When eCommerce companies want to optimize information security, password management tools enable users to create strong passwords for every login.

Better than a Master Pass
A two-factor authentication, a security process in which the user provides two means of identification, one of which is typically a physical token, such as a card, and the other of which is typically something memorized, such as a security code can drastically reduce online fraud such as identity theft . A common example of two-factor authenticationis a bank card: the card itself is the physical item and the personal identification number (PIN) is the data that goes with it.

LastPass 3.0 Premium and RoboForm, security downloads offer fingerprint-based authentication features that can be configured to any computer PC or mobile application.  Both are supported by the Google Authenticator mobile app for smart phone and device integration.

LastPass 3.0 is most powerful on-demand password manager on the market. LastPass 3.0 Premium includes mobile support and more features. Dashlane 2.0 is is not as robust, but includes a user-friendly interface. F-Secure Key is a free, one-device version of these top competitors. F-Secure Key is for exclusive use on an installed device, so password safe retention is dependent on proprietary use of the device itself. The application can be upgraded for a small annual fee.

Password Manager App Cross-Portability
F-Secure Key syncs with Mac, PC Android, and iOS devices simultaneously. A transient code is generated on mobile devices, in addition to the two-factor authentication default of the F-Secure Key master password security product.

Password capture and replay in case of lost credentials is made possible with a password manager. Integration of a password manager app with a browser allows a user to capture login credentials, and replay on revisit to a site. Dashlane, LastPass, Norton Identity Safe, Password Genie 4.0 offer continuous detection and management of password change events, automatically capturing credentials each time a new Web-based, service registration sign up is completed.

Other applications like F-Secure Key, KeePass, and My1login replay passwords via a bookmarklet, supported by any Java-equipped browser. KeePass ups the ante for would be keyloggers, with a unique replay technology.

Personal Data and Auto-Fill Forms
Most password managers fill username and password credentials into login forms automatically. Password managers also retain personal data for form fill interfaces with applications, and other HTML forms online. The RoboForm app is one of the most popular for its flexibility in multi-form password and personal data management, but the others also capture and reuse at least a portion of what has been entered in a form manually.

The 1Password app for Windows stores the most types of personal data for use to fill out forms. Dashlane, LastPass, and Password Genie store the various types of ID data used for form fill-in, like passport and driver's license numbers and other key details to HTML acknowledgement of discretionary password and personal information.

The Cost of Protection
LastPass Premium and Password Box are the lowest monthly password manager plans on the market, going for $1 a month. Annual plans offered by other password manager sources vary according to internal plan: Dashlane $20, F-Secure Key $16, and Password Genie, $15.
All password manager companies and their products may not be alike in the end.

Security checks on security products like password managers have become more sophisticated in response to product cross-portability and open source app interface volatility. Norton, RoboForm, KeePass, generate strong, random passwords on-demand. Some security procedures now require three-factor authentication, which involves possession of a physical token and a password, used in conjunction with biometricdata, such as finger-scanningor a voiceprint.

What are the best languages for getting into functional programming?

Computer Programming as a Career?

A business rule is the basic unit of rule processing in a Business Rule Management System (BRMS) and, as such, requires a fundamental understanding. Rules consist of a set of actions and a set of conditions whereby actions are the consequences of each condition statement being satisfied or true. With rare exception, conditions test the property values of objects taken from an object model which itself is gleaned from a Data Dictionary and UML diagrams. See my article on Data Dictionaries for a better understanding on this subject matter.

A simple rule takes the form:

if condition(s)

then actions.

An alternative form includes an else statement where alternate actions are executed in the event that the conditions in the if statement are not satisfied:

if condition(s)

then actions

else alternate_actions

It is not considered a best prectice to write rules via nested if-then-else statements as they tend to be difficult to understand, hard to maintain and even harder to extend as the depth of these statements increases; in other words, adding if statements within a then clause makes it especially hard to determine which if statement was executed when looking at a bucket of rules. Moreoever, how can we determine whether the if or the else statement was satisfied without having to read the rule itself. Rules such as these are often organized into simple rule statements and provided with a name so that when reviewing rule execution logs one can determine which rule fired and not worry about whether the if or else statement was satisfied. Another limitation of this type of rule processing is that it does not take full advantage of rule inferencing and may have a negative performance impact on the Rete engine execution. Take a class with HSG and find out why.

Rule Conditions

Technology has continued to evolve in ways that few would have been able to imagine. This has allowed electronics to become smarter, more connected and far more useful.

With the Internet of Things (IoT), they're allowing more than just computers to become connected to the Internet. This aims to make the life of the average person easier, better and more care-free.

Let's examine why the Internet of Things has become such a powerful idea that an estimated one out of every five developers currently works on an IoT project.


What is the Internet of Things?

The Internet of Things hinges on one seemingly simple concept: electronics can be embedded in machines, clothing, animals and even people to provide a networked world where the whole is more than just the sum of its parts.

For example, consider how the Internet of Things can influence things like refrigerators. They can be networked directly to the manufacturer for readings that can warn if the refrigerator is about to malfunction. They can even be connected to a grocery shopping service to allow someone to restock them automatically or to notify the owner that the refrigerator is almost out of an item.

The most interesting notion about the Internet of Things is that it's not just a situation where one “thing” connects with a party. They typically communicate with other things, which in turn allows for a network of automated processes to occur.

These processes can simplify and expedite tedious tasks to make everyday life for everyone easier, which is why projects involving the Internet of Things are so popular.


How Prevalent is IoT Development?

An estimated one in five developers are currently developing projects for the Internet of Things. Their chosen languages vary widely because of the flexibility that IoT enjoys.

For example, IoT projects that hinge on interacting with mobile phones tend to have apps written in JavaScript or Java. The back-end code that runs the IoT functionality for machines tends to be written in Assembly, C++,Java,Perl,Pythonor another compiled language for efficiency.

To put the growth of IoT work into perspective, Evans Data Corp. performed research to create predictions about IoT projects in 2014. They stated that 17% of companies would be developing IoT projects.

In this year, that figure's risen to a solid 19%. Given the fact that 44% of developers have stated that they will enter into the IoT scene this year or next, this means that development will only grow in the coming future.


The Future Involving the Internet of Things

Development of IoT-related projects will likely explode in the next few years. The advantages it brings, such as more efficient work in manufacturing environments and the projected 15% savings to the restaurant industry over the next five years, will make it one of the most valuable technological changes in the near future.

Without a comprehensive understanding of the Internet of Things and the skills to lead IoT projects, businesses and developers may find themselves falling behind. Don't let the Internet of Things pass you by.

The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

Related:

Who Are the Main Players in Big Data?