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NSW Electoral Commission claims physical separation mitigates Swiss voting flaw

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(Image: Joe McKendrick)

The NSW Electoral Commission (NSWEC) has claimed it is not impacted by the security issues that were disclosed about the Swiss e-voting system overnight, thanks to using an air-gapped machine, even though the flaw exists in its iVote system.

“The identification of this issue does not affect the use of iVote for the NSW State election,” the NSW Electoral Commission said in a statement.

As described by security researchers Sarah Jamie Lewis, Olivier Pereira, and Vanessa Teague, the flaw is found in the mixnet component that shuffles votes in an effort to remove the ability to link votes to individual electors.

“The implementation of the commitment scheme in the SwissPost-Scytl mixnet uses a trapdoor commitment scheme, which allows anyone who knows the trapdoor values to generate a shuffle-proof transcript that passes verification but actually alters votes,” the researchers said.

“This allows undetectable vote manipulation by an authority who implemented or administered a mix server.”

Must read: E-voting is still the wrong answer to the wrong question

However, the NSWEC claims it is unaffected because its mixnet is not connected to any systems, and is “securely housed” at the NSWEC.

“In order for this weakness to be an issue, a person would need to gain access to the physical machine. They would need all the right credentials and the right code to alter the software,” a spokesperson for NSWEC said.

“Our processes reduce this risk as we specifically separate the duties of people on the team and control access to the machine to reduce the potential for an insider attack.”

The electoral commission said Scytl is still delivering a patch for the flaw, and that it is confident in the security of iVote.

“iVote is an important voting channel to ensure equal access to democracy, particularly for people with disability and remote voters, and we will continue working to strengthen its operation,” the spokesperson said.

Tell ’em they’re dreaming: Australia Post details plan to use blockchain for voting

On Twitter, Lewis pointed out the high level of auditing the system was subjected to.

“I also think it’s very important that everyone who might find themselves in a nation implementing electronic voting is aware of how many audits, and public puffery the Swiss election system has gone through. It is very important you understand how well audited this system was,” the researcher said.

Two other researchers also discovered the mixnet flaw.

In 2015, Teague was part of a team that discovered iVote was susceptible to the FREAK vulnerability.

Once again, the findings appeared close to a week out from polling day.

“The commission has now had time to review the claims made by Dr Teague and Dr Halderman, and has received advice from our information security auditors,” the NSWEC said at the time. “The commission’s principal security advisers CSC Cyber Security ANZ noted that Dr Teague and Dr Halderman’s claims about the vulnerabilities in iVote are overstated.

Previously: NSW Electoral Commission scrambles to patch iVote flaw

“The proposed FREAK attack requires a high level of technical expertise and a number of pre-conditions to be successful, and as such is not considered a real threat to iVote. We have been advised that the likelihood of someone intercepting votes online using this approach is as real as a malicious postman replacing a postal vote.”

The similarities between the incidents do not end there, with Scytl questioning the motivation of the researchers, as the NSWEC did four years ago.

The iVote system has been subsequently used in elections in Western Australia.

Related Coverage

Online voting: Now Estonia teaches the world a lesson in electronic elections

In this month’s Estonian parliamentary elections, a whopping 44 percent of the ballot was cast using e-voting.

EU to tech giants: Step up fake news fight before European elections

Facebook, Google, Twitter and Mozilla have all made progress fighting disinformation campaigns, but they “need to go further and faster before May,” the European Commission warns.

Australian Electoral Commission wants money to fix ageing IT systems

The Australian Electoral Commission has said it needs money to update its election IT systems, warning that the existing ones are at the end of their useful life.

NSW iVote ballot mistake put down to human error

The NSW Electoral Commission’s CIO Ian Brightwell has said that human error was at the core of an electronic ballot problem on the NSW iVote system that may have the potential to see some of the results from last month’s state election thrown into question.



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Cloud Data Security

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Data security has become an immutable part of the technology stack for modern applications. Protecting application assets and data against cybercriminal activities, insider threats, and basic human negligence is no longer an afterthought. It must be addressed early and often, both in the application development cycle and the data analytics stack.

The requirements have grown well beyond the simplistic features provided by data platforms, and as a result a competitive industry has emerged to address the security layer. The capabilities of this layer must be more than thorough, they must also be usable and streamlined, adding a minimum of overhead to existing processes.

To measure the policy management burden, we designed a reproducible test that included a standardized, publicly available dataset and a number of access control policy management scenarios based on real world use cases we have observed for cloud data workloads. We tested two options: Apache Ranger with Apache Atlas and Immuta. This study contrasts the differences between a largely role-based access control model with object tagging (OT-RBAC) to a pure attribute-based access control (ABAC) model using these respective technologies.

This study captures the time and effort involved in managing the ever-evolving access control policies at a modern data-driven enterprise. With this study, we show the impacts of data access control policy management in terms of:

  • Dynamic versus static
  • Scalability
  • Evolvability

In our scenarios, Ranger alone took 76x more policy changes than Immuta to accomplish the same data security objectives, while Ranger with Apache Atlas took 63x more policy changes. For our advanced use cases, Immuta only required one policy change each, while Ranger was not able to fulfill the data security requirement at all.

This study exposed the limitations of extending legacy Hadoop security components into cloud use cases. Apache Ranger uses static policies in an OT-RBAC model for the Hadoop ecosystem with very limited support for attributes. The difference between it and Immuta’s attribute-based access control model (ABAC) became clear. By leveraging dynamic variables, nested attributes, and global row-level policies and row-level security, Immuta can be quickly implemented and updated in comparison with Ranger.

Using Ranger as a data security mechanism creates a high policy-management burden compared to Immuta, as organizations migrate and expand cloud data use—which is shown here to provide scalability, clarity, and evolvability in a complex enterprise’s data security and governance needs.

The chart in Figure 1 reveals the difference in cumulative policy changes required for each platform configuration.

Figure 1. Difference in Cumulative Policy Changes

The assessment and scoring rubric and methodology is detailed in the report. We leave the issue of fairness for the reader to determine. We strongly encourage you, as the reader, to discern for yourself what is of value. We hope this report is informative and helpful in uncovering some of the challenges and nuances of data governance platform selection. You are encouraged to compile your own representative use cases and workflows and review these platforms in a way that is applicable to your requirements.

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GigaOm Radar for Data Loss Prevention

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Data is at the core of modern business: It is our intellectual property, the lifeblood of our interactions with our employees, partners, and customers, and a true business asset. But in a world of increasingly distributed workforces, a growing threat from cybercriminals and bad actors, and ever more stringent regulation, our data is at risk and the impact of losing it, or losing access to it, can be catastrophic.

With this in mind, ensuring a strong data management and security strategy must be high on the agenda of any modern enterprise. Security of our data has to be a primary concern. Ensuring we know how, why, and where our data is used is crucial, as is the need to be sure that data does not leave the organization without appropriate checks and balances.

Keeping ahead of this challenge and mitigating the risk requires a multi-faceted approach. People and processes are key, as, of course, is technology in any data loss prevention (DLP) strategy.

This has led to a reevaluation of both technology and approach to DLP; a recognition that we must evolve an approach that is holistic, intelligent, and able to apply context to our data usage. DLP must form part of a broader risk management strategy.

Within this report, we evaluate the leading vendors who are offering solutions that can form part of your DLP strategy—tools that understand data as well as evaluate insider risk to help mitigate the threat of data loss. This report aims to give enterprise decision-makers an overview of how these offerings can be a part of a wider data security approach.

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Key Criteria for Evaluating Data Loss Prevention Platforms

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Data is a crucial asset for modern businesses and has to be protected in the same way as any other corporate asset, with diligence and care. Loss of data can have catastrophic effects, from reputational damage to significant fines for breaking increasingly stringent regulations.

While the risk of data loss is not new, the landscape we operate in is evolving rapidly. Data can leave data centers in many ways, whether accidental or malicious. The routes for exfiltration also continue to grow, ranging from email, USB sticks, and laptops to ever-more-widely-adopted cloud applications, collaboration tools, and mobile devices. This is driving a resurgence in the enterprise’s need to ensure that no data leaves the organization without appropriate checks and balances in place.

Keeping ahead of this challenge and mitigating the risk requires a multi-faceted approach. Policy, people, and technology are critical components in a data loss prevention (DLP) strategy.

As with any information security strategy, technology plays a significant role. DLP technology has traditionally played a part in helping organizations to mitigate some of the risks of uncontrolled data exfiltration. However, both the technology and threat landscape have shifted significantly, which has led to a reevaluation of DLP tools and strategy.

The modern approach to the challenge needs to be holistic and intelligent, capable of applying context to data usage by building a broader understanding of what the data is, who is using it, and why. Systems in place must also be able to learn when user activity should be classified as unusual so they can better interpret signs of a potential breach.

This advanced approach is also driving new ways of defining the discipline of data loss prevention. Dealing with these risks cannot be viewed in isolation; rather, it must be part of a wider insider risk-management strategy.

Stopping the loss of data, accidental or otherwise, is no small task. This GigaOM Key Criteria Report details DLP solutions and identifies key criteria and evaluation metrics for selecting such a solution. The corresponding GigOm Radar Report identifies vendors and products in this sector that excel. Together, these reports will give decision-makers an overview of the market to help them evaluate existing platforms and decide where to invest.

How to Read this Report

This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding consider reviewing the following reports:

Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.

GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.

Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.

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