The more we depend on technology to do business, the more critical cybersecurity becomes. In this age of remote work, companies are relying on more third-party tools and employee devices. Each of those devices and applications represents a potential access point for cybercriminals. Here are five technologies shaping the future of cybersecurity.

The good news is, technology can also be used to combat cyber threats.

Not only can the right software stop breaches now, but these sophisticated tools can be continuously tweaked as new threats continue to evolve.

Here are five technologies shaping the future of cybersecurity:

1. Security Orchestration, Automation, and Response (SOAR)

SOAR security is a suite of technologies that allow businesses to automate some security processes. Typically used in combination with SIEM systems, SOAR closes the gap between incident identification and response.

SIEM systems are great at telling businesses what the issue is. The trouble with them is two-fold: IT personnel sometimes lack the expertise to stop threats; even if they have that expertise, much of the damage is done in milliseconds.

To understand how SOAR systems work, let’s break down the acronym:

• Security Orchestration

Security technologies need to work in concert with one another. Orchestration is the process of stringing them together so action can be taken swiftly from a single dashboard.

• Automation

No technology can totally eliminate the need for security experts. But by automating certain steps of the process, SOAR reduces response time and the risk of human error.

• Response

Unlike prior software approaches, SOAR can actually stop certain threats. Because breaches cause reputational damage to brands even if no customer data is compromised, preventing them is key.

2. Cloud Access Security Broker (CASB)

These days, cloud computing and storage is the standard. Most business applications are hosted remotely, which often allows apps to be accessed from anywhere and on multiple devices.

Naturally, easy access attracts bad actors. Any time data is transferred, it has the potential to be intercepted. Protecting your devices during transfer is where Cloud Access Security Brokers (CASBs) come into play.

CASBs sit between a cloud application and the cloud users, carefully monitoring activity. Sometimes CASBs are in-house software, but they can also be cloud-based programs themselves.

CASBs have a couple of use cases. Some of these access security brokers simply notify administrators about potential incidents. Others work to prevent malware or man-in-the-middle attacks.

3. User and Entity Behavior Analytics

User and Entity Behavior Analytics (UEBA) systems detect insider threats by monitoring users and entities, which include things like routers. They use a combination of machine learning and human decision-making.

If appropriate access restrictions have not been put in place it’s easy for insiders to access sensitive files. UEBA tools analyze users’ behavior patterns and look for anomalies that could indicate malicious activity.

For example, let’s say a particular employee downloads a few images and Word documents each day. Then one day, that person downloads several gigabytes of files. A UEBA tool would flag that download — and either take action or notify an administrator.

4. Hardware Authentication

It’s no secret that most login credentials can be cracked by dedicated hackers. If all it takes is one username and password to access your sensitive data — from any device, anywhere in the world — you’re devices can be in trouble.

Hardware authentication requires not just a username and password, but also a hardware-based approval from a separate device. There are multiple ways hardware authentication can be done:

• USB security keys

These small devices (sometimes called “tokens”) plug into a USB port to authenticate the user. Using a token will add a layer of protection because the key must be physically possessed, which is difficult to do from a remote location.

• Optical recognition

An optical recognition factor is a futuristic tool that reads your retina and matches it to a database to verify you are authorized to access the network. Each person’s retinas have unique patterns, just like fingerprints.

• Finger swipes

Your smartphone might let you login by pressing your finger to a small sensor. Finger swipes work the same way, by using your fingerprints to authenticate you.

5. Data Loss Prevention (DLP)

Often, cybercriminals either sell sensitive data or post it online. Once your sensitive data is out on the internet — getting it taken down is a nightmare. To recover from these attacks, companies often have to send embarrassing emails to customers and reset thousands of accounts and passwords.

DLP is a collection of software and approaches designed to keep sensitive data from leaving the organization’s own network. DLP systems combine a lot of best practices, including:

• Identifying what data is sensitive
• Monitoring and controlling endpoint activities, or how users access information
• Checking data that is uploaded and downloaded from the cloud for malicious software
• Producing reports to stay compliant with governing agencies
• Encrypting data in transit

Cybersecurity technologies aren’t just cool, complex things to talk about. They’re essential tools that protect your business from fraud, data leaks, malware, and more.

Knowing what tools are available to you is, at best, half the battle. Don’t wait until a breach happens to put these “data-best-practices” into your data-protection arsenal.

Image Credit: Soumil Kumar; Pexels

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Data breaches are happening at an alarming rate. The first half of 2019 saw 4.1 billion compromised records, with the business sector accounting for 67% of the reported breaches and 84.6% of exposed records.

People are starting to take the protection of their own digital identities more seriously.

According to a recent privacy survey, 81% of consumers are more concerned about how companies use their data and 89% say companies should be clearer about how their products use data.

This is why more than 80 countries and regions have adopted comprehensive data protection laws and others will soon follow. But are these laws really working to keep the massive amounts of personal data from falling into the wrong hands?

Regulations like GDPR and the California Consumer Privacy Act (CCPA) are developed with the intent to protect the privacy of consumers in an age where social media and other digital footprints are making it harder to keep that personal information safe and secure.

There are two interesting factors in play that exempt companies from disclosing what they plan to do with the consumer data they collect in certain situations.

Exemptions

In section 1798.105(d), CCPA states, “a business or service provider shall not be required to comply with a consumer’s request to delete the consumer’s personal information if it is necessary for the business or service provider to maintain the customer’s personal data in order to detect security incidents, protect against malicious, deceptive, fraudulent, or illegal activity; or prosecute those responsible for that activity.”

The statement appears to exempt anyone in cybersecurity from the request if they can prove the data is required to meet one of those activities.

Items within certain security platforms that leverage the device and user identity for detection can operate under this exclusion, which is something both the security vendor and customer should, therefore, be cognizant of.

Services Provided

Additionally, section item 1798.105(3) of CCPA states that business shall not be required to comply with the act if they provide a service to “debug to identify and repair errors that impair existing intended functionality.”  

Read that statement again, please!

It opens another huge exception for businesses that debug or repair devices. It appears they are removed from any responsibility to destroy or delete the data after any period of time.

Another implication of this “law” ties into the consumer’s right to repair. Consider a consumer who has their private data stored on a personal device but modifies or repairs that device in some way that leaves the device susceptible to attack or breach.

Who is responsible? The manufacturer or the consumer?

CCPA does not provide guidance on this leaving ambiguity and potential loopholes.

While businesses may comply within these exemptions and services loopholes, that shouldn’t exclude them from the basic ethical obligation they have to inform their customers on what they plan to do with their data.

And these exemptions aren’t winning any favors with consumers, which is why nearly half of Americans don’t trust the government or social media sites to protect their data.

While governments are attempting to help by enacting privacy legislation, consumers must take the protection of their privacy into their own hands by following a few basic guidelines.

Don’t Open that Link

Phishing attempts have grown 65% in the last year and those attacks account for 90% of data breaches. And attackers are finding new ways to make their phishing scams even harder to detect.

An example shows how these attacks are now happening in real-time. The bad actor pretends to be known to the user who claims to have limited cellphone reception, so a confirmation call is not possible. The victim then helps, which then leads to handing over sensitive data to the attacker.

While phishing is getting harder to detect, there are ways to defend against them.

For instance, if there is a request to click on a link, CHECK to see if there any misspellings or weird characters in the URL.

In these cases, it’s a safe bet you can just delete the email (and link) right away.

Make it a habit to avoid clicking on links sent to you via email or social media solutions – especially those from your bank, utility companies, social networks, etc.

Instead, go to the source and type out the URL in the browser and login there.

Multi-Factor Authentication

Multi-factor authentication is one of the easiest ways to protect one’s information, yet many consumers don’t know this capability exists. With multi-factor authentication, a user is asked to provide two or more pieces of information for logging into his/her devices.

For example, along with providing a password, an individual can arrange to have a code sent to their device before access is granted. When you login this way, if an unauthorized third-party somehow steals the password, they still can’t log into the account because they won’t receive the follow up mobile text code.

Many consumer services like Google and Facebook support this capability and individuals are well-advised to use this extra security.

Multiple Passwords

People still fall victim to bad password habits despite the incentives to avoid them.

Using unique passwords for all accounts helps ensure hackers only gain access to the one system associated with that password.

You can check sites like haveibeenpwned.com to determine if your information was lost in a breach.

Please use different passwords for every account — whether it’s for business or personal use.

I know it’s a pain in the butt — however, the longer the password, the better. Password manager applications can then help you store all of these passwords securely and protect them with multi-factor authentication.

There is no one sure-fire way to ensure that the billions of global data records remain protected.

Privacy regulations are a first (and much needed) step in the right direction. However, it’s up to everyone – including consumers – to do their part in protecting their personal identities online.

The post Privacy Regulations — Are They Really Working to Protect Your Data? appeared first on ReadWrite.

Data analyst is the process in which the judgment, refining, changing, and modeling data takes place with the aim of making a better conclusion. Data analysis takes part in an important role, it helps in generating scientific conclusions and also increases the regulations in an organization. Here are six skills you need to become a data analyst.

Data-Driven Business Strategies

Today, with the deepening of the concept of data operation, more and more companies are aware of the value of data-driven business strategies and emphasize the participation of all employees in data operations. Developing the ability to analyze data is also a future trend.

A data analyst is someone who accumulates data, processes, and performs analysis of data. He or she can interpret numbers and data into simple English in order to help organizations and companies understand how to make better business decisions.

At its core, data analysis means taking a business question or need and turning it into a data question. Then, you’ll need to transform and analyze data to extract an answer to that question.

Companies of today realize how data-driven strategy is important to them and they are in need of talented individuals who can provide insights into a constant stream of collected information.

Types of Data Analysts

• Finance
• Data assurance
• Business Intelligence
• Marketing
• Sales

The types of data analyst listed above are some of the most challenging fields which require a data analyst in their management.

Here are 6 skills you need to become a data analyst.

1. MATHEMATICAL SKILLS

Mathematical skills are important for making a profession in data analysis, as you have to play with numbers and figures all through the day. Necessary mathematics skills include:

*One should be good at calculations

*Measuring and analyzing data

*Having the ability to organize information

*One should know how to schedule and budget

Mathematical skills help in having better problem-solving skills — and also helps in financing our individual businesses.

2. ANALYTICAL SKILLS

As it is called, It is clear that analytical skills are the huge significance of data analysis. These skills include assembling, sorting, and analyzing all kinds of raw data in particular. It also helps you to view provocation or situation from a different angle. Hence, If you want to be a professional data analyst then you need to widen your analytical skills and thinking. Analytical skills help in viewing a challenge or situation from different perspectives. It is one of the most important and efficient parts of the skill you need to become a data analyst.

3. TECHNICAL SKILLS

Good computer and technical skills are very important. The main knowledge of statistics is quite helpful as well as producing languages like python or Mat Lab, and analytical languages like R and SAS are very favorable to know as a data analyst.

The more language you know, the faster and better for you to get your dream job. Examples of technical skills you need to know are:

• Programming languages.
• Common operating systems.
• Software proficiency.
• Technical writing.

4. DETAILS SKILLS

Data analyst is all about details, It helps a data analyst to be able to find and see any basic unseen errors and links, that is especially important at the point of solving problems and making decisions.

5. BUSINESS SKILLS

Aside from the technical skills, there are some business skills that one should acquire to function as a Data analyst. Some of which are:

Communication Skills:

As a data analyst, you are expected to work with different sets of people in your team which makes your communication a really important part of your job. Working well together as a team for the benefit of your organization is also one of your main responsibilities and skill.

You should be able to communicate effectively with the teammates to prepare, present, and explain data. Communication is key in collaborating with your colleagues. For example, in a kickoff meeting with business stakeholders, careful listening skills are needed to understand the analyses they require.

Similarly, during your project, you may need to be able to explain a complex topic to non-technical teammates.

Time Management and Organizational Skills:

As it is expected of you to work with different people in your team. You should be able to manage your time including your responsibilities, as well as meet your deadlines.

Decision-making and Problem-solving:

These skills are the bottom line of data analysis. The main job of a data analyst is to give the right information for decision-making and problem-solving process. Which is why it occurs to be a perfect skill required to be a data analyst.

You might need to research a quirk of some software or coding language that you’re using. Your company might have resource constraints that force you to be innovative in how you approach a problem.

The data you’re using might be incomplete. Or you might need to perform some “good enough” analysis to meet a looming deadline.

6. DOMAIN KNOWLEDGE

Domain knowledge is understanding things that are specific to the particular industry and company that you work for. For example, if you’re working for a company with an online store, you might need to understand the nuances of e-commerce. In contrast, if you’re analyzing data about mechanical systems, you might need to understand those systems and how they work.

Domain knowledge changes from industry to industry, so you may find yourself needing to research and learn quickly. No matter where you work if you don’t understand what you’re analyzing it’s going to be difficult to do it effectively, making domain knowledge a key data analyst skill.

Remember that Domain knowledge is certainly something that you can learn on the job, but if you know a specific industry or area you’d like to work in, building as much understanding as you can upfront will make you a more attractive job applicant and a more effective employee once you do get the job.

Once you have the skills mentioned above — you can use them to attract attention to yourself so as to get your dream job. These are the criteria you need for the data analyst skills checklist.

Academic Background

A bachelor’s degree is often necessary, not all the time though. To work as a data analyst you need to acquire a degree in any of these Science courses.

• Economics
• Business information systems
• Mathematics
• Statistics
• Computer science

As much as the above degrees are important for your success — what matters the most are the skills that you possess. Right now during the COVID-19 problems may be the time for you to upgrade yourself and your skills.

Conclusion

Data analysis is speedily growing field and skilled data analysts are huge in demand throughout the country, in every industry. This means that you would find many opportunities only if you are exceptional and show your excellent data analytic skills.

The post 6 Skills You Need to Become a Data Analyst appeared first on ReadWrite.

The world is in between huge technological transition. Every day there is more use of technology-intensive tools in place of traditional ones. Old tricks used to be tedious, costly, mostly false, and often harmful.  As a result, business intelligence is not what it use to mean a decade ago.

Today, increased automation is making companies to go on the look-out for up-to-date business intelligence software to keep up with the new global technology order. We know that data is the main part that is driving this change. Take for example our growing need for datification to improve our minor as well as major affairs.

Companies around the world are using datification to turn our daily lives into a huge mass of data. This is why datification is the heart of data science. This unique field of science works closely with business intelligence (BI) and many other fields e.g., scientific computing, exploratory statistics, etc., to be able to infer active meaning via data handling.

What is business intelligence and BI Software?

To put it simply, BI is a technology-based process that puts raw data into a readable form. Business and data specialists figure out this raw data and turn it into easy visual facts to aid the decision-making process. Because people tend to make better decisions when they have better information.

BI uses many software with technical and nontechnical sides to turn data into useful facts. These facts greatly assist business organizations in making the right decisions as well as solve serious problems.

The usual BI process takes many complex tools, software applications, and special methods. BI helps businesses in setting up an extensive data collection mechanism through many different sources. The sources usually hold a huge amount of data. The data is then explored, modeled, and analyzed by using highly advanced tools to identify irregularities, patterns, concerns, and trends.

The purpose of extracting information through this process is to develop infographics, dashboards, analytical outcome reports, etc. All of this information communicates results with corporate executives or anyone with the power to make strategic business decisions.

Best Business Operating System

We could go about making a case of one OS against the other and confuse you to no limit. Or we could straight away get down to the best possible option and tell you why it is, in fact, the best for you. We choose to go with the latter. Because frankly, the whole point of this article is to make seemingly difficult choices easy for you.

The saturated spectrum of OS gives us the same names whenever we need a system in tune with our interests.

It usually renders people to believe that compatible or not, only these few names e.g., Windows, macOS, Unix, Android, etc., are their possible options. However, if you dig a little to look behind the obvious you will find the most well-matched solution seemingly hiding in the shadows.

Although the best OS option – Linux – for businesses that we intend to talk about today is not actually hiding in the crowd, it is still not much talked about especially given the unending list of values it is adding to businesses worldwide.

If you, like many others, have missed the appearance of Linux operating systems as a worthwhile alternative to nearly all the existing OS, now is the time to rectify that. it is being estimated that Linux is set to replace the OS arena as you know it today due to its dizzying range of futuristic features that are sweeping the technology bigwigs off their feet. take Huawei reliance on Linux Deepin for its MateBook laptop for example.

Why go with Linux for your business?

2020 is not just the year of further technical advancement if anything, 2020 seems to be more business-centric than anything else regardless of the subject area or nature. The technological progress of businesses can only be ensured if the in-house IT infrastructures are up to date. For cloud computing though, Linux is proving to be an unparalleled fit and rather an inexpensive fit for businesses.

You will also find that the integration of Linux systems is quite simple depending on the specific Linux distribution –  distro – you select in coordination with your computing requirement. The best still is the fact that you don’t have to discard your standing infrastructure to appropriate the flexibility that open-source software and cost-effective functionality of Linux provides. It is literally a free replacement for other OSs, which businesses find more than a little hard to comprehend.

Linux does not require purchase prizes even for the applications unless you are a kind of business that needs expert help from paid tech support. Even that can be worked away, given the variety of Linux system administrator training programs available today which effectively ticks an overhead off the list of businesses’ overall cost.

Best Linux for Businesses in 2020

So how do you figure out which distro is the best fit for your business? Because Linux OS comes in a vast variety with several futuristic business-grade features. Well, we have put together a list of top of the range distribution based on a criterion that includes:

• Stability
• Practicality
• Support

Let’s have a look at some of the best Linux in 2020 with critical uptime, unwavering support, and practical capabilities.

CentOS

CentOS is one of the most popular Linux server distributions. Linux has developed CentOS on the foundation of Red Hat Enterprise Linux (RHEL) by the funding support of Red Hat in 2014. Assembled with pleasant Gnome – the default desktop for Red Hat & Fedora – familiarity along with widely supported Red Hat package manager (RPM) open-source, CentOS makes for a highly compatible enterprise-class Linux distro for workstations and servers.

Slackware

Slackware is the oldest Softlanding based Linux distro which is active to date. Patrick Volkerding created it in 1993. Slackware provided bases for many distributions like SUSE Linux distro. It provides end-users maximum control than any other Linux OS but this feature has both sides to consider. For instance, while it gives you huge command control, this lightweight distribution lacks the graphical configuration and software dependency resolution mechanism. If you are looking for a customized distro, Slackware is the one to suit your requirements,

ClearOS

This Linux distro specifically optimizes small and medium enterprises. It serves as a network gateway as well as a network server that you can administer completely from a web-based interface. ClearOS is an effective alternative to commercially supported software solutions with professional tech support availability. Like CentOS, this distribution also has a relatively simple configuration and maintenance due to innate RHEL foundation packages. But the similarities cease here because unlike CentOS, ClearOS is strictly a server platform. Its absolute web reliance proffers the use of varying consoles unnecessary after the distro installation.

Ubuntu

The ever increasing popularity of Ubuntu – Linux desktop distribution – make people think that it is most compatible with personal usage. Which is hardly true given its well-recognized community support system. Ubuntu provides its end-users absolute stability and flexibility along with the free version called Ubuntu Servers for the backend requirement.

Ubuntu is designed based on another Linux distro named Debian. It means Ubuntu can use Debian packages using advanced package tools (Apt) management system to add or remove software. If you choose to select Ubuntu as your Linux OS, you will have the finest support from its massive userbase. The latest releases are marketed as long term support (LTS) backed distros with 5 years maintenance option for professional tech support.

IPFire

IPFire distro is often regarded as a Linux watchdog due to its extraordinary security solutions. This is especially relevant to small businesses that are more susceptible to cyber threats to the security of their networks. Install this distribution and leave it to manage the IP addresses, firewall protection, and employee monitoring for safety or behavioral check. Although it is not difficult to maintain, IPFire will surely require expert-level knowledge to get it installed and running.

There are several reasons for its complex configuration. For example; distinct nature from any other Linux versions, Tor node, proxy protocols, etc. There are several Linux administrator training programs available that should solve these support issues in the installation process of IPFire.

OpenSUSE

OpenSUSE or more accurately SUSE Linux Professional is another Linux distribution community program. It is powered by SUSE Linux GmbH to be used as the basis for commercial SUSE Enterprise. Contrary to CentOS and ClearOS, OpenSUSE is designed with a strong desktop environment that has its window manager called K development environment (KDE). KDE comes with a graphical interface that makes it a heavyweight distro to be highly compatible with timeworn hardware systems. For instance,  Raspberry Pi single-board computers. It is a stable and secure OS due to the latest release of rolling models that has consistent update availability.

Best Business Intelligence Software for 2020

Often the term business intelligence refers to a vast range of brilliant BI software. Software that quickly accesses and analyzes data sets to provide easily understandable and actionable information in the form of:

1. Analytical reports
2. Insightful summaries
3. Dashboards and ad hoc queries
4. Graphs, charts, and maps

Yet, the hunt for just perfect business intelligence software can be a somewhat daunting and costly process. Especially if we consider the fact this software often delivers more than what’s required by small or medium-sized organizations. The good news is that there are many free BI tools maintained by highly skilled developers motivated to break BI monopoly.

Seven of the most optimal free BI software for you to start taking advantage of data analytics — and these cost less.

ChartMogul BI Software

ChartMogul is one of the most popular BI software that manages an extensive user community rather smoothly. It is known to provide the best services to businesses that are working to build a subscription package. It is possible due to its churn rate measurement and customer value features.

QlikView

QlikView is an exceptional ETL data storage and multilayered analysis BI software. Presented by Qlik, this tool also offers an end-user dashboard that connects different data sources to develop data visualizations.

Cluvio

Cluvio is programming language compatible business intelligence software. It lets businesses to process data written in SQL, R, etc., against their databases to produce data visualization and dashboards. It also provides webinars and online training to help businesses get started.

ActivTrak Business Intelligence Software

ActivTrak – released by Birch Grove Software – is a behavior analytics software that can sustain the teams of 5 to 1,000. This BI tool is designed for business, IT, and HR executives, managers. It also assists team leaders to track the overall status and productivity. ActivTrak also comes with both the iOS and Android compatible apps.

Databox

Databox is known to be a powerhouse of the best business intelligence software. It has an impressive interface and simple functionality that allow businesses to keep tabs of key performance indicators (KPI). It presents dashboard reports and information that can be shared on multiple devices. Databox also comes with integrated systems like Adobe Analytics along with iOS and Android compatible mobile app.

Tableau

Tableau, true to its name, is an Excel-based BI software. It is perfect for those who enjoy data analysis within pivot tables. It has an advanced user interface that offers a drag-and-drop feature for data manipulation and visualizations.

Kyubit Business Intelligence Software

Kyubit BI – powered by Kyubit Solutions – is another programming language assimilated business intelligence software. It allows businesses to develop reports off their SQL, CSV, OLAP, etc., data. It is an ideal tool for those with a little bit of knowledge of data analytics or business intelligence mechanisms.

You can install these free BI software from the cloud, web portals, and SAAS and offer 24/7 live support availability.

Significance of Business Intelligence

Today, optimizing BI is no longer considered the province of only mega-corporations. Because affording data centers and computing powers that are required to analyze business data was not for average businesses. Courtesy to inexpensive data-analysis tools today and BI software even small and medium businesses are benefitting from the BI revolution.

An effective business intelligence program can improve business decision making at all levels which leads to improved organization’s tactical management processes. To improve every aspect of the company, businesses need to develop central association. It is only possible with establishing better access to the company’s data. Because after all data is the main factor that brings forth the maximum profitability.

BI and Data Science

Business Intelligence (BI) is a subdivision of data analytics that takes a predetermined set of processes, technologies, strategic architecture to transform the raw data into actionable business intelligence (information).

BI is designed to employs a reverse approach in which it analyzes past data to solve the current problems. Although, this approach provides tactical reports that contain factual statistics but they cannot predict future events. That is where the distinction between business intelligence and data science begins. You use data in an advancing approach to predict the future outcome in data science to make profitable business decisions.

Business Intelligence in data science works by combining business analytics, data mining, data visualization, input/output bounds tools, and data infrastructure, to augment businesses’ decision-making abilities. BI integrated into data-science methods is the faster way of reporting and communicating results through specialized business intelligence software tools.

Specialized business intelligence software tools include:

• SAP Business Intelligence
• Oracle BI
• Microsoft Power BI
• SAS Business Intelligence

At the end of the day, all the areas that we talked about above and more are businesses. You just cannot be a  good data scientist for an organization if you do not have great business intelligence skills. BI as a system connects all the skills that a business has.

So, if you want to work in the field of business intelligence you must get the following few skills:

1. Experience with data analysis tools and SQL Programming
2. Data warehousing concepts
3. Problem-solving techniques
4. Domain knowledge

Conclusion

Today is the right time to take full advantage of the BI software system for your business. Invest in BI training programs, best OS, business intelligence software for good results. Keeping up with technology is no longer a matter of choice for organizations. Today it is a matter of survival for businesses around the world regardless of the size of the company.

The post Best Business Intelligence Software and Business Operating System Options for 2020 appeared first on ReadWrite.

In 2020, phishing is among the most common forms of cyberattacks on businesses and individuals alike. 56% of IT decision-makers state that phishing attacks are the top security threat they are facing, with 32% of hacks involving phishing. Here is video phishing and how you protect yourself.

Phishing is no longer limited to emails from Nigerian princes offering the recipients massive returns on investments.

Many phishing messages and websites have become sophisticated to the point that users are no longer able to recognize them without specific training. Google now blacklists an average of 50,000 websites for phishing every week.

On the upside, the ways that you can protect yourself from phishing attacks have evolved as well in recent years. They range from using up-to-date firewall software to using secure platforms such as cloud-based business phone services.

A new threat is looming on the horizon: video phishing.

Driven by technological advances, artificial intelligence, and machine learning, this new trend has the potential of causing catastrophic security breaches.

Keep reading to find out what video phishing is, what it looks like, and how you can protect yourself.

How does Video Phishing work?

Surprise! Elon Musk is interrupting your Zoom call.

Sounds fake? It is.

But it looks disturbingly real.

See the end of the document for embed.

The video above shows an application of Avatarify, a tool developed by a researcher to transform users into celebrities in real-time during Zoom or Skype calls. Its inventor, Ali Aliev, says that the program’s purpose was to have some fun during COVID-19 lockdown — by surprising friends during video conferences as Albert Einstein, Eminem, or the Mona Lisa.

The technology behind donning someone else’s animated face like a mask is called deepfaking.

Deepfakes are relatively new applications of machine learning tools. These tools generate realistic faces by analyzing thousands of videos and images of a target’s face and extracting patterns for common expressions and movements. Then, these patterns can be projected onto anyone, effectively morphing them into someone else.

You use the image of  Elon Musk. Or President Obama. In fact, a deep fake video of the former President calling his successor ‘a total and complete dips**t’ went viral back in 2018.

The implications of this technology for cybersecurity are wide-reaching and potentially disastrous.

Because instead of trolling your friends, or insulting President Trump via someone famous deepfakes — you won’t know if it’s friends being comical — or the dangerous, video phishing.

What are the Dangers of Video Phishing?

According to CNN, the majority of deepfake videos on the internet as of the end of 2019, were pornography. In total, 15,000 of such videos were counted. That might not sound like much, considering the vastness of the internet.

The reason for these rather limited numbers has been that generating convincing deepfakes takes a fair amount of computational power. Avatarify, for example, takes a high-level gaming PC to run properly.

But lower-quality applications have already been developed, such as a face-swapping app that got banned again fairly quickly.

It is only a question of time before deepfake technology becomes widely available. And widely used for cybercrime.

Some of these scams have already been recorded and you can find them on YouTube.

In one case, hackers used similar technology to deepfake the voices of CEOs and sent voicemail messages to executives. They succeeded in effecting a transfer of a mind-boggling $243,000.

In another case, three men were arrested in Israel for swindling a businessman out of $8 million by impersonating the French foreign minister.

Experts are already warning against other possible applications of deepfake videos for frauds to generate funds. One scenario, for example, is extortion. Hackers could threaten the release of a video containing content that can be damaging to a person’s or business’ reputation. Such content could range from straight-out pornography to the CEO of a company endorsing racist views.

As experiences have shown, that could be disastrous. For businesses, even the regular kind of ‘fake news’ can have catastrophic impacts on industry relationships, and even their stock market values.

“Those kinds of things can put a company out of business through reputation damage,” Chris Kennedy of the AI cyber-security platform AttackIQ said in a recent interview with Forbes. “We’re hitting the tipping point in which technology is taking advantage of the biggest human weakness, we’re over-trusting.”

How to Defend Yourself against Deepfake Video Phishing

Today, having a high cybersecurity standard is more important than ever. With online life proliferating during the COVID-19 crisis, scams and phishing attacks have flourished as well.

The good news in the case of phishing videos is that the technology, as of 2020, is still relatively new, and the case numbers relatively low. That means that individuals and businesses have time to prepare, and disseminate information to ward against such attacks.

Know the basic defense moves

As a most basic form of defense, extreme caution is advised if you receive an unsolicited video call, especially from someone famous or in a position of authority. Never trusting caller IDs, hanging up immediately, and not sharing any information on such calls is essential.

If you receive video messages that might be authentic, but you are uncertain about it, you can use software to determine if what you are facing is a deep fake. For example, companies such as Deeptrace offers software with the capacity to recognize AI-generated video content.

Apart from that, some low-tech solutions to protect against video phishing are having agreed-upon code words when communicating about sensitive information via video messaging, using a second communication channel to confirm information, or asking security questions that your interlocutor can only answer if they are the real deal.

Basically, pretend you’re in an old James Bond film. ‘In London, April’s a Spring month’ and all that.

Final Thoughts

Using AI to morph into someone else and extract sensitive information may still sound futuristic. But it is only a question of time until video phishing hits the mainstream.

As technology advances and artificial intelligence and machine learning applications to copy the face and voice of people become widely available, the number of deepfake scams is set to go through the roof.

The best you can do, is to be aware, keep informed, and brace yourself. Keep safe.

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Location intelligence has gained much attention lately, especially as more businesses harness the power of this technology. Location intelligence builds on geographical information systems (GIS) tools, and its definition goes beyond the analysis of geospatial or geographic information. Here is how location intelligence will create even smarter cities.

Location Intelligence is the ability to visualize spatial data to identify and analyze relationships and trends.

The output of location intelligence is actionable insights that help both the public and private sectors to detect patterns and make strategic decisions.

Location intelligence comes from a multitude of sources, such as GPS systems, Internet of Things (IoT) data, and environmental and consumer sources. The technology is not one specific tool but rather the ability to use geospatial data to create business insights. As location intelligence grows in popularity, because its uses are multiplying, it has had an impact on an interesting global technological development: smart cities.

Location intelligence use cases.

Before diving into the implications of location intelligence on smart cities, it’s important to take a step back and look at where this technology has already made an impact.

The insurance industry.

The insurance industry has been leading the charge in the use of location intelligence. By knowing, with high accuracy, if a property is located in a flood, earthquake, or wildfire zone, insurance carriers can more draft accurate policies.

Furthermore, this technology allows carriers to take a more proactive, instead of reactive approach. Instead of simply paying out claims, these companies can help homeowners proactively protect their properties and mitigate risk by understanding the potential damage based on the area.

Financial institutions.

Financial institutions are also using location intelligence to improve fraud detection by better analyzing customer profiles. By matching customer locations and transactions, banks can better understand fraudulent behavior and avoid flagging normal activity.

Both finance companies and retail companies are also using location intelligence to send customers offers when they are near a specific store. Retail companies are taking this a step further by mapping customer behavior in-store to optimize store layout and inventory management.

As more and more industries harness the power of location intelligence, the public and the private sectors are also looking at this technology as a means to create better smart cities around the world.

Location intelligence growing smart cities.

The IESE Cities in Motion Index (CIMI) uses nine dimensions to measure the development of smart cities: human capital, social cohesion, economy, environment, governance, urban planning, international outreach, technology, and mobility and transportation.

The 2019 index (From the Business School at The University of Navarra) named London, New York, and Amsterdam as the smartest global cities based on these criteria, after reviewing 165 cities in 80 countries. Location intelligence plays a critical role in many of these nine dimensions, namely four key parts of any smart city.

Environment

Location intelligence can help with two parts related to the environment. First, natural disasters happen in large cities around the world, causing devastating consequences. From filing damage reports to opening lines of communication, location intelligence can help cities rebuild faster.

Second, location intelligence can help city developers better understand where to plan conservation projects and create green spaces around the city. The technology can also analyze air quality and measure the environmental impact a project will have during and after construction.

Urban planning

Location intelligence is crucial to 3D planning, which has become a considerable part of urban development. From the experimentation phase through construction, this technology helps make sure city planning improves the lives of those in the city and can also help to track and measure operational costs.

Technology

Technology powers almost every aspect of a smart city. According to IESE, (Media iese.edu research, University of Navarra) technology, “is an aspect of society that improves the present quality of life, and its level of development or spread is an indicator of the quality of life achieved or the potential quality of life.

In addition, technological development is a dimension that allows cities to be sustainable over time and to maintain or extend the competitive advantages of their production system and the quality of employment.” Location intelligence clearly aids in this endeavor, as both individuals and cities can use this technology to improve smart city functionality.

Mobility and transport

Smart cities around the globe are revolutionizing transportation using location and mobile data to improve traffic and congestion and optimize travel. City planners are able to harness location data to figure out where traffic is the heaviest, when, and why. Using that information, they can then solve these transit problems with new construction or more modes of transport.

Challenges: Privacy and security.

Data collection happens constantly. From ride sharing apps to food delivery services, consumers are constantly giving out location-based data. While the benefit of this is more customized services, the challenge is consumers are more aware and concerned about how their data is used.

Not only has customer awareness increased, but restrictions such as GDPR have forced companies to be more transparent in personal data collection. Furthermore, as technology advances, so do hackers intent on infiltrating these systems. Security concerns are widespread across the industry, and breaches come with heightened consequences.

On the privacy side, more consumer awareness might end up helping improve location intelligence. Consumers taking control of their data means smart cities can rely more on first-party data, rather than third-party aggregators who may not provide the most accurate data.

On the security side, this challenge will likely always remain and will take a combination of individuals protecting their own data and companies providing more transparent data use initiatives to tackle this challenge.

Location intelligence, however, will continue to grow and aid in the creation of better, smarter cities. Especially as this technology advances, and more cities compete to implement smart initiatives, more will come to rely on location intelligence as the crucial component.

Image Credit: Scott Webb; Pexels

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