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Thanks to Aza Raskin, this week we learned of a new phishing attack, dubbed “tabnabbing” by Brian Krebs. It opening a tab (unbeknownst to the user), changes the favicon, and does a great job of impersonating a web page – or a bank account, or any other phishing target. Through the magic of JavaScript, the tabs can be controlled and the attack made very hard to detect since it preys on the familiarity of users with common webmail and banking interfaces. So what do you do? You can run NoScript in your Firefox browser and to prevent the JavaScript from running (unless you idiotically allowed JavaScript on a compromised page). Another option is leveraging a password manager. Both Rich and I have professed our love for 1Password on the Mac. 1Password puts a button in your browser, and when logging in brings up a choice of credentials for that specific domain to automatically fill in the form. So when I go to Gmail, logging in is as easy as choosing one of the 4 separate logins I use on google.com domains. Now if I navigate to the phishing site, which looks exactly like Gmail, I’d still be protected. 1Password would not show me any stored logins for that domain, since presumably the phisher must use a different domain. This isn’t foolproof because the phisher could compromise the main domain, host the page there, and then I’m hosed. I could also manually open up 1Password and copy/paste the login credentials, but that’s pretty unlikely. I’d instantly know something was funky if my logins were not accessible, and I’d investigate. Both of these scenarios are edge cases and I believe in a majority of situations I’d be protected. I’m not familiar with password managers on Windows, but if they have similar capabilities, we highly recommend you use one. So not only can I use an extremely long password on each sensitive site, I get some phishing protection as a bonus. Nice. Share:

The first four posts our the SIEM series dealt with understanding what SIEM is, and what problems it solves. Now we move into how to select the right product/solution/service for your organization, and that involves digging into the technology behind SIEM and log management platforms. We start with the foundation of every SIEM and Log Management platform: data collection. This is where we collect data from the dozens of different types of devices and applications we monitor. ‘Data’ has a pretty broad meaning – here it typically refers to event and log records but can also include flow records, configuration data, SQL queries, and any other type of standard data we want to pump into the platform for analysis. It may sound easy, but being able to gather data from every hardware and software vendor on the planet in a scalable and reliable fashion is incredibly difficult. With over 20 vendors in the Log Management and SIEM space, and each vendor using different terms to differentiate their products, it gets very confusing. In this series we will define vendor-neutral terms to describe the technical underpinnings and components of log data collection, to level-set what you really need to worry about. In fact, while log files are what is commonly collected, we will use the term “data collection”, as we recommend gathering more than just log files. Data Collection Overview Conceptually, data collection is very simple: we just gather the events from different devices and applications on our network to understand what is going on. Each device generates an event each time something happens, and collects the events into a single repository known as a log file (although it could actually be a database). There are only four components to discuss for data collection, and each one provides a pretty straight-forward function. Here are the functional components: Fig 1. Agent data collector Fig 2. Direct connections to the device Fig 3. Log file collection Source: There are many different sources – including applications, operating systems, firewalls, routers & switches, intrusion detection systems, access control software, and virtual machines – that generate data. We can even collect network traffic, either directly from the network for from routers that support Netflow-style feeds. Data: This is the artifact telling us what actually happened. The data could be an event, which is nothing more than a finite number of data elements to describe what happened. For example, this might record someone logging into the system or a service failure. Minimum event data includes the network address, port number, device/host name, service type, operation being performed, result of the operation (success or error code), user who performed the operation, and timestamp. Or the data might just be configuration information or device status. In practice, event logs are pretty consistent across different sources – they all provide this basic information. But each offers additional data, including context. Additional data types may include things such as NetFlow records and configuration files. In practice, most of the data gathered will be events and logs, but we don’t want to arbitrarily restrict our scope. Collector: This connects to a source device, directly or indirectly, to collect the events. Collectors take different forms: they can be agents residing on the source device (Fig. 1), remote code communicating over the network directly with the device (Fig. 2), an agent writing code writing to a dedicated log repository (Fig. 3), or receivers accepting a log file stream. A collector may be provided by the SIEM vendor or a third party (normally the vendor of the device being monitored). Further, the collector functions differently, depending upon the idiosyncrasies of the device. In most cases the source need only be configured once, and events will be pushed directly to the collector or into a neutral log file read by it. In some cases, the collector must continually request data be sent, polling the source at regular intervals. Protocol: This is how collector communicates with the source. This is an oversimplification, of course, but think of it as a language or dialect the two agree upon for communicating events. Unfortunately there are lots of them! Sometimes the collector uses an API to communicate directly with the source (e.g., OPSEC LEA APIs, MS WMI, RPC, or SDEE). Sometimes events are streamed over networking protocols such as SNMP, Netflow, or IPFIX. Sometimes the source drops events into a common file/record format, such as syslog, Windows Event Log, or syslog-ng, which is then read by the collector. Additionally, third party applications such as Lasso and Snare provide these features as a service. Data collection is conceptually simple, but the thousands of potential variations makes implementation a complex mess. It resembles a United Nations meeting: you have a whole bunch of people talking in different languages, each with a particular agenda of items they feel are important, and different ways they want to communicate information. Some are loquacious and won’t shut up, while others need to be poked and prodded just to extract the simplest information. In a nutshell, it’s up to the SIEM and Log Management platforms to act as the interpreters, gathering the information and putting it into some useful form. Tradeoffs Each model for data collection has trade-offs. Agents can be a powerful proxy, allowing the SIEM platform to use robust (sometimes proprietary) connection protocols to safely and reliably move information off devices; in this scenario device setup and configuration is handled during agent installation. Agents can also take full advantage of native device features, and can tune and filter the event stream. But agents have fallen out of favor somewhat. SIEM installations cover thousands of devices, which means agents can be a maintenance nightmare, requiring considerable time to install and maintain. Further, agents’ processing and data storage requirements on the device can affect stability and performance. Finally, most agents require administrative access, which creates am additional security concern on each device. Another common technique streams events to log files, such as syslog or the Windows Event

As some of you know, I’ve always been pretty critical of quantitative risk frameworks for information security, especially the Annualized Loss Expectancy (ALE) model taught in most of the infosec books. It isn’t that I think quantitative is bad, or that qualitative is always materially better, but I’m not a fan of funny math. Let’s take ALE. The key to the model is that your annual predicted losses are the losses from a single event, times the annual rate of occurrence. This works well for some areas, such as shrinkage and laptop losses, but is worthless for most of information security. Why? Because we don’t have any way to measure the value of information assets. Oh, sure, there are plenty of models out there that fake their way through this, but I’ve never seen one that is consistent, accurate, and measurable. The closest we get is Lindstrom’s Razor, which states that the value of an asset is at least as great as the cost of the defenses you place around it. (I consider that an implied or assumed value, which may bear no correlation to the real value). I’m really only asking for one thing out of a valuation/loss model: The losses predicted by a risk model before an incident should equal, within a reasonable tolerance, those experienced after an incident. In other words, if you state that X asset has $Y value, when you experience a breach or incident involving X, you should experience $Y + (response costs) losses. I added, “within a reasonable tolerance” since I don’t think we need complete accuracy, but we should at least be in the ballpark. You’ll notice this also means we need a framework, process, and metrics to accurately measure losses after an incident. If someone comes into my home and steals my TV, I know how much it costs to replace it. If they take a work of art, maybe there’s an insurance value or similar investment/replacement cost (likely based on what I paid for it). If they steal all my family photos? Priceless – since they are impossible to replace and I can’t put a dollar sign on their personal value. What if they come in and make a copy of my TV, but don’t steal it? Er… Umm… Ugh. I don’t think this is an unreasonable position, but I have yet to see a risk framework with a value/loss model that meets this basic requirement for information assets. Share:

I seriously got this last night and just had to share. It’s the digital equivalent of sending someone a letter that says, “Hello, this is a robber. Please put all your money in a self addressed stamped envelope and mail it to…” Dear Valued Member, Due to the congestion in all Webmail account and removal of all unused Accounts,we would be shutting down all unused accounts, You will have to confirm your E-mail by filling out your Login Info below after clicking the reply botton, or your account will be suspended within 48 hours for security reasons. UserName: …………………………………… Password:……………………………………. Date Of Birth: ………………………………. Country Or Territory:…………………………. After Following the instructions in the sheet,your account will not be interrupted and will continue as normal.Thanks for your attention to this request. We apologize for any inconvinience. Webmaster Case number: 447045727401 Property: Account Security Share:

I ran long on yesterday’s Oracle Buys Secerno, but it is worth diving into Secerno’s technology to understand why this is a good fit for Oracle. I get a lot of questions about Secerno product, from customers unclear how the technology works. Even other database activity monitoring vendors ask – some because they want to know what the product is really capable of, others who merely want to vent their frustration at me for calling Secerno unique. And make no mistake – Secerno is unique, despite competitor claims to the contrary. Unlike every other vendor in the market, Secerno analyzes the SQL query construct. They profile valid queries, and accept only queries that have the right structure. This is not content monitoring, not traditional behavioral monitoring, not context monitoring, and not even attribute-based monitoring, but looking at the the query language itself. Consider that any SQL query (e.g., SELECT, INSERT, UPDATE, CREATE, etc.) has dozens of different options, allowing hundreds of variations. You can build very complex logic, including embedding other queries and special characters. Consider an Oracle INSERT operation as an example. The (pseudo) code might look like: INSERT INTO Table.Column VALUE ‘XYZ’ Or it might look like … INSERT INTO User.Table.@db_Link ColumnA, ColumnC VALUE ‘XYZ’, ‘PDQ’ | SELECT * FROM SomeSystemTable … WHERE 1=1; We may think of INSERT as a simple statement, but there are variations which are not simple at all. Actually they get quite complex, and enable me to all sorts of stuff to confuse the query parser into performing operations on my behalf. There are ample opportunities for me to monkey with the WHERE clause, embed logic or reference other objects. Secerno handles this by mapping every possible SQL query variation for the database platform it is protecting, but depending upon the application, only allows a small subset of known variations to be accepted. Everything else can be blocked. In the examples above, the first would be permitted while the latter blocked. Attackers commonly abuse query syntax to confuse the database query parser into doing something it is not supposed to do. The more obscure uses of the SQL query language are ripe targets for abuse. In essence you remove a lot of the possible attacks because you simply do not allow unacceptable query structures or variations. This is a different way to define acceptable use of the database. Secerno calls this a “Database Firewall”, which helps the general IT audience quickly get the concept, but I call this technology query White Listing, as it is a bit more accurate. Pick the acceptable queries and their variations, and block everything else. And it can ‘learn’ by looking at what the application sends the database – and if my memory serves me, can even learn appropriate parameters as well. It’s less about context and content, and more about form. Other vendors offer blocking and advertise “Database Firewall” capabilities. Some sit in front of the database like Secerno does, and others reside on the database platform. The real difference is not whether or not they block, but in how they detect what to block. As with any technology, there are limitations. If Secerno is used to block queries, it can create a performance bottleneck. Similarly to a network firewall, more rules means more checking. You can quickly build a very detailed rule set that creates a performance problem. You need to balance the number of rules with performance. And just like a firewall or WAF, if your application changes queries on a regular basis, your rule set will need to adapt to avoid breaking the application. The real question is “Is this technology better?” The answer depends upon usage. For detection of insider misuse, data privacy violation, or hijacked accounts, either stateful inspection and behavioral monitoring will be a better choice. For databases that support a lot of ad hoc activity, content inspection is better. But for web applications, especially those that don’t add/change their database queries very often, this query analysis method is very effective for blocking injection attacks. Over and above the analysis capabilities, the handful of customers I have spoken with deployed the platform very quickly. And from the demos I have seen, the product’s interface is on par with the rest of the DAM providers. Secerno is not revolutionary and does not offer extraordinary advantages over the competition. It is a good technology and a very good fit for Oracle, because it fills the gaps they in their security portfolio. Just keep in mind that each Database Activity Monitoring solution offers a different subset of available analysis techniques, deployment models, and supporting technologies – such as WAF, Assessment and Auditing. And each vendor provides a very different experience – in terms of user interface quality, ease of management, and deployment. DAM is a powerful tool for your arsenal, but you need to consider the whole picture – not just specific analysis techniques. Share:

Much of the buzz around the security industry this week revolved around Wired’s story about LifeLock’s CEO getting his identity stolen not once (which we knew about), but an additional 12 times. Guess 13 is not Todd Davis’ lucky number. Obviously the media blitz posting this guy’s Social Security number on buses, TV, and other mass media made this guy target #1. And the reality is no identity protection network is going to be foolproof for a pretty simple reason. The companies issuing credit don’t always check for fraud alerts, so a fraud alert may not be triggered when a new account is opened. Even if you are religiously monitoring your credit, you are blind until the fraudulent account shows up where you can see it. But what’s troubling to me is the guy didn’t know about the issues until a collection agency came after him. I’m concerned for several reasons, and the blame can be directed everywhere. First to LifeLock, how do you not see 12 new accounts? Hard to believe that none of the accounts showed up on Davis’ credit history. If not, what is the point of their identity protection service again? Also note that none of the 13 transactions were for big numbers. A couple hundred here, a couple hundred there. That’s been my personal experience as well. The fraudsters don’t try to milk personal accounts of thousands at a time because that will set off alarms. They don’t want to be discovered until they are long gone. More disturbing is how the merchants handle most of these situations. In the crazy search for growth at any cost, they cut corners. It’s as simple as that. They don’t check credit ahead of time (or they would have seen the fraud lock). They don’t report new credit accounts to the bureaus (which would have triggered a credit monitoring alert). And they don’t verify addresses when sending bills (which would have shown an inconsistency on the original application). Amazingly enough, a collection agent finds the guy within a hour, but the companies can’t do that over a year. I guess I shouldn’t be surprised, since these big companies just build a ‘shrinkage’ number into their models. They figure a certain percentage of their customers will not pay, either for legitimate or fraudulent reasons. And I guess that’s cheaper than setting up the right processes to prevent a portion of that fraud. Ultimately it’s just economics, but it’s still very disturbing. Buyt if I allowed myself to get into a funk every time a big company did something stupid and harmful, I’d be even grumpier than I already am. So I need to let that go. Though there are things we can and should do to minimize the damage of identity theft. (Try to) Prevent it: OK, you can’t really prevent it. But you can act proactively to minimize your attack surface. That means setting up your own fraud alerts (since the credit bureaus and their lobbyists succeeded in killing the ability for a service to do this for you) and use a credit monitoring service (I use Debix, but there are lots out there). Accept it: Understand that it will happen and there is likely nothing you can do. Getting upset won’t help. You need to be focused and contain the damage. Contain it: As we always say, you need an incident response plan for your business in the event of a breach, but you need a personal incident response plan as well. Who do you call? What steps do you take? Those should be documented and in a place you can get to quickly. You need to act fast, and having a documented process reduces emotion and lets you make the decisions when you’re clear-headed and not rushing. Confirm it: The credit bureaus are a hassle to deal with, but you have to stay on top of them to make sure your credit rating is properly cleaned. The three you need to worry about are Experian, Equifax, and TransUnion. That means checking your credit rating on an ongoing basis and keeping all documentation on the fraudulent use of your accounts. Finally, don’t post personal information on the side of a bus. We know how that turns out. Share:

This morning Oracle announced that it has entered into an agreement to acquire Secerno, the UK-based Database Activity Monitoring firm. Oracle posted a FAQ on the acquisition with some generic data points. Terms of the deal have not been disclosed and, knowing Oracle, won’t be. Many of us in the security industry are chuckling at this purchase as Oracle – at least to customers – has been disparaging Database Activity Monitoring technologies as a whole and pushing Audit Vault as an equivalent solution. But when your database is Unbreakable™, maybe you don’t need a database firewall, eh? Seriously, DAM has been a hole in their security offerings for years, and after much blustering to the contrary, they have finally plugged the hole. And from the synergies of the platforms, I’d say they did a pretty good job of it. Key Points about the Acquisition Here are the most important top-level points: The deal is clearly about the security alerting and blocking features of Secerno. Oracle calls it a “Database Firewall”, and never says Database Activity Monitoring. Oracle sees Audit Vault as their DAM equivalent, and has heavily disparaged that market and the techniques used by DAM vendors. Customers really struggle with Oracle patching, which makes it very difficult to keep systems compliant and secure. Positioning Secerno as a stopgap to protect the database from particular exploits so you have time to patch is reasonable and appropriate. It’s also a good straight up security play. Secerno was always stronger on security than activity monitoring for compliance, which makes it more complementary to the existing Oracle product line and security messaging. Oracle may include this in Oracle Advanced Security, or keep it standalone. We’ll have to see, but based on the current physical architecture I’d bet on stand-alone for at least a few years. In terms of messaging, expect Audit Vault to remain the focus for building those audit trails, with Secerno positioned for real-time alerting and blocking. Expect to see Oracle market “Database Firewall” with “Zero False Positives”, but those claims overlook the real world difficulties in building and maintaining query rules. Let’s delve deeper into the specifics. What the Acquisition Does for Oracle Fills big technology gaps: Secerno provides Oracle a lot of security technology they did not have. Secerno includes real-time analysis not available from current Oracle products, which is a growing requirement – especially for customer-facing web applications. It also gives Oracle a security tool that offers genuine heterogenous database support for Oracle, Microsoft, and Sybase (IBM support is in beta). Oracle hates to admit it, but nearly all of their enterprise clients have several different databases in use, and customers want a common platform for security or compliance when possible. Secerno provides blocking capabilities – importantly before queries reach the database – to reduce DB load and risk. Secerno has a much better UI than Oracle Audit Vault, and hopefully Oracle will continue to use it rather than standardize on their own weaker UI. Prevention: Privately we have been calling Secerno a Query White Listing technology, as we think that better encompasses what they provide. “Database Firewall” is one of those throw-away marketing terms used by several DAM vendors, but fails to differentiate what Secerno provides. Yes, Secerno will block queries, and will do so before they get to the database, reducing processing and filtering load on the database engine. I’ll get into technology details later in this post, but Oracle now has a viable way to block many unwanted queries. Web Applications: Like it or not, web applications are a huge part of the Oracle database business, and auditing is totally inappropriate for securing web applications from things like SQL injection. This helps address Oracle’s repeated issues with patching and playing catch-up with vulnerabilities, finally helping prevent some attacks without totally disrupting business operations for database updates that applications don’t support. Circumvents a perception problem: Oracle Audit still has a serious perception problem, and correctly or not is considered a performance and operations burden. On paper, Oracle’s native audit trail can provide many of the same functions as other DAM and Auditing tools, but in practice Oracle Audi pales in the light of the competition – or even Audit Vault. This helps escape serious a perception problem for compliance and security adoption. What This Means to the DAM Market Validation: Let’s face it – when Oracle and IBM both make investments into Database Activity Monitoring, we are past wondering when DAM will be considered viable technology. Even though Oracle isn’t positioning this as DAM, Secerno did, and this serves as high-profile validation of the market. Business to be won: There were many unhappy IPLocks customers who Fortinet was unable to bring into the fold with their upgraded offerings. Some of Guardium’s business has been at risk for a while, and some of their resellers started looking for other relationships after the IBM purchase. Oracle’s customers have looked at – and in many cases purchased – other security products to close the gaps. Imperva still needs to do a better job of converting WAF customers to DB Security customers, and Application Security still needs to do a better job at holding onto the customers they already have. All this shows that the leader of this segment has yet to be determined, and there is a lot of potential business. One less vendor: Tizor went to Netezza. IPLocks went to Fortinet. Guardium went to IBM. Now Secerno to Oracle. That leaves Application Security and Imperva as the major database security providers out there, with Sentrigo the best of the smaller niche players in the market. EMC needs this technology next, perhaps followed by Symantec or McAfee, but the price of entry just increased. Investors: Secerno’s investors, Amadeus Capital Parners, must be happy. They did a logical reset and re-investment back in early 2008, a decision that was clearly the right one. They also had considerably less initial investment than the competitors in this space. While we do not

Australia is my second-favorite place on the planet to visit (New Zealand is first). But it’s a darn good thing I’m not a porn fiend, since they now require you to declare porn at the border, and, well, here’s a quote: Australian customs officers have been given new powers to search incoming travellers’ laptops and mobile phones for pornography, a spokeswoman for the Australian sex industry says. … Fiona Patten, president of the Australian Sex Party, is demanding an inquiry into why a new question appears on Incoming Passenger Cards asking people if they are carrying “pornography”. They are also working on a big Internet filter. You know, kind of like China and many Middle East countries. Gotta love democracy. (Thanks to Slashdot for the pointer). Share:

I want to respond to something Adam wrote about Facebook over at Emergent Chaos, but first I’m going to excerpt my own article from TidBITS: Privacy is Personal – In the Information Age, determining what you want others to know about you isn’t always a simple decision. Aside from the potential tradeoffs of avoiding particular features or services, we all have different thresholds for what we are comfortable sharing. It’s also extremely difficult to control our information even when we do make informed decisions, and often impossible to eradicate information that escaped our control before we realized the rules of the game had changed. For example, I use both Amazon and Netflix, even though those services also collect personal information like my buying and viewing habits. I am trading my data (and money) for a combination of convenience and personalization. I’m less concerned with these services than Facebook since their privacy practices and policies are clearer, my information is compartmentalized within each service, and they have much more consistent and stable records. On the other hand I have minimized my usage of Google services due to privacy concerns. Google’s reach is incredibly expansive, and despite their addition of Google Dashboard to help show some of what they record, and much clearer policies than Facebook, I’m generally uncomfortable with any single company or government having that much potential information on me. I fully understand this is a somewhat emotional response. Facebook is building a similar Internet-wide ecosystem as they expand connections to external Web sites and services. In exchange for allowing them access to your information and activities, Facebook enables new kinds of services and personalization. The question each of us must answer is if those new services and personalization options are worth the privacy tradeoff. Deciding where to draw your own privacy lines is a very personal, complex, and even sometimes arbitrary decision. I trust Amazon and Netflix to a certain extent based on their privacy policies, even though they sometimes make mistakes (I didn’t use Amazon for years after a policy change that they later reversed). Yet I’ve limited my usage of both Google and Facebook due to general concerns (Google) or outright distrust (Facebook). Facebook, to me, is a tool to keep me connected to friends and family I don’t interact with on a daily basis. I restrict what information it has on me, and always assume anything I do on Facebook could be public. I’m willing to trade a little privacy for the convenience of being able to stay connected with an expanded social circle. I manage Facebook privacy by not using it for anything that’s actually private. Adam has a lot in his article, and I think his criticisms of my original post come down to: Your perceptions of your own privacy change within different contexts and over time, so what you are okay with today may not be acceptable tomorrow. If you only use the service to post things you’d want public anyway, why use it at all? I completely agree with Adam’s first point – what you share when you are 19 years old at college is very different than what you might want people to know about you once you are 35. Even things you might share at 35 as a member of the workforce might come back to haunt you when you are 55 and running for political office. But I disagree that this means your only option is to completely opt out of all centralized social media services. I believe we as society are reaching the point where some degree of social networking is the norm. Even “private” communications like email, IM, and SMS are open to potential disclosure and subsequent inclusion in public search results. The same used to be true of the written and spoken word, but clearly the scale and scope are dramatically larger in the Information Age. We are losing the insular layers that created our current social norms of privacy – which already vary around the world. The last time society needed to adapt to such changes in privacy was with the Industrial Age and movement from rural to urban society. Before that, it was probably the change from hunter/gatherers to an agrarian society. I see three possible scenarios that could develop: Society adopts a combination of laws and social mores to better protect privacy. It will be expected that you own your own data, and in the future retain a right to edit your past. Essentially, we work to protect our current expectations of privacy – which will require active effort, as the terrain has already shifted under us, and will continue to do so. Social expectations change. You’ll be able to run for political office and no one will care that you called some chick or dude hot and joined the “I love some stupid emo vampire” movement. We gain better abilities to protect our privacy, but at the same time society becomes more accepting of greater personal information being public – partially through sheer boredom at the inanity and popularity of our embarrassing peccadilloes. There is no privacy. We have many years before these issues resolve, if ever, and it’s going to be a rough road no matter where we are headed. The end result probably won’t match any of my scenarios, but will instead be some mish-mash of those options and others I haven’t thought of. My rough guess is that society will slowly become more accepting of youthful indiscretions (or we won’t have anyone to hire or elect), but we will also gain more control over our personal information. Privacy isn’t dead, but it is definitely changing. We all need to make personal decisions about the level of risk we are willing to accept in the midst of changing social norms, government/business influence, and degrees of control. Share:

Next week I will be giving a webcast to complement my Quick Wins with Data Loss Prevention paper. This is a bit different than when I usually talk about DLP – it’s focused on showing immediate value, while also positioning for long term success. Like the paper it’s sponsored by McAfee. We’re holding it at 11am PT on May 25, and you can register by clicking here. Here’s the full description: Quick Wins with DLP – How to Make DLP Work for You Date: May 25, 2010 Time: 11am PDT / 2pm EDT When used properly, Data Loss Prevention (DLP) provides rapid identification and assessment of data security issues not available with any other technology. However, when not optimized, two common criticisms of DLP are 1) its complexity and 2) the fear of false positives. Security professionals often worry that DLP is expensive and will fail to deliver the expected value. A little knowledge and some planning go a long way towards a fast, simple, and effective deployment. By taking some straightforward best practice steps, you can realize significant immediate value and security gains without negatively impacting your productivity or wasting valuable resources. In this webcast you will learn how to: Establish a flexible incident management process Integrate with major infrastructure components Assess broad information usage Set a foundation for future focused efforts and policy tuning You will also hear how Continuum Health Partners safeguards highly sensitive patient data with McAfee DLP 9. Join us for this informative presentation. Presenters: Rich Mogull, Analyst & CEO, Securosis, LLC Mark Moroses, Assistant CIO, Continuum Health Partners John Dasher, Senior Director, Data Protection, McAfee Share: