Why are we adopting this approach

We needed to migrate an entire EC2 instance from AWS to GCP, including all data and the application hosted on the AWS EC2 instance. To achieve this, we chose the "Migrate to Virtual Machines" option under the Compute Engine service in GCP. Other options are available that migrate the EC2 instance’s AMI, where additional data should be transferred is a significant challenge. 

The EC2 instance migration was accomplished successfully by using the method described below, which streamlined the entire GCP migration procedure.

A detailed, step-by-step explanation is documented below.

Pre-Requirements on AWS console

We created a user in the AWS console, generated an access key and secret key for the user, and assigned them Administrator permissions. These keys were used to migrate an EC2 instance to a GCP VM instance.

Below are our EC2 instances listed in the AWS console. We are migrating these instances to the GCP console.

In this EC2 instance, we have a static web application as shown in the screenshot below.

‍STEP: 01

Open the GCP console, navigate to Compute Engine, and go to the "Migrate to Virtual Machines" service.

Migrate to Virtual Machines

Using the "Virtual Machines" option under the Compute Engine service, we successfully migrated the EC2 instance.

STEP: 02

Add the source from which we need to migrate the EC2 instance, such as AWS or Azure. Here, we are migrating an EC2 instance from AWS to GCP.

Choose an AWS source.

To create the AWS source, please provide the necessary details as shown in the screenshot below.

Verify all the details and create the AWS source. Once an AWS source is created, all AWS EC2 instances from that source will be visible in our GCP console, as shown in the screenshot below.

Select the instance from the list above that should be migrated to a GCP VM instance.

‍STEP: 03

I have selected an AWS EC2 instance and want to migrate it to Google Cloud by clicking "Add VM Migration" and confirming, as shown below.

Navigate to VM migration and start the replication.

Migrating all the data from AWS to GCP, as shown in the screenshot, takes some time.

STEP: 04

Specify the configuration details for launching the VM instance in GCP, including the machine type, VPC, instance name, public and private IPs, disk types, and service account. Also, assign the appropriate license to the newly launched VM instance by clicking "Edit Target Details" and providing the necessary information.

Fill in the details as shown in the screenshots:

STEP: 05

I have created a new service account in my testing GCP project with the "Service Account User" role. This role is essential for launching a GCP VM instance, so we need to include this service account in the source target details, as shown in the screenshots above.

Finally, verify all the details and then click 'Save.' The target details will be updated successfully.

STEP: 06

Before proceeding to the final cut-off state, we will launch a test VM instance using the test clone and confirm the setup. This step ensures that all configurations are correct and all data is successfully migrated before moving to the final cut-off state.

Where the test clone takes place—using the replicated data and target details—to launch a first test VM instance in the GCP console.

Test process:

‍

STEP: 07

During the final cut-over stage of the migration process, only the original VM instance is launched in the GCP console, exactly mirroring the EC2 instance in the AWS console

After the cut-over stage, we successfully launched a VM instance, as shown in the screenshots below.

STEP: 08

After successfully connecting via RDP to the newly launched VM instance in the GCP console, we verified that all data migrated from the EC2 instance in the AWS console was present in the GCP VM instance.

For reference, please find the screenshot below.

STEP: 09

We have also verified that our application, which is a static webpage hosted on an EC2 instance in the AWS console, is working as expected on the GCP VM machine.

Therefore, we have successfully migrated an AWS EC2 instance from AWS Cloud to GCP Cloud

E-mail spoofing is a technique whereby the attacker forges the sender's address in such a way as to make the recipient believe it is coming from a trusted party. It could be a colleague in the office, a company, or even a financial institution. In this scenario, an attacker sends email headers in a manner such that the recipient would consider it to have come from a particular person, and the possibility of getting people to click on links they should not download attachments that will harm them or share with sensitive information becomes more probable.

Most of the current email systems lack a good feature that identifies forged sender addresses, and this explains why most phishing, spear-phishing, and business email compromise attacks rely on such a strategy.

For example, you might get an email that you are in both "To" and "From." Now, that doesn't mean someone has breached your email account. What they would do instead is pretend to be you or maybe another person you trust so that you open the email and may click on malicious links or release sensitive information.

How to Identify a Spoofed Email?

Sent Folder does not have an e-mail - When you send yourself an e-mail, it always is going to be in your Sent folder. And consequently, since spammers spoofed your address, you'd never see it there because he sent it from nowhere, but it would appear as if it was from your account.

‍NOTE: If you compose an email to yourself and delete it from your sent folder, then you will no longer see the email in your inbox also.

Check the Original Email - Most E-mail systems will show you the "original" or "raw" version of an e-mail. This shows all the technical details of how the e-mail is sent. Look for a possible sign such as suspicious From, Reply-To, Return-Path, or Received, fields that don't look just right, maybe an indicator of a spoofed e-mail.

Grammar and spelling mistakes - Always keep an eye out for homoglyphs (Example: Ankercloud as Amk3rc10ud) and grammatical errors that a legitimate sender would never make.

Preventive measures: protecting both yourself and your organization

• Implement the SPF, DKIM, and DMARC email security protocols as a layer of protection against spoofing which helps in verifying that an email was actually sent from the person that it says it is, if not then the email will go to spam/deleted immediately. 
• Use spam filters- Generally, most email services have spam filters. These can filter suspicious-looking emails even before they reach your inbox. To be on the safe side, assume that your spam filter is active.
• Be Cautious - Be wary of opening any uncalled-for emails, particularly when suspicious, or asking for information that could be confidential.

‍What to Do If You Fall Victim to Spoofing Attack

• Don’t panic and disconnect the device from the internet immediately, to make sure no further damage is done by the malicious programs downloaded.
• Report the IT team on what happened so they can decide if sensitive information has been put at risk and make all the necessary arrangements to ensure safety measures are taken about your account. 
• Change your passwords in case you think you got infected, change all the passwords right away from a different device, and implement/enforce 2FA for that added layer of security. 
• Keep an eye on your email account and other accounts online for suspicious activities such as unauthorized login attempts or suspicious activities through your accounts.

Conclusion 

Email spoofing is very hard to prevent, but definitely difficult to detect; if you are alert and think of some basic precautions, you should never fall for such a scam. So, always check suspicious emails and contact your IT/security team whenever in doubt, please ask for help.

In June 2023, the European Union took a significant step in regulating artificial intelligence with the introduction of the AI Act. This landmark legislation aims to create a legal framework for AI development and deployment across the EU, ensuring that AI technologies are used responsibly and ethically. For businesses leveraging AI, understanding and complying with the AI Act is crucial to avoid penalties and maintain consumer trust. This is where Ankercloud comes into play, offering solutions to help businesses navigate the complexities of the new law.

Understanding the AI Act

The AI Act classifies AI systems into three categories based on their potential risks:

1. Unacceptable Risk: AI applications deemed a threat to safety, livelihoods, and rights are banned. This includes systems for social scoring by governments and real-time biometric identification in public spaces.
2. High Risk: AI systems that impact critical areas such as healthcare, transport, and employment must meet strict requirements. This includes robust risk management, high-quality data, human oversight, and transparency.
3. Limited Risk: Applications with a minimal risk, like chatbots, must ensure transparency and inform users that they are interacting with AI.

For businesses, especially those operating in high-risk categories, the AI Act mandates a comprehensive approach to risk management, data governance, and compliance documentation.

Challenges for Businesses

The introduction of the AI Act presents several challenges for businesses:

• Compliance Costs: Adhering to the stringent requirements of the AI Act may involve significant costs, particularly for SMEs.
• Technical Expertise: Ensuring that AI systems meet the law's standards requires specialized knowledge in AI development and data governance.
• Documentation and Transparency: Businesses need to maintain detailed records of their AI systems' design, testing, and deployment processes.

How Ankercloud Can Help

Ankercloud offers a suite of services designed to help businesses comply with the new AI Act seamlessly and efficiently. Here’s how Ankercloud can assist:

1. Risk Assessment and Management:
   • Comprehensive Risk Analysis: Ankercloud provides support to assess the risks associated with AI systems, helping businesses identify potential issues early in the development process in line with the industry best practices.
   • Risk Mitigation Strategies: Through detailed analysis and expert guidance, Ankercloud helps implement robust risk mitigation strategies, ensuring compliance with the AI Act’s high-risk requirements.
2. Data Governance:
   • Quality Data Management: Ankercloud’s approach to data governance ensures that AI systems are trained on high-quality, non-biased data, meeting the AI Act’s standards.
     1. ISO/IEC 25024: This international standard outlines data quality measurement criteria like accuracy, completeness, consistency, and timeliness. Ankercloud's platform helps businesses assess these metrics to ensure their data meets regulatory expectations.
     2. Fairness and Bias Mitigation: According to the AI Act, data used for high-risk AI systems must be free from bias. Ankercloud incorporates AI fairness tools that detect and correct biased datasets, ensuring compliance with EU requirements for fairness, inclusivity, and non-discrimination.
     3. Traceability and Transparency: Ankercloud enables businesses to track and document the provenance of their data, ensuring compliance with the transparency demands of the AI Act. This feature helps maintain accountability and verifiability throughout the AI lifecycle.
   • Data Security and Privacy: Ensuring that personal data is protected and privacy is maintained is crucial. Ankercloud helps implement security measures and privacy protocols compliant with the AI Act.
     1. ISO/IEC 27001: This standard defines the requirements for a comprehensive Information Security Management System (ISMS). Ankercloud helps businesses implement and manage information security strategies to ensure sensitive data is protected.
     2. GDPR (General Data Protection Regulation): GDPR is the key regulation in the EU for protecting personal data. Ankercloud supports businesses in meeting GDPR requirements, including data minimization, obtaining consent for data use, and ensuring data subject rights are respected.
     3. ISO/IEC 27701: This extension to ISO 27001 provides guidelines for privacy and helps implement a Privacy Information Management System (PIMS). Ankercloud incorporates this standard to assist businesses in complying with privacy regulations.
     4. Encryption and Access Controls: Ankercloud implements technologies such as end-to-end encryption and multi-factor authentication to ensure data is protected during transmission and storage. This helps businesses meet the AI Act's security requirements. Ankercloud’s comprehensive security and privacy solutions help businesses minimize the risk of data breaches and ensure compliance with relevant security standards, which is critical for using AI in line with the AI Act.

3. Transparency and Documentation:
   • Documentation Support: Ankercloud assists in creating and maintaining comprehensive documentation of AI system development and deployment, essential for audits and regulatory reviews.
4. Human Oversight:
   • Human-in-the-Loop Solutions: Ankercloud helps integrate human oversight mechanisms into AI systems, ensuring that critical decisions are reviewed by humans, as required by the AI Act.
5. Training and Support:
   • Ongoing Support: With continuous support and 24/7 account management delivered by a dedicated Managed Services team, Ankercloud continuously ensures that businesses stay compliant with evolving regulations and industry standards over the long term.

Conclusion

The EU’s AI Act marks a pivotal moment in the regulation of artificial intelligence, emphasizing the importance of ethical and responsible AI use. For businesses, navigating this new legal landscape may seem daunting. However, with Ankercloud’s comprehensive suite of solutions, companies can confidently manage compliance, mitigate risks, and leverage AI’s full potential within the bounds of the law. Partnering with Ankercloud ensures that your business not only meets regulatory requirements but also sets a benchmark for responsible AI innovation.