Hertha  Walsh

Hertha Walsh

1604316180

Responsible AI/ML Alleviates Technological Risks and Security Concerns

Artificial Intelligence (AI) and Machine Learning (ML) is transforming industries and solving important and real-world challenges at a scale. The technology is maturing rapidly with seemingly limitless applications. These vast openings carry with it a deep responsibility to build AI that works for everyone.

AI applications have demonstrated its ability to automate daily works while also augmenting human capacity with new insight. However, with great power comes great responsibility. The fear of workforce displacement, loss of privacypotential biases in decision making and lack of control over automated systems and robots are some of the menacing possibilities. Artificial intelligence technologies in the commercial and public sector like autonomous cars, chatbots take over the tough human labor process by packing and endlessly answering human queries. However, the downside is that an autonomous car could cause an accident and a chatbot might learn to use offensive languages. These possible incidents have stoked fears of a ‘job apocalypse’ that concerns over inclusion, diversity, privacy and security.

As the usage of AI and ML increases, technology is becoming more pervasive. Technology is taking part in an increasing number of decisions like benefit payments, mortgage approvals, and medical diagnosis. When AI becomes a part of every working system, transparency and visibility disappears. One of the major threats that AI might imply is reinforcing existing human biases. These biases are unidentified and come about due to a lack of diverse perspective when developing and training the system.

In addressing all these issues and furthermore, Responsible AI/ML offers a way for everyone to adopt a ‘people first’ approach that is fair, accountable, honest, transparent and human-centric.

#artificial intelligence #latest news

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Responsible AI/ML Alleviates Technological Risks and Security Concerns
Wilford  Pagac

Wilford Pagac

1596789120

Best Custom Web & Mobile App Development Company

Everything around us has become smart, like smart infrastructures, smart cities, autonomous vehicles, to name a few. The innovation of smart devices makes it possible to achieve these heights in science and technology. But, data is vulnerable, there is a risk of attack by cybercriminals. To get started, let’s know about IoT devices.

What are IoT devices?

The Internet Of Things(IoT) is a system that interrelates computer devices like sensors, software, and actuators, digital machines, etc. They are linked together with particular objects that work through the internet and transfer data over devices without humans interference.

Famous examples are Amazon Alexa, Apple SIRI, Interconnected baby monitors, video doorbells, and smart thermostats.

How could your IoT devices be vulnerable?

When technologies grow and evolve, risks are also on the high stakes. Ransomware attacks are on the continuous increase; securing data has become the top priority.

When you think your smart home won’t fudge a thing against cybercriminals, you should also know that they are vulnerable. When cybercriminals access our smart voice speakers like Amazon Alexa or Apple Siri, it becomes easy for them to steal your data.

Cybersecurity report 2020 says popular hacking forums expose 770 million email addresses and 21 million unique passwords, 620 million accounts have been compromised from 16 hacked websites.

The attacks are likely to increase every year. To help you secure your data of IoT devices, here are some best tips you can implement.

Tips to secure your IoT devices

1. Change Default Router Name

Your router has the default name of make and model. When we stick with the manufacturer name, attackers can quickly identify our make and model. So give the router name different from your addresses, without giving away personal information.

2. Know your connected network and connected devices

If your devices are connected to the internet, these connections are vulnerable to cyber attacks when your devices don’t have the proper security. Almost every web interface is equipped with multiple devices, so it’s hard to track the device. But, it’s crucial to stay aware of them.

3. Change default usernames and passwords

When we use the default usernames and passwords, it is attackable. Because the cybercriminals possibly know the default passwords come with IoT devices. So use strong passwords to access our IoT devices.

4. Manage strong, Unique passwords for your IoT devices and accounts

Use strong or unique passwords that are easily assumed, such as ‘123456’ or ‘password1234’ to protect your accounts. Give strong and complex passwords formed by combinations of alphabets, numeric, and not easily bypassed symbols.

Also, change passwords for multiple accounts and change them regularly to avoid attacks. We can also set several attempts to wrong passwords to set locking the account to safeguard from the hackers.

5. Do not use Public WI-FI Networks

Are you try to keep an eye on your IoT devices through your mobile devices in different locations. I recommend you not to use the public WI-FI network to access them. Because they are easily accessible through for everyone, you are still in a hurry to access, use VPN that gives them protection against cyber-attacks, giving them privacy and security features, for example, using Express VPN.

6. Establish firewalls to discover the vulnerabilities

There are software and firewalls like intrusion detection system/intrusion prevention system in the market. This will be useful to screen and analyze the wire traffic of a network. You can identify the security weakness by the firewall scanners within the network structure. Use these firewalls to get rid of unwanted security issues and vulnerabilities.

7. Reconfigure your device settings

Every smart device comes with the insecure default settings, and sometimes we are not able to change these default settings configurations. These conditions need to be assessed and need to reconfigure the default settings.

8. Authenticate the IoT applications

Nowadays, every smart app offers authentication to secure the accounts. There are many types of authentication methods like single-factor authentication, two-step authentication, and multi-factor authentication. Use any one of these to send a one time password (OTP) to verify the user who logs in the smart device to keep our accounts from falling into the wrong hands.

9. Update the device software up to date

Every smart device manufacturer releases updates to fix bugs in their software. These security patches help us to improve our protection of the device. Also, update the software on the smartphone, which we are used to monitoring the IoT devices to avoid vulnerabilities.

10. Track the smartphones and keep them safe

When we connect the smart home to the smartphone and control them via smartphone, you need to keep them safe. If you miss the phone almost, every personal information is at risk to the cybercriminals. But sometimes it happens by accident, makes sure that you can clear all the data remotely.

However, securing smart devices is essential in the world of data. There are still cybercriminals bypassing the securities. So make sure to do the safety measures to avoid our accounts falling out into the wrong hands. I hope these steps will help you all to secure your IoT devices.

If you have any, feel free to share them in the comments! I’d love to know them.

Are you looking for more? Subscribe to weekly newsletters that can help your stay updated IoT application developments.

#iot #enterprise iot security #how iot can be used to enhance security #how to improve iot security #how to protect iot devices from hackers #how to secure iot devices #iot security #iot security devices #iot security offerings #iot security technologies iot security plus #iot vulnerable devices #risk based iot security program

Hertha  Walsh

Hertha Walsh

1602709200

Learning AI/ML: The Hard Way

The Wave and the Curve

Data science, Artificial Intelligence (AI), and Machine Learning (ML), since last five to six years these phrases have made their places in Gartner’s hype cycle curve. Gradually they have crossed the peak and moving toward the plateau. The curve also has few related terms such as Deep Neural Network, Cognitive AutoML etc. This shows that, there is an emerging technology trend around AI/ML which is going to prevail over the software industry during the coming years. Few of their predecessors such as Business Intelligence, Data Mining and Data Warehousing were there even before these years.

Finding the Crystal Ball in the Jungle

Prediction and forecasting being my favorite topics, I started finding a way to get into this world of data and algorithms back in early 2019. Another driving force for me to learn AI/ML was my fascination on neural networks that was haunting me since I started learning about computer science. I collected few books, learned some python skills to dive into the crystal ball.

While I was going through the online articles, videos and books, I discovered lots of readily available tools, libraries and APIs for AI/ML. It was like someone who is trying to learn cycling and given a car to drive. Due to my interest in neural networks, I got attracted to most the most interesting sub-set of AI/ML, Deep Learning, which deals with deep neural networks. I couldn’t stop myself from directly jumping into Google Tensorflow (a free Google ML tool) and got overwhelmed by a huge collection of its APIs. I could follow the documentation, write code and even made it work. But there was a problem, I was unable understand why I am doing what I am doing. I was completely drowning with the terms like bios, variance, parameters, feature selection, feature scaling, drop out etc. That’s when I took a break, rewind and learn about the internals of AI/ML rather than just using the APIs and Libs blindly. So, I took the hard way.

On one side, I was allured by the readily available smart AI/ML tools and on the other side, my fascination on neural networks was attracting me to learn it from scratch. Meanwhile, I have spent around a month or two just looking for a path to enter the subject. A huge pool of internet resources made me thoroughly confused in identifying the doorway to the heart of puzzle. I realized, why it is a hard nut for people to learn. Janakiram MSV pointed out the reasons correctly in his article.

However, some were very useful, such as an Introduction to Machine Learning by Prof. Grimson from MIT OpenCourseWare. Though its little long but helpful.

#machine learning #ai #artificial intelligence (ai) #ml #ai guide #ai roadmap

Otho  Hagenes

Otho Hagenes

1619511840

Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution

Wilford  Pagac

Wilford Pagac

1596796680

OWASP Top 10 API Security - DZone Security

I am sure that almost all of you would be aware about OWASP. But, just for the context let me just brief about the same.

OWASP is an international non-profit organization that is dedicated to web application security. It is a completely opensource and community driven effort to share articles, methodologies, documentation, tools, and technologies in the field of web application security.

When we talk about API, we are almost every time talking about REST and OWASP has a dedicated project to API security. As this series of articles are focused towards the API security, we shall not be going in details of web application security. You can use the provided links to find more about these. Let us spend some time on the background, before we dive deep in to API security project.

Background

OWASP’s most widely acknowledged project is OWASP top 10. This is the list of security risks compiled by the security experts from across the world. This report is continuously updated, outlining the concerns of web application security, and specially focuses on the Top 10 of the most critical risks. According to OWASP, this report is an “The OWASP Top 10 is a standard awareness document for developers and web application security. It represents a broad consensus about the most critical security risks to web applications.” They recommend that all companies incorporate the report into their processes in order to minimize and/or mitigate security risks. The latest version was published in 2017 and below is the list.

  1. Injection
  2. Broken Authentication
  3. Sensitive Data Exposure
  4. XML Eternal Entities (or XXE)
  5. Broken Access Control
  6. Security Misconfiguration
  7. Cross-Site Scripting (or XSS)
  8. Insecure Deserialization
  9. Using Components With known vulenerabilities
  10. Insufficient Logging And Monitoring

How API Security Is Different from Web Application Security

Although API’s have many similarities with web applications, but both are fundamentally different in nature.

In web applications, all the processing is done on the servers and the resulting web page is sent back to web-browser for rendering. Because of this nature, they have limited entry point and attack surface which are resulting web pages. This can easily be protected by putting up and web-application firewall (WAF) in front of the application server.WAF

In most of the modern application UI itself uses API’s to send and receive data from backend servers and provide the functionality of the application. It is the responsibility of the clients to do the rendering and convert the responses to a web page.

API GET and raw data

Also, with the rise of microservices architecture individual components become APIs, and it becomes a different world altogether, where UI clients could interact with hundreds of services via API calls. This significantly increases the attack surface. Now all those API’s become the entry point and attack surface.

These entry points can’t be guarded using the WAF solutions as they cannot differentiate between the legitimate and malicious API calls.

Why A Separate Project on API security?

Since its first release in 2003 OWASP top 10 projects has been the most useful resource in terms of web application security risks and to suggest the ways to mitigate these issues.

These days almost all the application development like banking, retail, transportation, smart devices, are done with the APIs.

APIs are critical to modern mobile and SaaS application. By nature, the API’s expose business logic and data, often these data are sensitive in nature, for example Personally Identifiable Information (PII). Because of this API’s are increasingly being targeted by attackers.

As API’s are changing how we design and develop our application, this is also changing the way we think about our security. A new approach in needed in terms of security risks. To cater to this need, OWASP decided to come up with another version of Top 10 dedicated to API security which is named “OWASP API Security Project”. The first report was released on 26 December 2019.

Below is the OWASP Top 10 API security risks and their brief description as provided by the official report.

API1:2019 Broken Object Level Authorization

APIs tend to expose endpoints that handle object identifiers, creating a wide attack surface Level Access Control issue. Object level authorization checks should be considered in every function that accesses a data source using an input from the user.

API2:2019 Broken User Authentication

Authentication mechanisms are often implemented incorrectly, allowing attackers to compromise authentication tokens or to exploit implementation flaws to assume other user’s identities temporarily or permanently. Compromising system’s ability to identify the client/user, compromises API security overall.

#security #api security #owasp top 10 #api penetration testing #api security risks #owasp top 10 web security risk

Shradha Singh

1604928723

Building A Strong AI Team for Your Organization

AI technologies are becoming standard across industries. Organizations are exploring select opportunities and implementing a few use cases while becoming an AI-fueled organization. Though this is a welcoming initiative for AI implementation, an organization must rethink the way they are implementing technology in their business so that they can be called the market makers.

It is critical to consider AI tools, machine learning techniques, and other cognitive tools to deploy systematically across every core process. Implementing AI will become a strategy and fundamental expectation in due course. At this juncture, the organizations must have a strong AI team that can drive new offerings and business models.

Let us understand the AI team in detail here for the survival of the business.

BUILDING AN AI TEAM FOR YOUR ORGANIZATION
The AI-fueled journey presents a straightforward proposition of keeping AI, ML, and other cognitive technologies at the center of business. AI helps to improve existing products, optimize internal and external operations, make better decisions, and give space for employees to become more creative.

To achieve this quantum leap, it is necessary to possess a strong AI team. It is critical to approach AI with a process-level view so that you can deploy them in a way that it significantly brings successful changes and improve customers’ experiences. Though you may start small, your team must have these AI professionals to be successful.

Here isa list of must-have professionals in your AI team.

C-Suite Executive
The organizations that have successfully implemented AI have strong leadership support. A C-suite professional who can take an active role in aligning and ensuring AI projects with the company’s business strategy is of utmost importance. The C-suite professional is responsible for partnering with solutions providers, obtain funding, and taking the right initiative in the AI journey. This person acts as the real bridge between technology and business by driving AI pilot projects that deliver a measurable return on investment (ROI).

Artificial Intelligence Researcher (AI Researcher)
30 percent of IT executives find AI researchers as their top priorities than any other role, Deloitte’s survey reports. The research and development (R&D) department in an enterprise is not a luxury, but a necessity.

For instance, AppTek had to invest in research to transform and keep up their specialization in human language technology.

#ai technologies #artificial intelligence #ai researchers #ai #ml