FCC Wants ‘Open Internet’ Rules for Wireless

Well, this is interesting: the FCC Chairman announced that they do not believe wireless carriers should be able to block certain types of Internet traffic, according to the AP release a few hours ago. The thrust of the comments seems to be that they want to extend Internet usage rights over the wireless carrier networks. The chairman is now proposing to make it a formal rule that Internet carriers cannot discriminate against certain types of traffic by degrading service. That expands on the principle that they cannot “block” traffic, as articulated in a 2005 policy statement. It’s unclear how the rules would apply in practice to wireless data. For instance, carriers officially restrict how Internet-access cards for laptops are used, but rarely enforce the rules. The government also has been investigating Apple Inc.’s approval process for iPhone applications, but Genachowski isn’t directly addressing manufacturers’ right to determine which applications run on their phones. It does highlight that if you can control the applications used (available) on the devices, you can in turn control the content. Unless of course you break the protection on the phone. But still, this would appear to put the handset providers in the driver’s seat as far as what applications are acceptable. How long will it be before the carriers try to dictate acceptable applications when they negotiate deals? How will the carriers attempt to protect their turf and their investment? Could users say “screw both of you” and encrypt all of their traffic? Personally I like the idea, as it does foster invention and creativity outside the rigorous use models the carriers and phone providers support today. This is going to be a complex and dynamic struggle for the foreseeable future. Share:

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Incomplete Thought: Why Is Identity and Access Management Hard?

Thanks to the opportunity to be the Securosis Contributing Analyst, I’m back to blogging here on Securosis even though Rich isn’t off getting bits of his body operated on. I’ve decided to revive an old Identity and Access Management (IDM) research project of mine to kick off my work here at Securosis. Once you get past compliance, one of the biggest recent concerns for CIOs and CISOs has been IDM. This isn’t really that surprising when you consider that IDM is a key aspect of any successful security or compliance program. After all, how can you say with confidence whether or not you’ve had a breach, if you don’t know who has access to what data, or don’t have a process for granting and revoking that access? In principle this should be pretty straightforward, right? Keep a database of users with what applications they have access to and whenever they change roles, re-evaluate that access and make the appropriate changes for their new (or now non-existent) role. Unfortunately, simple doesn’t mean easy. Many large enterprises have hundreds if not thousands of applications that they need to track and in many (most?) cases these applications are not centrally controlled, even if you just count the ‘critical’ ones. This disparate control will continue to get worse as corporations continue to embrace “The Cloud.” Realistically, companies are in a situation where IDM is not only a difficult problem to solve, but also a fairly complex one as well. IDM is a large enough problem for enough companies that an entire market has sprung up over the last ten years to help organizations deal with it. In the beginning, IDM solutions were all about managing Moves, Adds and Changes (MAC) for accounts. There are several products to help with this issue, but by all reports many of them just make the situation even more complicated then it already was. Since these initial products hit the market, vendors who sell directory services, single sign on/federated identity, and entitlement services (to name just a few) have jumped onto the IDM bandwagon with claims to solve your woes. This has just caused even more confusion and made customers’ jobs even more difficult, causing many to ask: “Just what is IDM anyway?” As a result, I’m planning on breaking up my project into two major pieces. One part of the larger project will be to evaluate the IDM space in order to make recommendations on what security practitioners should look for in such products, to the extent that they choose to go that route. From my investigations to date, many companies (especially SMBs) don’t have a technology problem to solve, but rather one of process. As a result, the other part of this project will be to create a series of recommendations for companies to implement to make their IDM efforts more successful. In the meantime, feel free to treat the comments here as an open thread for your thoughts on IDM and how to do it better. Share:

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Cloud Data Security: Share (Rough Cut)

In our last post in this series, we covered the cloud implications of the Use phase of our Data Security Cycle. In this post we will move on to the Share phase. Please remember that we are only covering technologies at a high level in this series on the cycle; we will run a second series on detailed technical implementations of data security in the cloud a little later. Definition Share includes controls we use when exchanging data between users, customers, and partners. Where Use focuses on controls when a user interacts with the data as an individual, Share includes the controls once they start to exchange that data (or back-end data exchange). In cloud computing we see a major emphasis on application and logical controls, with encryption for secure data exchange, DLP/CMP to monitor communications and block policy violations, and activity monitoring to track back-end data exchanges. Cloud computing introduces two new complexities in managing data sharing: Many data exchanges occur within the cloud, and are invisible to external security controls. Traditional network and endpoint monitoring probably won’t be effective. For example, when you share a Google Docs document to another user, the only local interactions are through a secure browser connection. Email filtering, a traditional way of tracking electronic document exchanges, won’t really help. For leading edge enterprises that build dynamic data security policies using tools like DLP/CMP, those tools may not work off a cloud-based data store. If you are building a filtering policy that matches account numbers from a customer database, and that database is hosted in the cloud as an application or platform, you may need to perform some kind of mass data extract and conversion to feed the data security tool. Although the cloud adds some complexity, it can also improve data sharing security in a well-designed deployment. Especially in SaaS deployments, we gain new opportunities to employ logical controls that are often difficult or impossible to manage in our current environments. Although our focus is on cloud-specific tools and technologies, we still review some of the major user-side options that should be part of any data security strategy. Steps and Controls Control Structured/Application Unstructured Activity Monitoring and Enforcement Database Activity Monitoring Cloud Activity Monitoring/Logs Application Activity Monitoring Network DLP/CMP Endpoint DLP/CMP Encryption Network/Transport Encryption Application-Level Encryption Email Encryption File Encryption/EDRM Network/Transport Encryption Logical Controls Application Logic Row Level Security None Application Security see Application Security Domain section Activity Monitoring and Enforcement We initially covered Activity Monitoring and Enforcement in the Use phase, and many of these controls are also used in the Share phase. Our focus now switches from watching how users interact with the data, to when and where they exchange it with others. We include technologies that track data exchanges at four levels: Individual users exchanging data with other internal users within the cloud or a managed environment. Individual users exchanging data with outside users, either via connections made from the cloud directly, or data transferred locally and then sent out. Back-end systems exchanging data to/from the cloud, or within multiple cloud-based systems. Back-end systems exchanging data to external systems/servers; for example, a cloud-based employee human resources system that exchanges healthcare insurance data with a third-party provider. Database Activity Monitoring (DAM): We initially covered DAM in the Use phase. In the Share phase we use DAM to track data exchanges to other back-end systems within or outside the cloud. Rather than focusing on tracking all activity in the database, the tool is tuned to focus on these exchanges and generate alerts on policy violations (such as a new query being run outside of expected behavior), or track the activity for auditing and forensics purposes. The challenge is to deploy a DAM tool in a cloud environment, but an advantage is greater visibility into data leaving the DBMS than might otherwise be possible. Application Activity Monitoring: Similar to DAM, we initially covered this in the Use phase. We again focus our efforts on tracking data sharing, both by users and back-end systems. While it’s tougher to monitor individual pieces of data, it’s not difficult to build in auditing and alerting for larger data exchanges, such as outputting from a cloud-based database to a spreadsheet. Cloud Activity Monitoring and Logs: Depending on your cloud service, you may have access to some level of activity monitoring and logging in the control plane (as opposed to building it into your specific application). To be considered a Share control, this monitoring needs to specify both the user/system involved and the data being exchanged. Network Data Loss Prevention/Content Monitoring and Protection: DLP/CMP uses advanced content analysis and deep packet inspection to monitor network communications traffic, alerting on (and sometimes enforcing) policy violations. DLP/CMP can play multiple roles in protecting cloud-based data. In managed environments, network DLP/CMP policies can track (and block) sensitive data exchanges to untrusted clouds. For example, policies might prevent users from attaching files with credit card numbers to a cloud email message, or block publishing of sensitive engineering plans to a cloud-based word processor. DLP can also work in the other direction: monitoring data pulled from a cloud deployment to the desktop or other non-cloud infrastructure. DLP/CMP tools aren’t limited to user activities, and can monitor, alert, and enforce policies on other types of TCP data exchange, such as FTP, which might be used to transfer data from the traditional infrastructure to the cloud. DLP/CMP also has the potential to be deployed within the cloud itself, but this is only possible in a subset of IaaS deployments, considering the deployment models of current tools. (Note that some email SaaS providers may also offer DLP/CMP as a service). Endpoint DLP/CMP: We initially covered Endpoint DLP/CMP in the Use phase, where we discussed monitoring and blocking local activity. Many endpoint DLP/CMP tools also track network activity – this is useful as a supplement when the endpoint is outside the corporate network’s DLP/CMP coverage. Encryption In the Store phase we covered encryption for protecting data at rest.

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