraud, victims experience a wide range of impacts in the aftermath of victimisation. While many believe these to be only financial, in reality, it extends to a decline in both physical and emotional wellbeing, relationship breakdown, unemployment, homelessness, and in extreme cases, suicide. In the case of romance fraud, there is the additional trauma associated with grieving both the loss of the relationship as well as any funds they have transferred. For many victims, the loss of the relationship can be harder to cope with than the monetary aspect, with victims experiencing large degrees of betrayal and violation at the hands of their offender.

Sadly, there is also a large amount of victim blaming that exists with both romance fraud and fraud in general. Fraud is unique in that victims actively participate in the offence, through the transfer of money, albeit under false pretences. As a result, they are seen to be culpable for what occurs and are often blamed for their own circumstances. The stereotype of fraud victims as greedy, gullible and naïve persists, and presents as a barrier to disclosure as well as inhibiting their ability to report the incident and access any support services.

Given the magnitude of losses and impacts on romance fraud victims, there is an emerging body of scholarship that seeks to better understand the ways in which offenders are able to successfully target victims, the ways in which they are able to perpetrate their offences, and the impacts of victimisation on the individuals themselves. The following three articles each explore different aspects of romance fraud, to gain a more holistic understanding of this crime type.

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