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This is the fourth post in a new series. If you want to track it through the entire editing process, you can follow along and contribute on GitHub. You can read the first post and find the other posts under “related posts” in full article view. Key Management Options As mentioned back in our opening, the key (pun intended – please forgive us) to an effective and secure encryption system is proper placement of the components. Of those the one that most defines the overall system is the key manager. You can encrypt without a dedicated key manager. We know of numerous applications that take this approach. We also know of numerous applications that break, fail, and get breached. You will nearly always want to use a dedicate key management option, which breaks down into four types: The first thing to consider is how to deploy external key management. There are four options: An HSM or other hardware key management appliance. This provides the highest level of physical security. It is the most common option in sensitive scenarios, such as financial services and payments. The HSM or appliance runs in your data center, and you always want more than one for backup. Lose access and you lose your keys. Apple, for example, has stated publicly that they physically destroy the administrative access smart cards after configuring a new appliance so no one can ever access and compromise the keys, which are destroyed if someone tries to open the housing or certain other access methods. A hardware root of trust is the most secure option, and all those products also include hardware acceleration for cryptographic operations to improve performance. A key management virtual appliance. A vendor provides a pre-configured virtual appliance (instance) for you to run where you need it. This reduces costs and increases deployment flexibility, but isn’t as secure as dedicated hardware. If you decide to go this route, use a vendor who takes exceptional memory protection precautions, because there are known techniques for pulling keys from memory in certain virtualization scenarios. A virtual appliance doesn’t offer the same physical security as a physical server, but they do come hardened, and support more flexible deployment options – you can run them within a cloud or virtual datacenter. Some systems also allow you to use a physical appliance as the hardware root of trust for your keys, but then distribute keys to virtual appliances to improve performance in distributed scenarios (for virtualization or simply cost savings). Key management software, which can run either on a dedicated server or within a virtual/cloud server. The difference between software and a virtual appliance is that you install the software yourself rather than receiving a hardened and configured image. Otherwise software offers the same risks and benefits as a virtual appliance, assuming you harden the server as well as the virtual appliance. Key Management Software as a Service (SaaS). Multiple vendors now offer key management as a service specifically to support public cloud encryption. This also works for other kinds of encryption, including private clouds, but most usage is for public clouds. Client Access Options Whatever deployment model you choose, you need some way of getting keys where they need to be, when they need to be there, for cryptographic operations. Clients (whatever needs the key) usually need support for the following core functions for a complete key management lifecycle: Key generation Key exchange (gaining access to the key) Additional key lifecycle functions, such as expiring or rotating a key Depending on what you are doing, you will allow or disallow these functions under different circumstances. For example you might allow key exchange for a particular application, but not allow it any other management functions (such as generation and rotation). Access is managed one of three ways, and many tools support more than one: Software Agent: A dedicated agent handles client key functions. These are generally designed for specific use cases – such as supporting native full disk encryption, specific backup software, various database platforms, and so on. Some agents may also perform cryptographic functions for additional hardening, such as wiping the key from memory after each use. Application Programming Interfaces: Many key managers are used to handle keys from custom applications. An API allows you to access key functions directly from application code. Keep in mind that APIs are not all created equal – they vary widely in platform support, programming languages supported, simplicity or complexity of API calls, and the functions accessible via the API. Protocol & Standards Support: The key manager may support a combination of proprietary and open protocols. Various encryption tools support their own protocols for key management, and like software agents, the key manager may include support – even if it is from a different vendor. Open protocols and standards are also emerging but not yet in wide use, and may be supported. We have written a lot about key management in the past. To dig deeper take a look at Pragmatic Key Management for Data Encryption and Understanding and Selecting a Key Management Solution. Share:

I meant to write about this earlier and forgot. Last week I was listening to the Diane Rehm show on NPR while out for a long run (I am weird and prefer talk radio/podcasts on long workouts). The show was all about cybersecurity. To be honest, the panel was a bit weak (Ravi Pendse from Brown was decent). When they opened up the phone lines, as you would expect, a lot of consumers called in. I will paraphrase one call a bit.. I don’t really get what the big deal is. If someone uses my Social Security number all I need to do is call my bank and clean it up. This was prefaced by: I’ve worked on process control systems for over 20 years, like water treatment and other utilities. Even the panel had a hard time responding. (Sorry I don’t have a transcript.) Share:

Last week President Obama held a cybersecurity summit out in the Bay Area. He issued a new executive order and is standing up a new threat sharing center. This is in response to ongoing massive attacks such as the Anthem breach and (as we heard this weekend) hundreds of millions stolen in bank thefts. But what does it all mean to security pros and the industry? The truth is, not much in our day-to-day (yet), but you certainly had better pay attention. Watch or listen: Share:

Picture enterprise applications as a layer cake: applications sit on databases, databases on files, and files are mapped onto storage volumes. You can use encryption at each of these layers in your application stack: within the application, in the database, on files, or on storage volumes. Where you use an encryption engine dominates security and performance. Higher up the stack can offer more security, with higher complexity and performance cost. There is a similar tradeoff with encryption engine and key manager deployments: more tightly coupled systems offer less complexity, but less security and reliability. Building an encryption system requires a balance between security, complexity, and performance. Let’s take a closer look at each layer and their tradeoffs. Application Encryption One of the more secure ways to encrypt application data is to collect it in the application, send it to an encryption server or appliance (an encryption library embedded in the application), and then store the encrypted data in a separate database. The application has full control over who sees what and can secure data without depending on the security of the underlying database, file system, or storage volumes. The keys themselves might be on the encryption server or could even be stored in yet another system. The separate key store increases security, simplifies management of multiple encryption appliances, and helps keep keys safe for data movement – backup, restore, and migration/synchronization to other data centers. Database Encryption Relational database management systems (RDBMS) typically have two encryption options: transparent and column. In our layer cake above columnar encryption occurs as applications insert data into a database, whereas transparent encryption occurs as the database writes data out. Transparent encryption is applied automatically to data before it is stored at the file or disk layer. In this model encryption and key management happen behind the scenes, without the user’s knowledge or requiring application programming. The database management system handles encryption and decryption operations as data is read (or written), ensuring all data is secured, and offering very good performance. When you need finer control over data access, you can encrypt single columns, or tables, within the database. This approach offers the advantage that only authenticated users of encrypted data are able to gain access, but requires changing database or application code to manage encryption operations. With either approach there is less burden on application developers to build a crypto system, but slightly less control over who can access sensitive data. Some third-party tools also offer transparent database encryption by automatically encrypting data as it is stored in files. These tools aren’t part of the database management system itself, so they can work with databases that don’t support TDE directly, and provide greater separation of duties for database administrators. File Encryption Some applications, such as payment systems and web applications, do not use databases and instead store sensitive data in files. Encryption is applied transparently as data is written to files. This type of encryption is offered as a third-party add-on to the file system, or embedded within the operating system. Encryption and decryption are transparent to both users and applications. Data is decrypted when a user requests a file, after they have authenticated to the system. If the user does not have permission to read the file, or has not provided proper credentials, they only get encrypted data. File encryption is commonly used to protect “data at rest” in applications that do not include encryption capabilities, including legacy enterprise applications and many big data platforms. Disk/Volume Encryption Many off-the-shelf disk drives and Storage Area Network (SAN) arrays include automatic data encryption. Encryption is applied as data is written to disk, and decrypted by authenticated users/apps when requested. Most enterprise-class systems hold encryption keys locally to support encryption operations, but rely on external key management services to manage keys and provide advanced key services such as key rotation. Volume encryption protects data in case drives are physically stolen. Authenticated users and applications are provided unencrypted copies of files and data. Tradeoffs In general, the further “up the stack” you deploy encryption, the more secure your data is. The price of that extra security is more difficult integration, usually in the form o application code changes. Ideally we would encrypt all data at the application layer and fully leverage user authentication, authorization, and business context to determine who can see sensitive data. In the real world the code changes required for this level of precision control are often insurmountable engineering challenges and/or cost prohibitive. Surprisingly, transparent encryption often perform faster than application-layer encryption, even with larger data sets. The tradeoff is moving high enough “up the stack” to address relevant threats while minimizing the pain of integration and management. Later in this series we will walk you through the selection process in detail. Next up in this series: key management options. Share:

Welcome to the Friday the 13th edition of the Friday Summary! It has been a while since I wrote the summary so there is lots to cover … My favorite external post this week is a research paper, Mongo Databases At Risk, outlining a very common trend among MongoDB users: not using basic user authentication to secure their databases. Well, that, and putting them on the Internet. On the default port. Does this sound like SQL Server circa 2003 to anyone else? One angle I found important was the number of instances discovered: nearly 40k databases. That is a freakin’ lot! Remember, this is MongoDB. And just those running on the Internet at the default port. Yes, it’s one of the top NoSQL platforms, but during our inquiries we spoke with 4 Hadoop users for every MongoDB user. MongoDB was also behind Hadoop and Cassandra. I don’t know if anyone publishes download or usage numbers for the various platforms, but extrapolating from those numbers, there are a lot of NoSQL databases in use. Someone with more time on their hands might decide to scan the Internet for instances of the other platforms (the default port for Hadoop, Cassandra, CouchDB, and Redis is 6380; RIAK is 8087). I would love to know what you find. Back to security… I have had conversations with several firms trying to figure out how to monitor NoSQL usage; we know how to apply DAM principles to SQL, but MapReduce and other types of queries are much more difficult to parse. I expect several vendors to introduce basic monitoring for Hadoop in the next year, but it will take time to mature, and even more to cover other platforms. What I haven’t heard discussed is the easier – and no less pressing – issue of configuration and vulnerability assessment. The enterprise distributions are providing best practices but automated scans are scarce – and usually custom. That is a free hint for any security vendors looking for a quick way to help big data customers get secure. Mobile security consumes much more of my time than it should. I geek out on it, often engaging Gunnar in conversation on everything from the inner workings of secure elements to the apps that make payments happen. And I read everything I can find. This week I ran across Why Banks Will Win the Battle for the Mobile Wallet, by John Gunn – the guy who runs the wonderfully helpful twitter feed @AuthNews. But on this I think he has missed the point. Banks are not battling to win mobile wallets. In fact those I have spoken with don’t care about wallets. They care about transactions. And moving more transactions from cash to credit means a growing stream of revenue for merchant banks and payment processors, which makes them very happy. Wallets in and of themselves don’t fosters adoption – as Google is well aware – and in fact many users don’t really trust wallets at all. What gets people to move from a plastic card or cash, at least in the US, is a combination of convenience and trust. Starbucks leveraged their brand affinity into seven million subscribers for their app and an impressive 2.1 million transactions per week. Banks benefit directly when more transactions move away from cash, and they are happy to let others own the user experience. But things get really interesting in overseas markets, which make US adoption of mobile payments look like a payments backwater. Nations without traditional banking or payment infrastructure can now move money in ways they previously could not, so adoption rates have been huge. Leveraging cellular infrastructure makes it faster and safer to move money, with fewer worries about carrying cash. Nations like Kenya – which is not often considered on the cutting edge of technology, but had 25 million mobile payment users and moved $26 billion in 2014 via mobile payments and mobile money subscriptions. Sometimes technology really does make the world a better place. The banks don’t care which wallets, apps, technology, or carriers wins – they just want someone to make progress. In January I normally publish my research calendar for the coming year. But Rich has been hogging the Friday Summary for weeks now, so I finally get a chance to talk about what I am seeing and doing. Tokenization: I am – finally – going to publish some thoughts on the latest trends in tokenization. I want to talk about changes in the technology, adoption on mobile platforms, how the latest PCI specification is changing compliance, and some customer user cases. Risk-Based Authentication and Authorization: We see many more organizations looking at risk-based approaches to augment the security of web-based applications. Rather than rewrite applications they use metadata, behavioral information, business context, and… wait for it… big data analytics to better determine the acceptability of a request. And it is often cheaper and easier to bolt this on externally than to change applications. Gunnar and I have wanted to write this paper for a year, and now we finally have the time. Building a Security Analytics Platform: I have been briefed by many of security analytics startups, and each is putting together some basic security analysis capabilities, usually built on big data databases. I have, in that same period, also spoken with many large enterprises who decided not to wait for the industry to innovate, and are building their own in-house systems. The last couple even asked me what I thought of certain architectural choices, and which data elements should they use as hash keys! So there is considerable demand for consumer education; I will cover off-the-shelf and DIY options. I am still on the fence about some secure code development ideas, so if you have an idea, let’s talk. Even the security vendors I have visited in the last year have pulled me aside to ask about transitioning to Agile, or how to fix a failed transition to Agile. Most want to know what

This is the second post in a new series. If you want to track it through the entire editing process, you can follow along and contribute on GitHub. You can read the first post here Building an Encryption System In a straightforward application we normally break out the components – such as the encryption engine in an application server, the data in a database, and key management in an external service or appliance. Or, for a legacy application, we might instead enable Transparent Database Encryption (TDE) for the database, with the encryption engine and data both on the same server, but key management elsewhere. All data encryption systems are defined by where these pieces are located – which, even assuming everything works perfectly, define the protection level of the data. We will go into the different layers of data encryption in the next section, but at a high level they are: In the application where you collect the data. In the database that holds the data. In the files where the data is stored. On the storage volume (typically a hard drive, tape, or virtual storage) where the files reside. All data flows through that stack (sometimes skipping applications and databases for unstructured data). Encrypt at the top and the data is protected all the way down, but this adds complexity to the system and isn’t always possible. Once we start digging into the specifics of different encryption options you will see that defining your requirements almost always naturally leads you to select a particular layer, which then determines where to place the components. The Three Laws of Data Encryption Years ago we developed the Three Laws of Data Encryption as a tool to help guide the encryption decisions listed above. When push comes to shove, there are only three reasons to encrypt data: If the data moves, physically or virtually. To enforce separation of duties beyond what is possible with access controls. Usually this only means protecting against administrators because access controls can stop everyone else. Because someone says you have to. We call this “mandated encryption”. Here is an example of how to use the rules. Let’s say someone tells you to “encrypt all the credit card numbers” in a particular application. Let’s further say the reason is to prevent loss of data if a database administrator account is compromised, which eliminates our third reason. The data isn’t necessarily moving, but we want separation of duties to protect the database even if someone steals administrator credentials. Encrypting at the storage volume layer wouldn’t help because a compromised administrative account still has access within the database. Encrypting the database files alone wouldn’t help either. Encrypting within the database is an option, depending on where the keys are stored (they must be outside the database) and some other details we will get to later. Encrypting in the application definitely helps, since that’s completely outside the database. But in either cases you still need to know when and where an administrator could potentially access decrypted data. That’s how it all ties together. Know why you are encrypting, then where you can potentially encrypt, then how to position the encryption components to achieve your security objectives. Tokenization and Data Masking Two alternatives to encryption are sometimes offered in commercial encryption tools: tokenization and data masking. We will spend more time on them later, but simply define them for now: Tokenization replaces a sensitive piece of data with a random piece of data that can fit the same format (such as by looking like a credit card number without actually being a valid credit card number). The sensitive data and token are then stored together in a highly secure database for retrieval under limited conditions. Data masking replaces sensitive data with random data, but the two aren’t stored together for later retrieval. Masking can be a one-way operation, such as generating a test database, or a repeatable operation such as dynamically masking a specific field for an application user based on permissions. For more information on tokenization vs. encryption you can read our paper. That covers the basics of encryption systems. Our next section will go into details of the encryption layers above before delving into key management, platform features, use cases, and the decision tree to pick the right option. Share:

This is the first post in a new series. If you want to track it through the entire editing process, you can follow it and contribute on GitHub. The New Age of Encryption Data encryption has long been part of the information security arsenal. From passwords, to files, to databases, we rely on encryption to protect our data in storage and on the move. It’s a foundational element in any security professional’s education. But despite its long history and deep value, adoption inside data centers and applications has been relatively – even surprisingly – low. Today we see encryption growing in the data center at an accelerating rate, due to a confluence of reasons. A trite way to describe it is “compliance, cloud, and covert affairs”. Organizations need to keep auditors off their backs; keep control over data in the cloud; and stop the flood of data breaches, state-sponsored espionage, and government snooping (even their own). And thanks to increasing demand, there is a growing range of options, as vendors and even free and Open Source tools address the opportunity. We have never had more choice, but with choices comes complexity; and outside of your friendly local sales representative, guidance can be hard to come by. For example, given a single application collecting an account number from each customer, you could encrypt it in any of several different places: the application, the database, or storage – or use tokenization instead. The data is encrypted (or substituted), but each place you might encrypt raises different concerns. What threats are you protecting against? What is the performance overhead? How are keys managed? Does it meet compliance requirements? This paper cuts through the confusion to help you pick the best encryption options for your projects. In case you couldn’t guess from the title, our focus is on encrypting in the data center – applications, servers, databases, and storage. Heck, we will even cover cloud computing (IaaS: Infrastructure as a Service), although we covered that in depth in another paper. We will also cover tokenization and its relationship with encryption. We won’t cover encryption algorithms, cipher modes, or product comparisons. We will cover different high-level options and technologies, such as when to encrypt in the database vs. in the application, and what kinds of data are best suited for tokenization. We will also cover key management, some essential platform features, and how to tie it all together. Understanding Encryption Systems When most security professionals first learn about encryption the focus is on keys, algorithms, and modes. We learn the difference between symmetric and asymmetric and spend a lot of time talking about Bob and Alice. Once you start working in the real world your focus needs to change. The fundamentals are still important but now you need to put them into practice as you implement encryption systems – the combination of technologies that actually protects data. Even the strongest crypto algorithm is worthless if the system around it is full of flaws. Before we go into specific scenarios let’s review the basic concepts behind building encryption systems because this becomes the basis for decisions on which encryption options to go use. The Three Components of a Data Encryption System When encrypting data, especially in applications and data centers, knowing how and where to place these pieces is incredibly important, and mistakes here are one of the most common causes of failure. We use all our data at some point, and understanding where the exposure points are, where the encryption components reside, and how they tie together, all determine how much actual security you end up with. Three major components define the overall structure of an encryption system. The data: The object or objects to encrypt. It might seem silly to break this out, but the security and complexity of the system depend on the nature of the payload, as well as where it is located or collected. The encryption engine: This component handles actual encryption (and decryption) operations. The key manager: This handles keys and passes them to the encryption engine. In a basic encryption system all three components are likely located on the same system. As an example take personal full disk encryption (the built-in tools you might use on your home Windows PC or Mac): the encryption key, data, and engine are all stored and used on the same hardware. Lose that hardware and you lose the key and data – and the engine, but that isn’t normally relevant. (Neither is the key, usually, because it is protected with another key, or passphrase, that is not stored on the system – but if the system is lost while running, with the key in memory, that becomes a problem). For data centers these major components are likely to reside on different systems, increasing complexity and security concerns over how the pieces work together. Share:

Rich, Mike, and Adrian each pick a trend they expect to hammer us in 2015. Then they talk about it, probably too much. From threat intel to tokenization to SaaS security. And oh, we did have to start with a dig at the Pats. Cheating? Super Bowl? Really? Come on now. Watch or listen: Share:

As we wrap up our Applied Threat Intelligence series, we have already defined TI and worked our way through a number of the key use cases (security monitoring, incident response, and preventative controls) where TI can help improve your security program, processes, and posture. The last piece of the puzzle is building a repeatable process to collect, aggregate, and analyze the threat intelligence. This should include a number of different information sources, as well as various internal and external data analyses to provide context to clarify what the intel means to you. As with pretty much everything in security, handing TI is not “set and forget”. You need to build repeatable process to select data providers and continually reassess the value of those investments. You will need to focus on integration; as we described, data isn’t helpful if you can’t use it in practice. And your degree of comfort in automating processes based on threat intelligence will impact day-to-day operational responsibilities. First you need to decide where threat intelligence function will fit organizationally. Larger organizations tend to formalize an intelligence group, while smaller entities need to add intelligence gathering and analysis to the task lists of existing staff. Out of all the things that could land on a security professional, an intelligence research responsibility isn’t bad. It provides exposure to cutting-edge attacks and makes a difference in your defenses, so that’s how you should sell it to overworked staffers who don’t want yet another thing on their to-do lists. But every long journey begins with the first step, so let’s turn our focus to collecting intel. Gather Intelligence Early in the intelligence gathering process you focused your efforts with an analysis of your adversaries. Who they are, what they are most likely to try to achieve, and what kinds of tactics they use to achieve their missions – you need to tackle all these questions. With those answers you can focus on intelligence sources that best address your probable adversaries. Then identify the kinds of data you need. This is where the previous three posts come in handy. Depending on which use cases you are trying to address you will know whether to focus on malware indicators, compromised devices, IP reputation, command and control indicators, or something else. Then start shopping. Some folks love to shop, others not so much. But it’s a necessary evil; fortunately, given the threat intelligence market’s recent growth, you have plenty of options. Let’s break down a few categories of intel providers, with their particular value: Commercial: These providers employ research teams to perform proprietary research, and tend to attain highly visibility by merchandising findings with fancy exploit names and logos, spy thriller stories of how adversary groups compromise organizations and steal data, and shiny maps of global attacks. They tend to offer particular strength regarding specific adversary classes. Look for solid references from your industry peers. OSINT: Open Source Intelligence (OSINT) providers specialize in mining the huge numbers of information security sources available on the Internet. Their approach is all about categorization and leverage because there is plenty of information available free. These folks know where to find it and how to categorize it. They normalize the data and provide it through a feed or portal to make it useful for your organization. As with commercial sources, the question is how valuable any particular source is to you. You already have too much data – you only need providers who can help you wade through it. ISAC: There are many Information Sharing and Analysis Centers (ISAC), typically built for specific industries, to communicate current attacks and other relevant threat data among peers. As with OSINT, quality can be an issue, but this data tends to be industry specific so its relevance is pretty well assured. Participating in an ISAC obligates you to contribute data back to the collective, which we think is awesome. The system works much better when organizations both contribute and consume intelligence, but we understand there are cultural considerations. So you will need to make sure senior management is okay with it before committing to an ISAC. Another aspect of choosing intelligence providers is figuring out whether you are looking for generic or company-specific information. OSINT providers are more generic, while commercial offerings can go deeper. Though various ‘Cadillac’ offerings include analysts dedicated specifically to your organization – proactively searching grey markets, carder forums, botnets, and other places for intelligence relevant to you. Managing Overlap With disparate data sources it is a challenge to ensure you don’t waste time on multiple instances of the same alert. One key to determining overlap is an understanding of how the intelligence vendor gets their data. Do they use honeypots? Do they mine DNS traffic and track new domain registrations? Have they built a cloud-based malware analysis/sandboxing capability? You can categorize vendors by their tactics to help you pick the best for your requirements. To choose between vendors you need to compare their services for comprehensiveness, timeliness, and accuracy. Sign up for trials of a number of services and monitor their feeds for a week or so. Does one provider consistently identify new threats earlier? Is their information correct? Do they provide more detailed and actionable analysis? How easy will it be to integrate their data into your environment for your use cases. Don’t fall for marketing hyperbole about proprietary algorithms, Big Data analysis, or staff linguists penetrating hacker dens and other stories straight out of a spy novel. It all comes down to data, and how useful it is to your security program. Buyer beware, and make sure you put each intelligence provider through its paces before you commit. Our last point to stress is the importance of short agreements, especially up front. You cannot know how these services will work for you until you actually start using them. Many of these intelligence companies are startups, and might not be around in 3 or 4 years. Once you identify a set of core intelligence

Over the years the RSA Conference has racked up some (legitimate) criticism that its session selection process was too opaque, started too early for up-to-date content, and didn’t always reflect the community at large. I am a bit biased because I have been involved with RSAC for a while now, and talk to the organizers year round, but I know they make a concerted effort to deal with these issues. (No, I’m not on any of the selection committees). For example they can’t really release the names of the track leads since there is a swarm (or is that murder?) of PR and marketing pros who are paid to get their representatives on stage, no matter what. I guarantee you that if those names get out, those individuals will be hammered directly. The early Call For Papers? This is a large event with a ton of tracks and a selection process. Hold the CFP too close to the event and it opens yet more cans of messes. Community representation? Funny you ask! This year RSAC has dedicated an entire track to crowdsourced submissions. The goal is to directly address all the criticism above: Submissions are open until March 12, only a month before the conference. Anyone can submit, but corporate presentations will most definitely be scrutinized. The community will vote to pick the best sessions. Anyone can vote – not just RSAC attendees! RSAC attendee votes get weighted more, which should help reduce gaming the system. The final selections will be by a public panel, based on the top 25 vote receivers. The panel is comprised of known entities, who are used to dealing with PR and marketing techniques. Yes, I am on the panel. I also feel honored that they approached me early to get ideas and feedback on this concept. They have put a lot of thought into this (especially Britta Glade, who probably hates me for calling her out). It won’t be perfect but it’s version 1.0. If you always wanted to speak at RSA, but couldn’t get through the process, give it a shot. This is a great chance for new speakers, late-breaking research, and creative sessions. Share: