Category Archives: Three Paper Thursday

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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Three paper Thursday: Online Extremism and Radicalisation

With the recent United States presidential election, I have chosen to focus the theme of this Three Paper Thursday on extremism and radicalisation. This topic has got increasing media attention during the past six years in the United States, through both a general rise in the public prominence of far-right, racist rhetoric in political culture (often attributed to the Trump presidency), and a series of high-profile violent events associated with far-right extremism. These events range from the riots in Charlottesville, Virginia (which turned violent when rally attendees clashed with counter-protesters and a vehicle drove into a crowd marching through downtown, killing one protester (Heim, Silverman, Shapiro, & Brown, 2017), to the recent arrest of individuals plotting a kidnap of the Governor of Michigan. This far-right violence brought to light the continued existence of right-wing extremism in the United States. This has historical roots in well-known organisations such as the Ku Klux Klan (KKK), a secretive, racist, terrorist organisation founded in 1865 during Reconstruction as part of a backlash against the acquisition of civil rights by African-American people in the South (Bowman-Grieve, 2009; Martin, 2006).

In contemporary online societies, the landscape and dynamics of right-wing extremist communities have changed. These communities have learned how to exploit the capacities of online social networks for recruitment, information sharing, and community building. The sophistication and reach of online platforms has evolved rapidly from the bulletin board system (BBS) to online forums and now social media platforms, which incorporate powerful technologies for marketing, targeting, and disseminating information. However, the use of these platforms for right-wing radicalisation (the process through which an individual develops and/or accepts extreme ideologies and beliefs) remains under-examined in academic scholarship. This Three Paper Thursday pulls together some key current literature on radicalisation in online contexts.

Maura Conway, Determining the role of the internet in violent extremism and terrorism: Six suggestions for progressing research. Studies in Conflict & Terrorism, 40(1), 77-98. https://www.tandfonline.com/doi/full/10.1080/1057610X.2016.1157408.

The first paper comments on future directions for research in understanding and determining the role of the Internet in violent extremism and terrorism. After guiding readers through an overview of current research, the author argues that there is a lack of both descriptive and explanatory work on the topic, as the field remains divided. Some view Internet as mere speech platforms and argue that participation in online radicalised communities is often the most extreme behaviour in which most individuals engage. Others acknowledge the affordances of the Internet but are uncertain in its role in replacing or strengthening other radicalisation processes. The author concludes that two major research questions remain to be answered: whether radicalisation can occur in a purely online context, and if so, does it contribute to violence? In that case, the mechanisms merit further exploration. The author makes six suggestions for future researchers: a) widening current research to include movements beyond jihadism, b) conducting comparison research (e.g., between platforms and/or organisations), c) studying individual users in extremist communities and groups, d) using large-scale datasets, e) adopting an interdisciplinary approach, and f) examining the role of gender.

Yi Ting Chua, Understanding radicalization process in online far-right extremist forums using social influence model. PhD thesis, Michigan State University, 2019. Available from https://d.lib.msu.edu/etd/48077.

My doctoral dissertation examines the impact of participation in online far-right extremist groups on radicalisation. In this research, I applied social network analysis and integrated theories from criminology (social learning theory) and political science (the idea of the echo chamber) to understand the process of attitudinal changes within social networks. It draws on a longitudinal database of threads saved from eight online far-right extremist forums. With the social influence model, which is a regression model with a network factor, I was able to include the number of interactions and attitudinal beliefs of user pairs when examining attitudinal changes across time. This model allows us to determine if, and how, active interactions result in expression of more radical ideological beliefs. Findings suggested that online radicalisation occurred at varying degrees in six of seven forums, with a general lowered level of expressed extremism towards the end of observed time period. The study found strong support the proposition that active interactions with forum members and connectedness are predictors of radicalisation, while suggesting that other mechanisms, such as self-radicalisation and users’ prior beliefs, were also important. This research highlighted the need for theory integration, detailed measures of online peer association, and cross-platform comparisons (i.e. Telegram and Gab) to address the complex phenomena of online radicalisation.

Magdalena Wojcieszak, ‘Don’t talk to me’: effects of ideologically homogeneous online groups and politically dissimilar offline ties on extremism. New Media & Society, 12(4) (2010) pp 637-655. https://journals.sagepub.com/doi/abs/10.1177/1461444809342775.

In this article, the author is interested in answering two questions: 1) does participation in ideologically homogeneous online groups increase extreme beliefs, and 2) how do offline strong and weak ties with dissimilar beliefs affect extreme beliefs? The author uses online survey data and posts from neo-Nazi online forums. The outcome is measured by respondents’ responses to 10 ideology-specific statements. Other variables in the analysis included the level of participation in online groups, perceived dissimilarity of offline ties, news media exposure and demographics. Findings from a multivariate regression model indicate that participation in online groups was a strong predictor of support for racial violence after controlling for demographic factors and news media exposure. Forum members’ attitudes are subjected to normative influences via punitive or rewarding replies. For individuals with politically dissimilar offline ties, the author finds a weakened participation effect.

Together, these papers highlight the complexity of assessing the role played by the Internet in the radicalisation process. The first paper encourages researchers to tackle whether online violent radicalisation occurs via six different approaches. The other two papers show support for online radicalisation while simultaneously calling attention to the effect of other variables, such as the influence of offline relationships and users’ baseline beliefs prior to online participation. All of these papers cross academic disciplines, highlighting the importance of an interdisciplinary perspective.

References

Bowman-Grieve, L. (2009). Exploring “Stormfront”: A virtual community of the radical right. Studies in Conflict & Terrorism, 32(11), 989-1007.

Heim, J., Silverman, E., Shapiro, T. R., Brown, E. (2017, August 13). One dead as car strikes crowds amid protests of white nationalist gathering in Charlottesville; two police die in helicopter crash. The Washington Post. Retrieved from https://www.washingtonpost.com/local/fights-in-advance-of-saturday-protest-in-charlottesville/2017/08/12/155fb636-7f13-11e7-83c7-5bd5460f0d7e_story.html?utm_term=.33b6686c7838.

Martin, G. (2006). Understanding Terrorism: Challenges, Perspectives, and Issues. Thousand Oaks, California: Sage Publications.

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: Applying natural language processing to underground forums

Underground forums contain discussions and advertisements of various topics, including general chatter, hacking tutorials, and sales of items on marketplaces. While off-the-shelf natural language processing (NLP) techniques may be applied in this domain, they are often trained on standard corpora such as news articles and Wikipedia. 

It isn’t clear how well these models perform with the noisy text data found on underground forums, which contains evolving domain-specific lexicon, misspellings, slang, jargon, and acronyms. I explored this problem with colleagues from the Cambridge Cybercrime Centre and the Computer Laboratory, in developing a tool for detecting bursty trending topics using a Bayesian approach of log-odds. The approach uses a prior distribution to detect change in the vocabulary used in forums, for filtering out consistently used jargon and slang. The paper has been accepted to the 2020 Workshop on Noisy User-Generated Text (ACL) and the preprint is available online.

Other more commonly used approaches of identifying known and emerging trends range from simple keyword detection using a dictionary of known terms, to statistical methods of topic modelling including TF-IDF and Latent Dirichlet Allocation (LDA). In addition, the NLP landscape has been changing over the last decade [1], with a shift to deep learning using neural models, such as word2vec and BERT.

In this Three Paper Thursday, we look at how past papers have used different NLP approaches to analyse posts in underground forums, from statistical techniques to word embeddings, for identifying and define new terms, generating relevant warnings even when the jargon is unknown, and identifying similar threads despite relevant keywords not being known.

[1] Gregory Goth. 2016. Deep or shallow, NLP is breaking out. Commun. ACM 59, 3 (March 2016), 13–16. DOI:https://doi.org/10.1145/2874915

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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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Reinforcement Learning and Adversarial thinking

We all know that learning a new craft is hard. We spend a large part of our lives learning how to operate in everyday physics.  A large part of this learning comes from observing others, and when others can’t help we learn through trial and error. 

In machine learning the process of learning how to deal with the environment is called Reinforcement Learning (RL). By continuous interaction with its environment, an agent learns a policy that enables it to perform better. Observational learning in RL is referred to as Imitation Learning. Both trial and error and imitation learning are hard: environments are not trivial, often you can’t tell the ramifications of an action until far in the future, environments are full of non-determinism and there are no such thing as a correct policy. 

So, unlike in supervised and unsupervised learning, it is hard to tell if your decisions are correct. Episodes usually constitute thousands of decisions, and you will only know if you perform well after exploring other options. But experiment is also a hard decision: do you exploit the skill you already have, or try something new and explore the unknown?

Despite all these complexities, RL has managed to achieve incredible performance in a wide variety of tasks from robotics through recommender systems to trading. More impressively, RL agents have achieved superhuman performance in Go and other games, tasks previously believed to be impossible for computers. 

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Three paper Thursday: Ethics in security research

Good security and cybercrime research often creates an impact and we want to ensure that impact is positive. This week I will discuss three papers on ethics in computer security research in the run up to next week’s Security and Human Behaviour workshop (SHB). Ethical issues in research using datasets of illicit origin (Thomas, Pastrana, Hutchings, Clayton, Beresford) from IMC 2017, Measuring eWhoring (Pastrana, Hutchings, Thomas, Tapiador) from IMC 2019, and An Ethics Framework for Research into Heterogeneous Systems (Happa, Nurse, Goldsmith, Creese, Williams).

Ethical issues in research using datasets of illicit origin (blog post) came about because in prior work we had noticed that there were ethical complexities to take care of when using data that had “fallen off the back of a lorry” such as the backend databases of hacked booter services that we had used. We took a broad look at existing published guidance to synthesise those issues which particularly apply to using data of illicit origin and we expected to see discussed by researchers:

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Three Paper Thursday – Analysing social networks within underground forums

One would be hard pressed to find an aspect of life where networks are not present. Interconnections are at the core of complex systems – such as society, or the world economy – allowing us to study and understand their dynamics. Some of the most transformative technologies are based on networks, be they hypertext documents making up the World Wide Web, interconnected networking devices forming the Internet, or the various neural network architectures used in deep learning. Social networks that are formed based on our interactions play a central role in our every day lives; they determine how ideas and knowledge spread and they affect behaviour. This is also true for cybercriminal networks present on underground forums, and social network analysis provides valuable insights to how these communities operate either on the dark web or the surface web.

For today’s post in the series `Three Paper Thursday’, I’ve selected three papers that highlight the valuable information we can learn from studying underground forums if we model them as networks. Network topology and large scale structure provide insights to information flow and interaction patterns. These properties along with discovering central nodes and the roles they play in a given community are useful not only for understanding the dynamics of these networks but for various purposes, such as devising disruption strategies.

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Three Paper Thursday: Vulnerabilities! We’ve got vulnerabilities here! … See? Nobody cares.

Jurassic Park is often (mistakenly) left out of the hacker movie canon. It clearly demonstrated the risk of an insider attack on control systems (Velociraptor rampage, amongst other tragedies…) nearly a decade ahead of the Maroochy sewage incident, it’s the first film I know of with a digital troll (“ah, ah, ah, you didn’t say the magic word!”), and Samuel L. Jackson correctly assesses the possible consequence of a hard reset (namely, everyone dying), resulting in his legendary “Hold on to your butts”. The quotable mayhem is seeded early in the film, when biotech spy Lewis Dodgson gives a sack of money to InGen’s Dennis Nedry to steal some dino DNA. Dodgson’s caricatured OPSEC (complete with trilby and dark glasses) is mocked by Nedry shouting, “Dodgson! Dodgson! We’ve got Dodgson here! See, nobody cares…” Three decades later, this quote still comes to mind* whenever conventional wisdom doesn’t seem to square with observed reality, and today we’re going to apply it to the oft-maligned world of Industrial Control System (ICS) security.

There is plenty of literature on ICS security pre-2010, but people really sat up and started paying attention when we learned about Stuxnet. Possibly the most upsetting thing about Stuxnet (for security-complacent control system designers like me) was the apparent ease with which the “air gap” was bridged over and over again. Any remaining faith in the air gap was killed by Éireann Leverett’s demonstration (thesis and S4 presentation) that thousands of industrial systems were directly connected to the Internet — no air gap jumping required. Since then, we’ve observed a steady growth in Internet-connected ICS devices, due both to improved search techniques and increasingly-connectable ICS devices. On any given day you can find about 100,000 unique devices speaking industrial protocols on Censys and Shodan. These protocols are largely unauthenticated and unencrypted, allowing an attacker that can speak the protocol to remotely read state, issue commands, and even modify programmable logic without using an actual exploit.

This sounds (and is) bad, and people have (correctly) highlighted its badness on many occasions. The attacks, however, appear to be missing: we are not aware of a single instance of industrial damage initiated via an Internet-connected ICS device. In this Three Paper Thursday we’ll look at papers showing how easy it is to find and contextualise Internet-connected ICS devices, some evidence for lack of malicious interest, and some leading indicators that this happy conclusion (for which we don’t really deserve any credit) may be changing.

*Perhaps because guys of a certain age still laugh and say “Dodson! We’ve got Dodson here!” when they learn my surname. I try to explain that it’s spelt differently, but…
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