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The Basics of Cloud Computing Security

Enterprises using cloud computing

According to Gartner, the size of the global Cloud Computing market is projected to grow 17.3 % in 2019 with a total of $206.2 billion, up from $175.8 billion in 2018. These numbers demonstrate that Cloud computing is becoming mainstream in enterprise IT. By having a data storage in clouds business can benefit from a lower IT costs with greater scalability and greater reliability compared to having resources in their own data center. Study has also highlighted that the fastest-growing segment of the market is cloud system infrastructure services, also known as, SaaS or IaaS, which is forecast to grow 27.6% in 2019 to reach $39.5 billion, up from $31 billion in 2018.

 

In addition to these numbers, a recent study by Eurostat comes to the conclusion that “26 % of EU enterprises used cloud computing in 2018, mostly for hosting their e-mail systems and storing files in electronic form. 55 % of those firms used advanced cloud services relating to financial and accounting software applications, customer relationship management or to the use of computing power to run business applications. In 2018, many more firms used public cloud servers (18 %) than private cloud servers (11 %), i.e. infrastructure for their exclusive use”.

 

Compared with 2014, the use of cloud computing increased with more than 21%, particularly in large enterprises. These numbers will certainly go-up and companies must prepare themselves from “what-if” scenarios. “What-if” they have little or no control over data, such as a loss of service or a hacker attack.

Outsourcing means losing significant control over data. Even with a huge success of Cloud, few large companies don’t want to run a program delivered in the cloud that risk compromising their data through interaction with some other program. As they want to maintain full control over who has access to their data.

 

In addition to no control over data, companies are quite concerned about the risk of seizure. It means that if they opt to choose a public cloud, they are sharing computing resources with other companies. Exposing their data in an environment which is shared with other companies could give the government / federal authorities “reasonable cause” to seize your assets in case if another company has violated the law. Simply because you share the environment in the cloud, may put data at risk of seizure. The only protection against the risk of seizure is to encrypt their data. Even if cloud provider is forced, by law, to turn over user’s data and any access he might have to that data, as he won’t have user’s access or decryption keys, shearing data won’t be a risk. To get at the data, the court will have to come to user and subpoena user. As a result, user will end up with the same level of control user have in his private data-centre.

 

Plus, when it comes to encryption management in heterogeneous IT landscapes, IT managers should consider multi-vendor management tools that provide a 360-degree view of how all resources are encrypted and managed. Encryption key management and endpoint authentication are also centralized and server-based with these tools, often based on existing network policies, such as Active Directory databases. It is impossible to achieve infrastructure-wide encryption and security compliance without proper management tools. If the administration is difficult, mistakes happen. Protecting data in heterogeneous IT infrastructures with a high cloud and virtualization share is a tightrope walk that is sure to become no less complex in the future.

 

Next biggest concern, of companies, in adoption of Cloud is the failure of cloud provider to properly secure portions of its own infrastructure, especially in the maintenance of physical access control, which may result in the compromise of subscriber systems. Cloud can comprise multiple entities, and in such a configuration, no cloud can be more secure than its weakest link. It is expected that customer must check on regular basis and trust provider’s security. For small and medium size businesses provider security may exceed customer security. It is generally difficult for the details that help ensure that the right things are being done.

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In general cloud computing provides persuasive benefits in IT world but it’s not completely secure and risk free in terms of data security challenges. Cloud performance can be affected in case of security issues. Therefore, cloud computing providers are responsible for good care of security in systems and data. Cloud computing providers are good in many ways, sometimes better than some in-house IT. The reliability of cloud providers can be classified much better than some internal infrastructure, as they master all features of their logiciel.

 

For each cloud service that has been mentioned above, the cloud service provider provides some security measures. For example, that IaaS service provider only allows connectivity from specific IP addresses in their Access Control List (ACL). PaaS service providers only allow certain usernames and passwords. SaaS service providers also limit their service to those who already have the security token before utilizing the software.

 

In any case, before implementing cloud in your enterprise eco-system, one must analyze and identify appropriate security risks and overcome issues such as virtualization, authentication mechanisms and cryptography techniques and protect the confidentiality, integrity and availability of data regardless of the form the data may take.

 

Most businesses today rely on diverse IT infrastructures with different operating systems and multi-cloud environments. Despite all successes, the basic challenge remains. Data must be protected. Protecting this data is not just about protection against hackers. Good governance is also required to ensure that all dealings with this data in order to comply with legal privacy and compliance requirements and industry specific requirements.

Sources :
–Gartner Forecasts Worldwide Public Cloud Revenue to Grow 17.3 Percent in 2019
–Service Market for Data Center by Service Type (Design & Consulting, Installation & Deployment, Professional, Training & Development, Maintenance & Support), Tier Type, End-User, Data Center Type, Industry, and Region – Global Forecast to 2022
–Cloud computing – statistics on the use by enterprises

3 Basic A’s of Identity and Access Management -Authentication, Authorization, and Accounting

 

Identity and Access Management Model

The number of data breach incidents has continued to increase in the past year. Identity and access management is one of the basic security measures in this context to prevent any injuries from these breaches. And the goal of IAM to continuously secure, measure, monitor and improve access to identity and data assets bymaking sure that users can access necessary resources while following a prescribed process. It’s an effective and forward-looking method against data breaches.

 

Down to the basics, a breach of privacy is nothing more than breach of security leading to the accidental or unlawful destruction, loss, alteration, unauthorized disclosure of, or access to, private data transmitted, stored or otherwise processed. Despite all this awareness, most companies take IAM serious only when it is too late. They must not ignore that preventing cybercriminals from entering a network, getting business data, stealing it, and misusing it can be avoided by implementing a multi-layered security approach.

When using identity and access management, remember the basic three A’s: Authentication, Authorization, and Accounting.

 

Authentication

 

Authentication is based on the idea that each individual user has unique information that sets him or her apart from other users to provide proof of identity when they identify themselves. It ensures that the person who logs on to a system is actually the person who claims to be. The easiest way an attacker can access a company’s IT systems is by obtaining someone’s credentials. Like the passwords of any X employee working in any X organization. Phishing, social engineering or simple theft are common methods. The network can not recognize that it is the wrong person and will allow the attacker to access all data that the user has access to. IAM procedures and technologies help to get the authentication problem under control. Authentication can take place as an individual process or can be combined with authorization and accounting.

 

An effective password strategy is the key to an effective authentication process. These include the frequent change of passwords, a strict password policy and processes that protects data from outsiders. The basic problem with passwords, however, is that employees usually have so many of them that they are hard to remember and sometimes they have same passwords for different applications. Single sign-on technologies offer a solution to this problem. SSO means that after a one-time authentication, a user can access all the computers and services that he is authorized to access without having to log in each time.

 

In the meantime, there are also password management tools in which the user can manage, reset and re-assign his passwords via a self-service portal. These tools ensure that the selected password meets the strict requirements.  Most companies are moving toward Multi-Factor Authentication (MFA) or Two-Factor Authentication (2FA) which leverages a static password and challenge question to strengthen cybersecurityby adding a second layer of security that requires additional authentication.

 
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Authorization

 

It’s the process of granting or denying a user access to system resources once the user has been authenticated through the username and password. The amount of information and the amount of services the user has access depend on the rights the users have.Proper and complete authorization is the key to preventing data breaches. Effective IAM solutions ensure that users only have access to the data they really need and are assigned to their login credentials. And these solutions prevent a user from having too much access to sensitive data he should not have by giving sufficient access necessary to perform their required functions, and nothing more.

 

Administrator must have an eye on the access permissions and disactivate the open functions when they are no longer needed in order to avoid any accidental or malicious violations of security objectivesEmployees and service providers who no longer work for the company X should immediately be deprived of their assigned access rights. Without effective identity management, a business cannot be sure who can access what systems and whether an attacker might use accounts to gain access to sensitive data.

 

Accounting

 

Accounting means keeping an eye on user’s activity, access and data they have access to do their jobs while they are on companies’ network. It also includes the amount of time a X user spend to do X job. Having track of all above mentioned activities helps to detect breaches, tracing back to events leading up to a cybersecurity incident and forensic investigations.

 

If all the players of a team pull together and each player fills his position, then no power in the world can bring them down. Security requires a comprehensive approach and implementation of IAM concepts such as strong authentication, granular authorization, and powerful privileged access management and accounting to put cybercriminals in their place.

 

Sources :
–Planning Guide for Identity and Access
–Identity and access management Beyond compliance

Artificial Intelligence – Existing Educational Systems and Next Generation Jobs

Artificial Intelligence in education

 

Artificial intelligence has existed as a field for more than 50 years, but in pace with technological developments in recent years, the area has found increasing numbers of applications and has been the subject of increasing attention. New methods and technologies mean that the mobile phone not only understands what we say, but also translates between languages ​​as quickly as we speak, recognizes faces. There are methods and technologies of artificial intelligence that lie at the core of self-driving cars and robots that perform precise surgical procedures. Facial recognition in stores, robotic sellers who submit offers based on past behaviors, facial recognition in stores, language assistants (like Alexa or Google Home) who are always listening and making recommendations based on recorded conversations. Al is a subject area that is changing how we live and work and how the future will be.

 

With all these AI advances, the demand for expertise in artificial intelligence has exploded. Graduates are employed before they finish their education and receive millions of salaries. Analysts believe that 2020 will be an important year in terms of AI in the workplace and claim that artificial intelligence will create 2.3 million jobs worldwide that year.

 

The most important thing to remind here is that software and tools based on artificial intelligence reflect the culture, preferences and background of developers. Therefore, it is crucial for each country to build its own strong expertise in the field, both in research and education. An investment in artificial intelligence can only succeed if it is based on a general strengthening of the ICT subject. Here it is necessary to strengthen the competence and education at all levels, as well as to promote the interaction between theory and technology, and between research and application.

 

To be on the top of AI game, governments should aim to develop internationally strong research environments in the field. This must be done by building on and strengthening the existing research networks and the environments within artificial intelligence in their own country and helping to position these in European and international networks. It is important to link up with the strategies for artificial intelligence in Europe, and adapt to the EU’s strategies, compliances and framework conditions for research and development.

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In order for a strategy for artificial intelligence to succeed, it should put man in the center. It should aim for the entire population to be able to exploit the new tools the field brings in a reflective way where they are able to judge the weaknesses and strengths.

 

Artificial intelligence is not only important for innovation, growth and competitiveness, but for how we want to work and live in the future. Increasing the overall digital competence is also necessary in view of the ethical challenges associated with this development.

 

Education systems needs to be brought up to date to reflect that we now live in a world where problem-solving and creativity are becoming more important assets. Regurgitating knowledge is something that you can automate very easily, but with actual education system, isn’t preparing children for the modern workforce.

 

No need to repeat that for students, AI will inevitably impact their careers. The AI era is inevitably creating new job types, ranging from machine regulators to emotion engineers. McKinsey predicts that AI will replace up to 800 million jobs by 2030. That’s a drastic reshaping of the workforce — and one that universities should help students prepare for. Students interested in careers in AI can pursue a wide range of exciting new career possibilities focused on data science, machine learning or advanced statistics.

Solutions Related to Technologies in the IoT Field

Solutions Related to Technologies in the IoT Field

In our last blog-post we’ve discussed about the Challenges Related to Technologies in the IoT Field. As the challenges of IoT are numerous, their solutions should and must be developed and support to provide better services that are trusted by all parties such as users, companies, and so on. Some of the solutions include standard encryption technologies that comply with IoT. Since the devices are mobile, the encryption technologies that are going to be used must be faster and less energy consuming because energy consumption is another problem of IoT devices. Using authentication and authorization structures for controlling access level to view the data is also another solution that should be considered while designing IoT applications.

 

Some of the solutions put regarding the problems discussed, in our previous post, include:

 

Having Uniform Shared Standards/Structures:

 

The lack of uniform standards for the Internet of Things is a huge problem that IOT organizations are facing. Having uniform standards is helpful in a way that having a standard protocols or structures makes vendors to follow this structure and will not create a problem when there is a need to integrate the different parts developed by different organizations. For example, if hardware and sensor device designers, network service providers and application developers all follow some standard for IoT, it will greatly reduce the problem that will arise due to integration problem and compatibility issues.

 

Address privacy and security risks throughout the IoT device life cycle:

 
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Addressing IoT privacy and security challenges from start to end-of-life, including every change in maintenance ownership, can help prevent general vulnerabilities. Organizations must have a set of security guidelines, standards and best practices that all or their solutions must comply with. Strong privacy policy towards IoT on how to collect and use individual data in a transparent way to the user increases the trust of the user for the service, make him/her aware how it is used and how to control it. This means that the user should be made the center to decide on what personal information goes where and how it is used.

 

Using Anonymization: 

 

IoT devices are capable of capturing physiological measures, location and activity information, therefore sharing sensed data can lead to privacy implications. Data anonymization provides solution to this problem. Anonymization is a method of modifying personal data so that nothing is known about the individual. It does not only include de- identification by removing certain attributes but has to also be linkable because a large volume of data is being produced each time a device is connected. Methods such as K- anonymity can be used. K-anonymity is a key concept that is introduced by Latanya Sweeney, to address the risk of re-identification of anonymized data through linkage to other datasets.

 

Robust storage systems:

 

For many IoT applications, it has become critical for data to be screened and analyzed where it is generated. I.e. from sensors in a car, surveillance cameras, drones, personal devices, robots, gateways, etc. As the data produced from IoT devices is large volume data, it is needed to have fast and powerful storage mechanisms which can handle very large data even more than it is needed currently. The ability to deliver real-time analytics at the network’s edge can improve operational efficiencies, provide safer driving, create more secure environments, foresee upcoming maintenance, identify customer buying behaviors, and enable a world of opportunities.

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