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Posts Tagged ‘linkedin’

Destination Reached: CISSP

Friday, July 2nd, 2010

CISSP logoI am happy to report that I have been awarded the Certified Information Systems Security Professional (CISSP) by the International Information Systems Security Certification Consortium [(ISC)2]a.

I started pursuing the certification in mid-2009, got serious about studying early this year (2010), took the exam in late April, was notified that I passed and had my background endorsed in May, had to update my resume for an auditor in early June and was awarded the CISSP designation at the end of June.

I felt that this certification was important both professionally and personally.

Professionally, the certification serves as a validation that I have a solid and broad understanding of information systems’ security.  People who have worked with me know that I have been focused on IS security for many years.

Whether performing security-centered code reviews, fixing flawed implementations or teaching designers and developers how to improve the security of their systems, I have been on a mission to mentor and train people to observe effective security practices and principles.  I’ve also had operational responsibility for system infrastructures.  With that experience I was able to pass GIAC’s GSEC and Red Hat’s RHCE exams several years ago.

Personally, the process of studying and passing the exam allowed me to pursue and attain a non-trivial goal.  I am enrolled and taking classes toward my master’s degree, but completing that work will require several more years of part time attendance.  Setting and achieving intermediate goals helps to keep me focused and learning.

If you are wondering what the CISSP is all about, please read on.

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My First Semantic Web Program

Saturday, June 5th, 2010

I have create my first slightly interesting, to me anyway, program that uses some semantic web technology.  Of course I’ll look back on this in a year and cringe, but for now it represents my understanding of a small set of features from Jena and Pellet.

The basis for the program is an example program that is described in Hebler, Fischer et al’s book “Semantic Web Programming” (ISBN: 047041801X).  The intent of the program is to load an ontology into three models, each running a different level of reasoner (RDF, RDFS and OWL) and output the resulting assertions (triples).

I made a couple of changes to the book’s sample’s approach.  First I allow any supported input file format to be automatically loaded (you don’t have to tell the program what format is being used).  Second, I report the actual differences between the models rather than just showing all the resulting triples.

As I worked on the code, which is currently housed in one uber-class (that’ll have to be refactored!), I realized that there will be lots of reusable “plumbing” code that comes with this type of work.  Setting up models with various reasoners, loading ontologies, reporting triples, interfacing to triple stores, and so on will become nuisance code to write.

Libraries like Jena help, but they abstract at a low level.  I want a semantic workbench that makes playing with the various libraries and frameworks easy.  To that end I’ve created a Sourceforge project called “Semantic Workbench“.

I intend for the Semantic Workbench to provide a GUI environment for manipulating semantic web technologies. Developers and power users would be able to use such a tool to test ontologies, try various reasoners and validate queries.  Developers could use the workbench’s source code to understand how to utilize frameworks like Jena or reasoner APIs like that of Pellet.

I invite other interested people to join the Sourceforge project. The project’s URL is: http://semanticwb.sourceforge.net/

On the data side, in order to have a rich semantic test data set to utilize, I’ve started an ontology that I hope to grow into an interesting example.  I’m using the insurance industry as its basis.  The rules around insurance and the variety of concepts should provide a rich set of classes, attributes and relationships for modeling.  My first version of this example ontology is included with the sample program.

Finally, I’ve added a semantic web section to my website where I’ll maintain links to useful information I find as well as sample code or files that I think might be of interest to other developers.  I’ve placed the sample program and ontology described earlier in this post on that page along with links to a variety of resources.

My site’s semantic web page’s URL is: http://monead.com/semantic/
The URL for the page describing the sample program is: http://monead.com/semantic/proj_diffinferencing.html

Database Refactoring and RDF Triples

Wednesday, May 12th, 2010

One of the aspects of agile software development that may lead to significant angst is the database.  Unlike refactoring code, the refactoring of the database schema involves a key constraint – state!  A developer may rearrange code to his or her heart’s content with little worry since the program will start with a blank slate when execution begins.  However, the database “remembers.”  If one accepts that each iteration of an agile process produces a production release then the stored data can’t be deleted as part of the next iteration.

The refactoring of a database becomes less and less trivial as project development continues.  While developers have IDE’s to refactor code, change packages, and alter build targets, there are few tools for refactoring databases.

My definition of a database refactoring tool is one that assists the database developer by remembering the database transformation steps and storing them as part of the project – e.g. part of the build process.  This includes both the schema changes and data transformations.  Remember that the entire team will need to reproduce these steps on local copies of the database.  It must be as easy to incorporate a peer’s database schema changes, without losing data, as it is to incorporate the code changes.

These same data-centric complexities exist in waterfall approaches when going from one version to the next.  Whenever the database structure needs to change, a path to migrate the data has to be defined.  That transformation definition must become part of the project’s artifacts so that the data migration for the new version is supported as the program moves between environments (test, QA, load test, integrated test, and production).  Also, the database transformation steps must be automated and reversible!

That last point, the ability to rollback, is a key part of any rollout plan.  We must be able to back out changes.  It may be that the approach to a rollback is to create a full database backup before implementing the update, but that assumption must be documented and vetted (e.g. the approach of a full backup to support the rollback strategy may not be reasonable in all cases).

This database refactoring issue becomes very tricky when dealing with multiple versions of an application.  The transformation of the database schema and data must be done in a defined order.  As more and more data is stored, the process consumes more storage and processing resources.  This is the ETL side-effect of any system upgrade.  Its impact is simply felt more often (e.g. potentially during each iteration) in an agile project.

As part of exploring semantic technology, I am interested in contrasting this to a database that consists of RDF triples.  The semantic relationships of data do not change as often (if at all) as the relational constructs.  Many times we refactor a relational database as we discover concepts that require one-to-many or many-to-many relationships.

Is an RDF triple-based database easier to refactor than a relational database?  Is there something about the use of RDF triples that reduces the likelihood of a multiplicity change leading to a structural change in the data?  If so, using RDF as the data format could be a technique that simplifies the development of applications.  For now, let’s take a high-level look at a refactoring use case.

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Business Ontologies and Semantic Technologies Class

Sunday, May 9th, 2010

Last week I had the pleasure of attending Semantic Arts’ training class entitled, “Designing and Building Business Ontologies.”  The course, led by Dave McComb and Simon Robe, provided an excellent introduction to semantic technologies and tools as well as coverage of ontological best practices.  I thoroughly enjoyed the 4-day class and achieved my principle goals in attending; namely to understand the semantic web landscape, including technologies such as RDF, RDFS, OWL, SPARQL, as well as the current state of tools and products in this space.

Both Dave and Simon have a deep understanding of this subject area.  They also work with clients using this technology so they bring real-world examples of where the technology shines and where it has limitations.  I recommend this class to anyone who is seeking to reach a baseline understanding of semantic technologies and ontology strategies.

Why am I so interested in semantic web technology?  I am convinced that structuring information such that it can be consumed by systems, in ways more automated than current data storage and association techniques allow, is required in order to achieve any meaningful advancement in the field of information technology (IT). Whether wiring together web services or setting up ETL jobs to create data marts, too much IT energy is wasted on repeatedly integrating data sources; essentially manually wiring together related information in the absence of the computer being able to wire it together autonomously!

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Full Disk Encryption – A (Close to Home) Case Study

Wednesday, April 28th, 2010

This is a follow-up to my previous entry regarding full disk encryption (see: http://monead.com/blog/?p=319).  In this entry I’ll look at Blue Slate’s experience with rolling out full disk encryption company-wide.

Blue Slate began experimenting with full disk encryption in 2008.  I was actually the first user at our company to have a completely encrypted disk.  My biggest surprise was the lack of noticeable impact on system performance.  My machine (Gateway M680) was running Windows XP and I had 2GB of RAM and a similarly-sized swap space.  Beyond a lot of programming work I do video and audio editing.  I did not notice significant impact on editing and rendering of such projects.

Later in 2008, we launched a proof of concept (POC) project involving team members from across the company (technical and non-technical users).  This test group utilized laptops with fully encrypted drives for several months.  We wanted to assure that we would not have problems with the various software packages that we use. During this time we went through XP service pack releases, major software version upgrades and even a switch of our antivirus solution.  We had no reports of encryption-related issues from any of the participants.

By 2009 we were focused on leveraging full disk encryption on every non-server computer in the company.  It took some time due to two constraints.

First, we needed to rollout a company-wide backup solution (as mentioned in my previous post on full disk encryption, recovery of files from a corrupted encrypted device is nearly impossible).  Second, we needed to work through a variety of scheduling conflicts (we needed physical access to each machine to setup the encryption product) across our decentralized workforce.

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Full Disk Encryption – Two Out of Three Aren’t Bad

Wednesday, April 14th, 2010

Security is a core interest of mine.  I have written and taught about security for many years; consistently keeping our team focused on secure solutions, and am in pursuit of earning the CISSP certification.  Some aspects of security are hard to make work effectively and other aspects are fairly simple, having more to do with common sense than technical expertise.

In this latter category I would put full disk encryption.  Clearly there are still many companies and individuals who have not embraced this technique.  The barrage of news articles describing lost and stolen computers containing sensitive information on unencrypted hard drives makes this point every day.

This leads me to the question of why people don’t use this technology.  Is it a lack of information, limitations in the available products or something else?  For my part I’ll focus this posting on providing information regarding full disk encryption, based on experience. A future post will describe Blue Slate’s deployment of full disk encryption.

Security focuses on three major concepts, Confidentiality, Integrity and Availability (CIA).  These terms apply across the spectrum of potential security-related issues.  Whether considering the physical environment, hardware, applications or data, there are techniques to protect the CIA within that domain.

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Privacy Lost – Unmasking Masked Data

Thursday, April 1st, 2010

Privacy is an issue which is consistently in the news.  Large amounts of data are stored by retailers, governments, health care providers, employers and so forth. Much of this data contains personal information.  Keeping that data private has proven itself to be a difficult task.

We have seen numerous examples of unintended data loss (unintended by the company whose systems are stolen or attacked).

We hear about thefts of laptops containing personal information for hundreds of thousands of people.  Internet-based attacks that allow attackers access to financial transaction data and even rogue credit card swiping equipment hidden in gas pumps have become background noise in a sea of leaked data.  This is an area that gets the lion’s share of attention in the media and by security professionals.

Worse than these types of personal data loss, because they are completely preventable, are those that are predicated on a company consciously releasing their customer data.  Such companies always assume that they are not introducing risk, but often they are.  In all cases, if the owner of the data had simply held it internally no privacy loss would have occurred.

There have been cases of personal data loss due to mistakes in judgment.

AOL released a large collection of search data to researchers.  The people releasing the data didn’t consider this a risk to privacy.  How could the search terms entered by anonymous people present a risk to privacy?

Of course we now now know that within the data were people’s social security numbers (SSN), phone numbers, credit card numbers and so forth.  Why?  Well, it turns out that some people will search for those things, quite possibly to prove to themselves that their data is safe.  What better way to see if your SSN or credit card number is published on the Internet than by typing it into a search engine?  No matches, great!

Personal data has even been lost by companies releasing data after attempting to mask or anonymize it.

The intent of masking is to remove enough information, the personally identifying information (PII), so that the data cannot be associated with real people. Of course this has to be done without losing the important details that allow patterns and relationships in the data to be found.

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Encapsulation, It Isn’t Just For Your Public Interface

Tuesday, March 23rd, 2010

Encapsulation, one of Object Orientation’s (OO) “Big Three” (or four if you include composition), is the concept most often forgotten when I ask an interview candidate to define the key tenants of OO.  Giving the benefit of the doubt, perhaps it is considered “obvious” and hence not necessarily related to OO design in the person’s mind.  Once I bring it up though, there is usually agreement that it is an important aspect to achieving significant value from OO design.

Classically, encapsulation, also called information hiding, “serves to separate the contractual interface of an abstraction and its implementation.”1 The idea is that the user of the functionality only knows about the public interface (contractual interface) and has no knowledge, nor any ability to tie itself, to the implementation.  The implementation includes both data representation and, effectively, algorithm.

Many times I’ll get an alternate definition; essentially the respondent will define encapsulation as, “as an approach which allows an object’s behavior to be called without the caller having knowledge of how the behavior is implemented.”  This seems very close to the classical definition but misses the key point of “contractual interface.”

I could argue that when any method is called the caller doesn’t have knowledge of how the method is implemented; it just gets a value back.  The missing aspect, the key aspect, is the constraint regarding which methods the caller may call, e.g. the public interface.

What started me on this topic was a recent conversation with a peer regarding read-only objects.  Before I get into specifics, let me baseline the traditional encapsulation approach in a typical object.

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Cut Waste, Not Costs

Monday, March 15th, 2010

As I read more and more about the Toyota debacle I’m struck by an apparently myopic management drive to cut costs.  In the case of Toyota it appears that cost cutting extended into quality cutting.  A company once known for superb quality had methodically reduced that aspect of their output.  This isn’t just conjecture; it seems that people inside the company had been aware of a decline in quality due to a focus on reducing costs.1 Is there a general lesson to consider?

I believe the failure is one of misplaced focus. The focus when Toyota began cutting costs was to remove waste.  That waste could be found throughout their manufacturing processes.  Wasted materials, productivity, tooling, and equipment were all identified as Toyota’s management and workers struck out on a journey to reduce waste and improve productivity.  They ushered in a set of practices that others would soon adopt.

Head back to the 1950′s and you’ll find Taiichi Ohno2 hard at work addressing myriad manufacturing shortcomings at Toyota.  Mr. Ohno is really the father of lean manufacturing and just-in-time inventory management.  He didn’t name them as such.  He was just trying to remove waste from the entire manufacturing process.  By the late 1990′s these concepts had become standard operating procedure at many firms.

It makes sense that a business would focus on reducing waste.  Although it may require effort to remove waste without reducing productivity, overall one would expect a leaner process to have an overall efficiency gain.  It would also seem that quality does not benefit from waste.  After many years of experience with these principles, companies have found that an approach of using only the resources that are needed when they are needed provides a sound basis for their operations.  So what happened at Toyota?  They apparently went beyond cutting waste.

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