Tag Archives: data security
The problem many banks encounter today is that they have vast sums of investment tied up in old ways of doing things. Historically, customers chose a bank and remained ’loyal’ throughout their lifetime…now competition is rife and loyalty is becoming a thing of a past. In order to stay ahead of the competition, gain and keep customers, they need to understand the ever-evolving market, disrupt norms and continue to delight customers. The tradition of staying with one bank due to family convention or from ease has now been replaced with a more informed customer who understands the variety of choice at their fingertips.
Challenger Banks don’t build on ideas of tradition and legacy and see how they can make adjustments to them. They embrace change. Longer-established banks can’t afford to do nothing, and assume their size and stature will attract customers.
Here’s some useful information
Accenture’s recent report, The Bank of Things, succinctly explains what ‘Customer 3.0’ is all about. The connected customer isn’t necessarily younger. It’s everybody. Banks can get to know their customers better by making better use of information. It all depends on using intelligent data rather than all data. Interrogating the wrong data can be time-consuming, costly and results in little actionable information.
When an organisation sets out with the intention of knowing its customers, then it can calibrate its data according with where the gold nuggets – the real business insights – come from. What do people do most? Where do they go most? Now that they’re using branches and phone banking less and less – what do they look for in a mobile app?
Customer 3.0 wants to know what the bank can offer them all-the-time, on the move, on their own device. They want offers designed for their lifestyle. Correctly deciphered data can drive the level of customer segmentation that empowers such marketing initiatives. This means an organisation has to have the ability and the agility to move with its customers. It’s a journey that never ends -technology will never have a cut-off point just like customer expectations will never stop evolving.
It’s time for banks to re-shape banking
Informatica have been working with major retail banks globally to redefine banking excellence and realign operations to deliver it. We always start by asking our customers the revealing question “Have you looked at the art of the possible to future-proof your business over the next five to ten years and beyond?” This is where the discussion begins to explore really interesting notions about unlocking potential. No bank can afford to ignore them.
Original article can be found here, scmagazine.com
On Jan. 13 the White House announced President Barack Obama’s proposal for new data privacy legislation, the Personal Data Notification and Protection Act. Many states have laws today that require corporations and government agencies to notify consumers in the event of a breach – but it is not enough. This new proposal aims to improve cybersecurity standards nationwide with the following tactics:
Enable cyber-security information sharing between private and public sectors.
Government agencies and corporations with a vested interest in protecting our information assets need a streamlined way to communicate and share threat information. This component of the proposed legislation incents organizations that participate in knowledge-sharing with targeted liability protection, as long as they are responsible for how they share, manage and retain privacy data.
Modernize the tools law enforcement has to combat cybercrime.
Existing laws, such as the Computer Fraud and Abuse Act, need to be updated to incorporate the latest cyber-crime classifications while giving prosecutors the ability to target insiders with privileged access to sensitive and privacy data. The proposal also specifically calls out pursuing prosecution when selling privacy data nationally and internationally.
Standardize breach notification policies nationwide.
Many states have some sort of policy that requires notification of customers that their data has been compromised. Three leading examples include California , Florida’s Information Protection Act (FIPA) and Massachusetts Standards for the Protection of Personal Information of Residents of the Commonwealth. New Mexico, Alabama and South Dakota have no data breach protection legislation. Enforcing standardization and simplifying the requirement for companies to notify customers and employees when a breach occurs will ensure consistent protection no matter where you live or transact.
Invest in increasing cyber-security skill sets.
For a number of years, security professionals have reported an ever-increasing skills gap in the cybersecurity profession. In fact, in a recent Ponemon Institute report, 57 percent of respondents said a data breach incident could have been avoided if the organization had more skilled personnel with data security responsibilities. Increasingly, colleges and universities are adding cybersecurity curriculum and degrees to meet the demand. In support of this need, the proposed legislation mentions that the Department of Energy will provide $25 million in educational grants to Historically Black Colleges and Universities (HBCU) and two national labs to support a cybersecurity education consortium.
This proposal is clearly comprehensive, but it also raises the critical question: How can organizations prepare themselves for this privacy legislation?
The International Association of Privacy Professionals conducted a study of Federal Trade Commission (FTC) enforcement actions. From the report, organizations can infer best practices implied by FTC enforcement and ensure these are covered by their organization’s security architecture, policies and practices:
- Perform assessments to identify reasonably foreseeable risks to the security, integrity, and confidentiality of personal information collected and stored on the network, online or in paper files.
- Limited access policies curb unnecessary security risks and minimize the number and type of network access points that an information security team must monitor for potential violations.
- Limit employee access to (and copying of) personal information, based on employee’s role.
- Implement and monitor compliance with policies and procedures for rendering information unreadable or otherwise secure in the course of disposal. Securely disposed information must not practicably be read or reconstructed.
- Restrict third party access to personal information based on business need, for example, by restricting access based on IP address, granting temporary access privileges, or similar procedures.
The Personal Data Notification and Protection Act fills a void at the national level; most states have privacy laws with California pioneering the movement with SB 1386. However, enforcement at the state AG level has been uneven at best and absent at worse.
In preparing for this national legislation organization need to heed the policies derived from the FTC’s enforcement practices. They can also track the progress of this legislation and look for agencies such as the National Institute of Standards and Technology to issue guidance. Furthermore, organizations can encourage employees to take advantage of cybersecurity internship programs at nearby colleges and universities to avoid critical skills shortages.
With online security a clear priority for President Obama’s administration, it’s essential for organizations and consumers to understand upcoming legislation and learn the benefits/risks of sharing data. We’re looking forward to celebrating safeguarding data and enabling trust on Data Privacy Day, held annually on January 28, and hope that these tips will make 2015 your safest year yet.
Informatica users leveraging HDP are now able to see a complete end-to-end visual data lineage map of everything done through the Informatica platform. In this blog post, Scott Hedrick, director Big Data Partnerships at Informatica, tells us more about end-to-end visual data lineage.
Hadoop adoption continues to accelerate within mainstream enterprise IT and, as always, organizations need the ability to govern their end-to-end data pipelines for compliance and visibility purposes. Working with Hortonworks, Informatica has extended the metadata management capabilities in Informatica Big Data Governance Edition to include data lineage visibility of data movement, transformation and cleansing beyond traditional systems to cover Apache Hadoop.
Informatica users are now able to see a complete end-to-end visual data lineage map of everything done through Informatica, which includes sources outside Hortonworks Data Platform (HDP) being loaded into HDP, all data integration, parsing and data quality transformation running on Hortonworks and then loading of curated data sets onto data warehouses, analytics tools and operational systems outside Hadoop.
Regulated industries such as banking, insurance and healthcare are required to have detailed histories of data management for audit purposes. Without tools to provide data lineage, compliance with regulations and gathering the required information for audits can prove challenging.
With Informatica, the data scientist and analyst can now visualize data lineage and detailed history of data transformations providing unprecedented transparency into their data analysis. They can be more confident in their findings based on this visibility into the origins and quality of the data they are working with to create valuable insights for their organizations. Web-based access to visual data lineage for analysts also facilitates team collaboration on challenging and evolving data analytics and operational system projects.
The Informatica and Hortonworks partnership brings together leading enterprise data governance tools with open source Hadoop leadership to extend governance to this new platform. Deploying Informatica for data integration, parsing, data quality and data lineage on Hortonworks reduces risk to deployment schedules.
A demo of Informatica’s end-to-end metadata management capabilities on Hadoop and beyond is available here:
- A free trial of Informatica Big Data Edition in the Hortonworks Sandbox is available here .
Data proliferation has traditionally been measured based on the number of copies data reside on different media. For example, if data residing on an enterprise storage device was backed up to tape, the proliferation was measured by the number of tapes the same piece of data would reside. Now that backups are no longer restricted to the data center and data is no longer constrained by the originating application, this definition is due for an update.
Data proliferation should be measured based on the number of users who have access to or can view the data and that data proliferation is a primary factor in measuring the risk of a data breach. My argument here is that as sensitive, confidential or private data proliferates beyond the original copy, it increases its surface area and proportionally increases its risk of a data breach.
Using the original definition of data proliferation and an example of data storage shown below, data proliferation would include production, production copies used for disaster recovery purposes and all physical backup copies. But as you can see, data is also copied to test environments for development purposes. When factoring in the number of privileged users with access to those copies, you have a different view of proliferation and potential risk.
In the example, there are potentially thousands of copies of sensitive data but only a small number of users who are authorized to access the data.
In the case of test and development, this image highlights a potentially high area of risk because the number of users who could see the sensitive data is high.
Similarly with online advertising, the measure of how many people see an online ad is called an impression. If an ad was seen by 100 online users, it would have 100 impressions.
When you apply that same principal to data security, you could say that data proliferation is a calculation of the number of copies of a data element multiplied by the potential number of users who could physically view the data, or in other words ‘impressions’. In this second image below, rather than considering the total number of copies, what if we measured risk based on the total number of impressions?
In this case, the measure of risk is independent of the physical media the data reside on. You could take this a few steps further and add a factor based on security controls in place to prevent unauthorized access.
The Ponemon Institute stated that the biggest concern for security professionals is that they do not know where sensitive data resides. Informatica’s Intelligent Data Platform provides data security professionals with the technology required to discover, profile, classify and assess the risk of confidential and sensitive data.
Last year, we began significant investments in data security R&D support the initiative. This year, we continue the commitment by organizing around the vision. I am thrilled to be leading the Informatica Data Security Group, a newly-formed business unit comprised of a team dedicated to data security innovation. The business unit includes the former Application ILM business unit which consists of data masking, test data management and data archive technologies from previous acquisitions, including Applimation, ActiveBase, and TierData.
By having a dedicated business unit and engineering resources applying Informatica’s Intelligent Data Platform technology to a security problem, we believe we can make a significant difference addressing a serious challenge for enterprises across the globe. The newly formed Data Security Group will focus on new innovations in the data security intelligence market, while continuing to invest and enhance our existing data-centric security solutions such as data masking, data archiving and information lifecycle management solutions.
The world of data is transforming around us and we are committed to transforming the data security industry to keep our customer’s data clean, safe and connected.
For more details regarding how these changes will be reflected in our products, message and support, please refer to the FAQs listed below:
Q: What is the Data Security Group (DSG)?
A: Informatica has created a newly formed business unit, the Informatica Data Security Group, as a dedicated team focusing on data security innovation to meet the needs of our customers while leveraging the Informatica Intelligent Data Platform
Q: Why did Informatica create a dedicated Data Security Group business unit?
A: Reducing Risk is among the top 3 business initiatives for our customers in 2015. Data Security is a top IT and business initiative for just about every industry and organization that store sensitive, private, regulated or confidential data. Data Security is a Board room topic. By building upon our success with the Application ILM product portfolio and the Intelligent Data Platform, we can address more pressing issues while solving mission-critical challenges that matter to most of our customers.
Q: Is this the same as the Application ILM Business Unit?
A: The Informatica Data Security Group is a business unit that includes the former Application ILM business unit products comprised of data masking, data archive and test data management products from previous acquisitions, including Applimation, ActiveBase, and TierData, and additional resources developing and supporting Informatica’s data security products GTM, such as Secure@Source.
Q: How big is the Data Security market opportunity?
A: Data Security software market is estimated to be a $3B market in 2015 according to Gartner. Total information security spending will grow a further 8.2 percent in 2015 to reach $76.9 billion.
Q: Who would be most interested in this announcement and why?
A: All leaders are impacted when a data breach occurs. Understanding the risk of sensitive data is a board room topic. Informatica is investing and committing to securing and safeguarding sensitive, private and confidential data. If you are an existing customer, you will be able to leverage your existing skills on the Informatica platform to address a challenge facing every team who manages or handles sensitive or confidential data.
Q: How does this announcement impact the Application ILM products – Data Masking, Data Archive and Test Data Management?
A: The existing Application ILM products are foundational to the Data Security Group product portfolio. These products will continue to be invested in, supported and updated. We are building upon our success with the Data Masking, Data Archive and Test Data Management products.
Q: How will this change impact my customer experience?
A: The Informatica product website will reflect this new organization by listing the Data Masking, Data Archive, and Test Data Management products under the Data Security product category. The customer support portal will reference Data Security as the top level product category. Older versions of the product and corresponding documentation will not be updated and will continue to reflect Application ILM nomenclature and messaging.
I hate to break the news but data breaches have become an unfortunate fact of life. These unwanted events are happening too frequently that each time it happens, it feels like the daily weather report. The scary thing about data breaches is that these events will only continue to grow as criminals become more desperate to take advantage of the innocent and data about our personal records, financial account numbers, and identities continues to proliferate across computer systems in every industry from your local retailer, your local DMV, to one of the nation’s largest health insurance providers.
According to the 2014 Cost of Data Breach study from the Ponemon Institute, data breaches will cost companies $201 per stolen record. According to the NY Post, 80 million records were stolen from Anthem this week which will cost employees, customers, and shareholders $16,080,000,000 from this single event. The 80 million records accounted for includes the data they knew about. What about all the data that has proliferated across systems? Data about both current and past customers across decades that was copied onto personal computers, loaded into shared network folders, and sitting there while security experts pray that their network security solutions will prevent the bad guys from finding it and causing even more carnage the this ever growing era of Big Data?If you are worried as much as I am about what these criminals will do with our personal information, make it a priority to protect your data assets in your lives both personal and in business. Learn more about Informatica’s perspectives and video on this matter:
- Data Security – A Major Concern in 2015
- How organizations can prepare for 2015 data privacy legislation
- How Protected is your PHI?
- The CISO Challenge: Articulating Data Worth and Security Economics
- IDC Life Sciences and Ponemon Research Highlights Need for New Security Measures
- Video: Secure@Source – A Data-Centric Approach to Security
Follow me! @DataisGR8
I think I may have gone to too many conferences in 2014 in which the potential of big data was discussed. After a while all the stories blurred into two main themes:
- Companies have gone bankrupt at a time when demand for their core products increased.
- Data from mobile phones, cars and other machines house a gold mine of value – we should all be using it.
My main take away from 2014 conferences was that no amount of data is a substitute for poor strategy, or lack of organisational agility to adapt business processes in times of disruption. However, I still feel as an industry our stories are stuck in the phase of ‘Big Data Hype’, but most organisations are beyond the hype and need practicalities, guidance and inspiration to turn their big data projects into a success. This is possibly due to a limited number of big data projects in production, or perhaps it is too early to measure the long term results of existing projects. Another possibility is that the projects are delivering significant competitive advantage, so the stories will remain under wraps for the time being.
However, towards the end of 2014 I stumbled across a big data success story in an unexpected place. It did (literally) provide competitive advantage, and since it has been running for a number of years the results are plain to see. It started with a book recommendation from a friend. ‘Faster’ by Michael Hutchinson is written as a self-propelled investigation as to the difference between world champion and world class althletes. It promised to satisfy my slightly geeky tendency to enjoy facts, numerical details and statistics. It did this – but it really struck me as a ‘how-to’ guide for big data projects.
Mr Hutchinson’s book is an excellent read as an insight into professional cycling by a professional cyclist. It is stacked with interesting facts and well-written anecdotes, and I highly recommend the reading the book. Since the big-data aspect was a sub-plot, I will pull out the highlights without distracting from the main story.
Here are the five steps I extracted for big data project success:
1. Have a clear vision and goal for your project
The Sydney Olympics in 2000 had only produced 4 medals across all cycling disciplines for British cyclists. With a home Olympics set for 2012, British Cycling desperately wanted to improve this performance. Specific targets were clearly set across all disciplines stated in times that an athlete needed to achieve in order to win a race.
2. Determine data the required to support these goals
Unlike many big data projects which start with a data set and then wonder what to do with it, British Cycling did this the other way around. They worked out what they needed to measure in order to establish the influencers on their goal (track time) and set about gathering this information. In their case this involved gathering wind tunnel data to compare & contrast equipment, as well as physiological data from athletes and all information from cycling activities.
3. Experiment in order to establish causality
Most big data projects involve experimentation by changing the environment whilst gathering a sub-set of data points. The number of variables to adjust in cycling is large, but all were embraced. Data (including video) was gathered on the effects of small changes in each component: Bike, Clothing, Athlete (training and nutrition).
4. Guide your employees on how to use the results of the data
Like many employees, cyclists and coaches were convinced of the ‘best way’ to achieve results based on their own personal experience. Analysis of data in some cases showed that the perceived best way, was in fact not the best way. Coaching staff trusted the data, and convinced the athletes to change aspects of both training and nutrition. This was not necessarily easy to do, as it could mean fundamental changes in the athlete’s lifestyle.
5. Embrace innovation
Cycling is a very conservative sport by nature, with many of the key innovations coming from adjacent sports such as triathlon. Data however, is not steeped in tradition and does not have pre-conceived ideas as to what equipment should look like, or what constitutes an excellent recovery drink. What made British Cycling’s big data initiatives successful is that they allowed themselves to be guided by the data and put the recommendations into practice. Plastic finished skin suits are probably not the most obvious choice for clothing, but they proved to be the biggest advantage cyclist could get. Far more than tinkering with the bike. (In fact they produced so much advantage they were banned shortly after the 2008 Olympics.)
The results: British Cycling won 4 Olympic medals in 2000, one of which was gold. In 2012 they grabbed 8 gold, 2 silver and 2 bronze medals. A quick glance at their website shows that it is not just Olympic medals they are wining – but medals won across all world championship events has increased since 2000.
To me, this is one of the best big data stories, as it directly shows how to be successful using big data strategies in a completely analogue world. I think it is more insightful that the mere fact that we are producing ever-increasing volumes of data. The real value of big data is in understanding what portion of all avaiable data will constribute to you acieving your goals, and then embracing the use the results of analysis to make constructive changes in daily activities.
But then again, I may just like the story because it involves geeky facts, statistics and fast bicycles.
I have to admit, I was one of those who saw the movie and found the film humorous to say the least and can see why a desperate regime like North Korea would not want their leader admitting they love margarita’s and Katy Perry. What concerned me about the whole event was whether these unwanted security breaches were now just a fact of life? As a disclaimer, I have no affinity over the downfall of the North Korean government however what transpired was fascinating and amazing that companies like Sony continue to struggle to protect sensitive data despite being one of the largest companies in the world.
According to the Identity Theft Resource Center, there were 761 reported data security breaches in 2014 impacting over 83 million breached records across industries and geographies with B2B and B2C retailers leading the pack with 79.2% of all breaches. Most of these breaches originated through the internet via malicious WORMS and viruses purposely designed to identify and rely back sensitive information including credit card numbers, bank account numbers, and social security information used by criminals to wreak havoc and significant financial losses to merchants and financial institutions. According to the 2014 Ponemon Institute Research study:
- The average cost of cyber-crime per company in the US was $12.7 million this year, according to the Ponemon report, and US companies on average are hit with 122 successful attacks per year.
- Globally, the average annualized cost for the surveyed organizations was $7.6 million per year, ranging from $0.5 million to $61 million per company. Interestingly, small organizations have a higher per-capita cost than large ones ($1,601 versus $437), the report found.
- Some industries incur higher costs in a breach than others, too. Energy and utility organizations incur the priciest attacks ($13.18 million), followed closely by financial services ($12.97 million). Healthcare incurs the fewest expenses ($1.38 million), the report says.
Despite all the media attention around these awful events last year, 2015 does not seem like it’s going to get any better. According to CNBC just this morning, Morgan Stanley reported a data security breach where they had fired an employee who it claims stole account data for hundreds of thousands of its wealth management clients. Stolen information for approximately 900 of those clients was posted online for a brief period of time. With so much to gain from this rich data, businesses across industries have a tough battle ahead of them as criminals are getting more creative and desperate to steal sensitive information for financial gain. According to a Forrester Research, the top 3 breach activities included:
- Inadvertent misuse by insider (36%)
- Loss/theft of corporate asset (32%)
- Phishing (30%)
Given the growth in data volumes fueled by mobile, social, cloud, and electronic payments, the war against data breaches will continue to grow bigger and uglier for firms large and small. As such, Gartner predicts investments in Information Security Solutions will grow further 8.2 percent in 2015 vs. 2014 reaching $76.9+ billion globally. Furthermore, by 2018, more than half of organizations will use security services firms that specialize in data protection, security risk management and security infrastructure management to enhance their security postures.
Like any war, you have to know your enemy and what you are defending. In the war against data breaches, this starts with knowing where your sensitive data is before you can effectively defend against any attack. According to the Ponemon Institute, 18% of firms who were surveyed said they knew where their structured sensitive data was located where as the rest were not sure. 66% revealed that if would not be able to effectively know if they were attacked. Even worse, 47% were NOT confident at having visibility into users accessing sensitive or confidential information and that 48% of those surveyed admitted to a data breach of some kind in the last 12 months.
In closing, the responsibilities of today’s information security professional from Chief Information Security Officers to Security Analysts are challenging and growing each day as criminals become more sophisticated and desperate at getting their hands on one of your most important assets….your data. As your organizations look to invest in new Information Security solutions, make sure you start with solutions that allow you to identify where your sensitive data is to help plan an effective data security strategy both to defend your perimeter and sensitive data at the source. How prepared are you?
For more information about Informatica Data Security Solutions:
A few years ago the former eBay’s CISO, Dave Cullinane, led a sobering coaching discussion on how to articulate and communicate the value of a security solution and its economics to a CISO’s CxO peers.
Why would I blog about such old news? Because it was a great and timeless idea. And in this age of the ‘Great Data Breach’, where CISOs need all the help they can get, I thought I would share it with y’all.
Dave began by describing how to communicate the impact of an attack from malware such as Aurora, spearfishing, stuxnet, hacktivision, and so on… versus the investment required to prevent the attack. If you are an online retailer and your web server goes down because of a major denial of service attack, what does that cost the business? How much revenue is lost every minute that site is offline? Enough to put you out of business? See the figure below that illustrates how to approach this conversation.
If the impact of a breach and the risk of losing business is high and the investment in implementing a solution is relatively low, the investment decision is an obvious one (represented by the yellow area in the upper left corner).
However, it isn’t always this easy, is it? When determining what your company’s brand and reputation worth, how do you develop a compelling case?
Another dimension Dave described is communicating the economics of a solution that could prevent an attack based on the probability that the attack would occur (see next figure below).
For example, consider an attack that could influence stock prices? This is a complex scenario that is probably less likely to occur on a frequent basis and would require a sophisticated multidimensional solution with an integrated security analytics solution to correlate multiple events back to a single source. This might place the discussion in the middle blue box, or the ‘negotiation zone’. This is where the CISO needs to know what the CxO’s risk tolerances are and articulate value in terms of the ‘coin of the realm’.
Finally, stay on top of what the business is cooking up for new initiatives that could expose or introduce new risks. For example, is marketing looking to spin up a data warehouse on Amazon Redshift? Anyone on the analytics team tinkering with Hadoop in the cloud? Is development planning to outsource application test and development activities to offshore systems integrators? If you are participating in any of these activities, make sure your CISO isn’t the last to know when a ‘Breach Happens’!
To learn more about ways you can mitigate risk and maintain data privacy compliance, check out the latest Gartner Data Masking Magic Quadrant.
In the report, Gartner cites. “Global-scale scandals around sensitive data losses have highlighted the need for effective data protection, especially from insider attacks. Data masking, which is focused on protecting data from insiders and outsiders, is a must-have technology in enterprises’ and governments’ security portfolios.”
Organizations realize that data protection must be hardened to protect against the inevitable breach; originating from either internal or external threats. Data masking covers gaps in data protection in production and non-production environments that can be exploited by attackers.
Informatica customers are elevating the importance of data security initiatives in 2015 given the high exposure of recent breaches and the shift from just stealing identities and intellectual property, to politically charged platforms. This raises the concern that existing security controls are insufficient and a more data-centric security approach is necessary.
Recent enforcement by the Federal Trade Commission in the US and emerging legislation worldwide has clearly indicated that sensitive data access and sharing should be tightly controlled; this is the strength of data masking.
Data Masking de-identifies and/or de-sensitizes private and confidential data by hiding it from those who are unauthorized to access it. Other terms for data masking include data obfuscation, sanitization, scrambling, de-identification, and anonymization.
To learn more, Download the Gartner Magic Quadrant Data Masking Report now. And visit the Informatica website for data masking product information.
About the Magic Quadrant
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.