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iDrive is trying something a little different in cloud backups: Backing up your entire Google Workspace or Microsoft 365 storage, for only $20 per year per computer.

Confused? Then lets, er, back up. IDrive is one of our most highly recommended cloud backup options, able to back up your PC to the cloud with either a free plan or paid options that go all the way to 20TB. Its basically one of the only good independent cloud storage/backup providers that isnt a major corporation like Google or Microsoft.

Due to be formally announced Thursday, IDrive will now offer unlimited cloud backup for both Google Workspace (Google Drive, Gmail, Calendar, and Contacts) and Office 365 (OneDrive, Exchange, SharePoint, and Teams), called Unlimited Cloud to Cloud Backup. What IDrive will do is back up all of your files in the Google or Microsoft cloud over to to IDrive as well. And if you pay for extra storage in either service, IDrive can accommodate all of those files.

Why do this? Its an additional layer of security for those who worry about cloud services going down and data being unable to accessed. It sounds a little far-fetched until you remember that Western Digitals cloud service was down for over a week. Thats why the rule of three exists: You should have your data stored in three places, just in case: a local copy and two backups. Thats what IDrive is offering.

IDrives Unlimited Cloud to Cloud Backup backs up data from the other clouds three times per day. It retains snapshots of previous versions, allowing you to restore your data from a given point in time and not just all of it at once. You can seek out and restore individual files and folders, too. IDrive considers this service to be an add-on, meaning that you can attach it to existing IDrive plans. (You can also buy Unlimited Cloud to Cloud Backup as a standalone service.)

IDrive seems to be pitching this as a solution for individuals, families or small businesses, since a demonstration video showed a backup of a Microsoft cloud with about twenty different users. The only catch, if there is one, is that IDrive charges the $20 annual fee (or roughly $1.66 per month) per computer for backing up one service, Google Drive or Microsoft Office 365.

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IDrive gets even better with unlimited backups of your Google ... - PCWorld

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Quantum computing will process massive amounts of information. Workloads could include diagnostic simulations and analysis at speeds far greater than existing computing. But, to be fully effective, quantum computing will need to access, analyse and store huge amounts of data.

There is an expectation that quantum computing will be the next step in the evolution of IT systems. Just as the multicore processor allowed computers to perform multiple tasks in parallel, quantum processors will be a leap forward in compute power and allow performance of complex tasks in a fraction of the time required now.

Quantum computers, as the name implies, use quantum mechanics the branch of physics concerned with atomic and subatomic particles to overcome the limitations of existing computer systems.

The principles of the superposition of states and quantum entanglement enable a different computation method from that used currently. A quantum computer can potentially store more states per unit of information called quantum bits, or qubits and operate with much more efficient algorithms at the numerical level.

Qubits are a two-state quantum-mechanical system. However, because of superposition, they can also be both of the two states 1 and 0 at the same time. In a classic computer system, a bit would have to be in one state or the other 1 or 0. Quantum mechanics allows a qubit to be in a coherent superposition of both states simultaneously, a property that is fundamental to quantum mechanics and therefore to quantum computing.

At the core of the quantum computers potential for achieving exponentially greater computational power lies the qubits capacity to exist in a state of superposition Martin Weides, Glasgow University

Ultimately, this will allow quantum computers to process complex tasks using large datasets far more quickly than a classic computer, especially in the realms of big data and pattern recognition. For example, quantum computers have potential applications in the pharmaceutical industry, to screen larger and more complex molecules than they were previously able to, and to map the complex interactions between a pharmaceutical product and its intended target.

At the core of the quantum computers potential for achieving exponentially greater computational power lies the qubits capacity to exist in a state of superposition, explains Martin Weides, professor of quantum technologies at Glasgow University. It gives you a statistical answer of likelihoods and then you repeat the calculation a number of times, and amplify that result. At the end, you get some outcome, but its not with 100% certainty.

One of the core challenges of quantum computers is that their storage systems are unsuitable for long-term storage due to quantum decoherence, the effect of which can build up over time. Decoherence occurs when quantum computing data is brought into existing data storage frameworks and causes qubits to lose their quantum status, resulting in corrupted data and data loss.

Quantum mechanical bits cant be stored for long times as they tend to decay and collapse after a while, says Weides. Depending on the technology used, they can collapse within seconds, but the best ones are in a minute. You dont really achieve 10 years of storage. Maybe in two decades we might get there, but its not required either.

Quantum computers will need data storage during computation, but that needs to be a quantum memory for storing super-positioned or entangled states, and storage durations are going to present a challenge.

So, its likely data storage for quantum computing will need to rely on conventional storage, such as in high-performance computing (HPC).

Considering the massive financial investment required for quantum computing, to introduce a limitation of cheap data storage elements as a cost-saving exercise would be counter-productive.

Given the data storage challenges and requirement to process large datasets, quantum computing is likely to be best accessed through the cloud. IBMs current quantum systems are cloud-connected, for example. Naturally, the effectiveness of cloud storage is dependent on network connectivity to the cloud.

Although quantum computing faces challenges in scalability and decoherence, its ability to perform multiple simultaneous operations in a fraction of the time it would take conventional processors means it is likely to become a powerful tool for analytics workloads.

Quantum computing and quantum storage are unlikely to replace existing compute and storage systems.

Using classical compute and storage infrastructure will remain the easiest and most economical solution for tackling everyday problems, especially those that involve small, simple, repeatable tasks.

That said, quantum computing promises to deliver incredible advances in fields that include materials science, climate research and pharmaceutical development. Organisations are already experimenting with quantum computing to develop lighter and more powerful batteries for electric cars, and to help create new medicines.

The limited storage capabilities associated with quantum computers means they will continue to be dependent on classical storage systems for data extraction and information output. However, these would have to be capable of handling large datasets. Some of todays high-end storage systems, especially those that are cloud-based, should be more than adequate for the task.

A quantum computer being so expensive would almost certainly be operated in a dedicated facility with lots of new hardware, including storage, concludes Weides.

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Quantum computing: What are the data storage challenges? - ComputerWeekly.com

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More and more organizations utilize cloud technology for applications, file storage, and more. However, if an attacker compromises a cloud environment, organizations may not know how to investigate those technologies, or may not even be logging the evidence that could allow the organization to identify what an attacker did.

This blog post describes a hypothetical scenario of a cloud platform compromise with multiple components that would require investigation. Each component is an example of a real intrusion tactic that Mandiant has investigated across various cloud platforms, sometimes with logs available and sometimes without logs available.

For each part of the compromise, we provide recommended logging configurations and investigation processes organized into cloud technology themes that group cloud services from Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure together:

After reading through this scenario, you should be able to:

While we review many concepts, there are some limitations to be aware of in the scope of this post:

The attacker gained access to the Cloud Email platform through a credential stuffing attack against a cloud administrator account. Once the attacker found a valid password, the attacker authenticated with those credentials and the Cloud Email platform asked them which type of multi-factor authentication (MFA) process they preferred. The attacker chose the push option, which sent an approval request to the legitimate user. The administrator user deals with push authentication requests throughout the day for various services and mistakenly accepted the authentication request, which provided initial access to the attacker.

Once the attacker identified the cloud administrator credentials and authenticated, they logged in to the Cloud Management Console to identify other applications that the user could access.

The attacker identified that the cloud administrator account had access to the Cloud Authentication Services application and authenticated to it. In the Cloud Authentication Services application, the attacker changed the privileges of the cloud administrator to the highest global administrator account privileges available and removed the multi-factor requirement.

While in the Cloud Management Console, the attacker identified that the organization uses a custom Cloud Application. The attacker accessed the Cloud Code Repository with the global administrator account and identified the Cloud Application source code hosted there. The attacker accessed the code and identified plain-text hard-coded credentials for an application service account.

While in the Cloud Authentication Services application, the attacker identified that the Administrator had access to the Cloud Logging platform. The attacker authenticated to the Cloud Logging platform and searched logs for keywords related to plain-text credentials. The attacker exported logs that contained those keywords, particularly database user credentials.

The attacker returned to the cloud Authentication Service application and performed reconnaissance on systems and users. The attacker exported all environment objects including systems and accounts.

Next, the attacker pivoted to the Cloud Virtual Machine infrastructure and created a templated virtual machine. The attacker assigned the virtual machine to the application service account previously identified in the application source code. The attacker configured the Cloud Networking rules to allow remote desktop protocol (RDP) access from the internet. The application service account did not require MFA for any authentication activity because of its intended use. The attacker logged on to the virtual machine through RDP from their command and control (C2) server.

While logged on to the newly created virtual machine, the attacker identified a database server based on the hostname SQLDB01. The attacker moved laterally from the virtual machine they created to the database server via RDP using the application service account.

The attacker connected to the database, which utilized a Cloud Database Service backend, using the database user credentials previously identified in logs and explored the data by enumerating the table schema and running select * queries.

While logged on to the attacker-created virtual machine, the attacker also performed internal reconnaissance to identify other systems of interest. The attacker scanned the network for other systems using custom port scanning utilities that searched for open SSH, RPD, and SMB ports.

The attacker identified a network-shared file server that hosted files on a Cloud File Storage solution. After enumerating files stored on the network share, the attacker copied files to their C2 system using a bulk network file transfer utility.

While accessing the file server, the attacker also decided to stage further backdoors in trojanized files that are likely to be opened by users.

While logged on to cloud email for the administrator account, the attacker browsed through the last several days of messages. The attacker looked at email folders named finance and hr and downloaded attachments from sent messages.

The attacker shared the uploaded trojanized backdoor file through the collaboration platforms file sharing service with 20 users.

Several users messaged the administrators account and asked questions about errors opening the new document they downloaded through the collaboration platform based on an automated file shared email link. The attacker replied to tell the users the document is legitimate.

Finally, in an attempt to delay detection, the attacker created a mailbox rule to automatically delete replies to the compromised file share email.

The aforementioned hypothetical scenario took place in a matter of several days, reflecting how quickly the threat actors moved in the real scenarios this one is based on. In these cases, information security teams commonly have only a few medium priority alerts fire that go unnoticed due to the abundance of alerts feeding from their tools.

In this scenario, suspicion started when several helpdesk team members realized they had separate reports of users who had suspicious files shared with them. The helpdesk team escalated to Information Security per their documented processes and the Incident Response (IR) team started an investigation into the cloud file sharing platform associated with the file sharing.

The IR team quickly realized that the default logging available with their lowest cost license subscription recorded many useful logs such as:

Unfortunately, the investigation could not answer the question did the attacker access any email messages or synchronize any mailboxes? due to the default logging levels. The IR team also realized they were lucky the incident was detected relatively quickly because the default license subscription only stored logs for 90 days with their Cloud Logging platform.

After a post-mortem review several months later, the organization realized the IR team only reviewed collaboration platform authentications and did not cross reference against domain authentication logs. This meant that the internal team never identified that the attacker compromised the cloud infrastructure platform and performed follow-on activities such as creating and accessing a VM, elevating to domain administrator privileges, and interacting with file servers. They focused only the collaboration platform because the initial incident identification occurred after the sharing of files on the Collaboration Cloud File Sharing platform. The investigation had to be reopened several months later when evidence had started to disappear from Cloud Logging sources.

As the scenario demonstrates, attackers have a wider surface area to persist and steal data because of the adoption of cloud infrastructure and collaboration platforms. The move to these cloud platforms brings useful functionality and security features, but configuring everything correctly can be overwhelming for a team that is new to the technology.

Not only are there many access, permission, and protection configurations to consider, but teams should also make sure that they would be able to fully investigate various attacks that could happen by storing the correct logs.

Understanding what technologies your organization uses and performing threat modeling is one way to make sure you have these logs and investigative processes set up should you need to investigate.

For details on how Mandiant can assist with your cloud security, please check out the following resources:

The following attack path diagram visualizes how the actor accessed a wide range of cloud platforms from outside a standard perimeter in this scenario. The actor also used cloud technologies to interact with systems in the non-cloud environment as well through connections and integrations.

The following checklist is designed to be copied or printed for your cloud infrastructure logging review efforts. The provided logs are example categories of commonly utilized event logs for forensic investigations.

Reference Number

Technology

Log Type

1.1.1

Cloud Virtual Machines

Configure system event logs to follow standard endpoint logging policies for authentication, user activity, and privileged account use.

1.1.2

Cloud Virtual Machines

Log virtual machine management actions such as Start, pause, backup, snapshot, create, delete, and command executions etc.

1.1.3

Cloud Virtual Machines

Forward system logs to a log management platform or SEIM as part of standard polices and processes.

1.2.1

Applications or Functions

Log web server access to application including source IP address, protocol used, request parameters, response status, user agent, referrer, and response size. Ensure that source IP address is not overwritten by proxy or load balancer technology.

1.2.2

Cloud Applications, Containers, and Functions

Log creation, modification, and access to application code.

1.2.3

Cloud Applications, Containers, and Functions

Record successful and failed authentication activity including source IP address.

1.2.4

Cloud Applications, Containers, and Functions

Log application user activity including user account, information viewed, actions performed, and sensitive data accessed.

1.2.5

Cloud Applications, Containers, and Functions

Forward system logs to a log management platform or SEIM as part of standard polices and processes.

1.3.1

Cloud Database Services

Log database user authentication and source network address.

1.3.2

Cloud Database Services

Log data access including source network address and user.

1.3.3

Cloud Database Services

Log data modification and deletion including source network address and user.

1.3.4

Cloud Database Services

Forward system logs to a log management platform or SEIM as part of standard polices and processes.

1.3.5

Cloud Database Services

Log errors and long running queries, which could be indicative of data transfer or reconnaissance.

1.4.1

Cloud File Storage

Log user authentication.

1.4.2

Cloud File Storage

Log file creation, modification, upload, and deletion events with user account, IP address, and timestamp.

1.4.3

Cloud File Storage

Log file download events with user account, source IP address, and timestamp

1.4.4

Cloud File Storage

Log location, folder, and file permission changes.

1.4.5

Cloud File Storage

Log API access to file storage locations, folders, and files.

1.4.6

Cloud File Storage

Log file and directory listing metadata view.

1.4.7

Cloud File Storage

Turn on alerts for suspicious activity, including malware and mass downloads, if available.

1.5.1

Cloud Authentication Services

Log user authentication with timestamp, username, and source IP address.

1.5.2

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Cloudy with a Chance of Bad Logs: Cloud Platform Log ... - Mandiant

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Cloud storage is an important element of modern computing, allowing businesses to store and access data quickly and securely.

The costs of using a cloud storage service can be expensive. With more and more sectors relying on the cloud for data storage and transfer, it is no surprise that many seek a solution for the rising, sky high costs of cloud service providers. So, in this article, we'll discuss why your cloud costs may be reaching high levels, as well as ways to monitor and potentially reduce your cloud spending.

First and foremost, it is important to understand the different types of cloud storage services, and the associated costs. Cloud storage services can be broken down into three primary categories: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Each of these has its own set of associated costs, ranging from setup fees to monthly usage fees. Plus you may also incur additional fees as you begin using the service, such as support fees for when you need the advice of expert cloud engineers.

What are you paying for? - Depending on the particular cloud storage service, you may be paying for different elements. In addition to the fees outlined above, you could also be charged for data transfer bandwidth, or usage of applications hosted from the cloud. You may also have to pay extra for additional storage capacity or specific features and services that are not included in a basic subscription package.

One reason your cloud costs may be high is because of inefficient use or excessive storage. If you are currently storing large amounts of data that isn't being used, this can significantly drive up your costs. Its important to periodically review the data stored in your cloud and delete any unnecessary files or folders.

While it may be easy to turn to the cost of the provider, what is also useful is reviewing what you are paying for and deciding whether this is necessary for your organization. Different providers may offer varying levels of storage, features, or services that could be more cost-effective for your organization. Before signing up to access cloud services from your chosen provider, be sure to compare different providers and packages. You may find that certain providers offer better packages on a month-to-month basis.

It sounds simple to suggest simply reviewing your payments and your usage to ensure that you are truly paying for what you need from your cloud service provider. However, you may be wondering how to do this as your usage and requirements often fluctuate.

One of the best ways to manage and optimize your cloud costs is to work with cloud cost optimization tools. These tools provide daily, real-time monitoring of your cloud usage and can produce reports and analyses of your spend.

For large tech firms this is incredibly useful as cloud costs can often exceed thousands of dollars per month.

Not only are these tools automated, but they are incredibly efficient and do not require any additional software engineering work. With other features such as autoscaling and security insights, your engineers can stay on top of your organizations cloud usage without lifting a finger.

Cost optimization tools work by analyzing your cloud system for any inefficiencies or waste. They can identify areas where you may have over-provisioned resources, unused services, or misconfigured settings that are driving up costs unnecessarily. Additionally, these tools provide cost forecasts and recommendations on how to reduce your costs without compromising performance or security. By implementing a cost optimization tool into your cloud strategy, you will benefit from accurate reporting, and monitoring that will not only help you keep your cloud costs low but offer a wide range of other benefits to your IT team.

Cloud storage is an essential part of modern computing, but it comes with the potential for sky high costs. By understanding the different types of cloud storage and associated costs, you can take steps to monitor and reduce your spending. Furthermore, cost optimization tools can help automate this process and provide insights into how you are using your cloud services. Not only offering automated analysis of your cloud spending but providing real-time, continuous monitoring, optimizing your usage.

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Are Your Cloud Costs Sky High? - BBN Times

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Curtiss-WrightsDefense Solutions division, a developer and supplier of advanced Modular Open Systems Approach (MOSA)communications solutions for the U.S. Department of Defense (DoD), has collaborated with Nutanix to certify theNutanix Cloud Platform (NCP) solutionon thePacStar Modular Data Center (MDC), Curtiss-Wrights COTS-based, modular, tactical, and expeditionary rugged data center. The use of these interoperability tested technologies creates a combined solution that is capable of hosting cloud/storage, AI, and analytics applications. It enables warfighters to deploy data center-class computing and storage at the edge of tactical networks and rapidly set up a secure communications system in the field within hours instead of days. With support for the Nutanix Cloud Platform, a PacStar MDC-NR system can cluster together multiple PacStar servers, enabling shared compute and storage resources to run virtual machines (VM) and hypervisor containers.

Nutanix offers powerful tools for hybrid-cloud infrastructure and the robust data protection required for tactical operational environments, said Dominic Perez, CTO, Curtiss-Wright Defense Solutions division. When combined with the PacStar Modular Data Center, Nutanix Cloud Platform creates a powerful, transportable data center for the warfighter. We are excited to collaborate with Nutanix to host their powerful NutanixCloud Platform on our industry-leading PacStar MDC at the tactical edge of the battlefield.

We are proud to partner with Curtiss-Wright to provide a rugged, integrated solution to support in-theatre communications, CSfC, C5ISR/EW and other mission-critical applications and data vital to mission success, said Chip George, Vice President, Public Sector at Nutanix. Like the PacStar MDC, Nutanix software is hardened and secure upon delivery , reducing the burden of IT administrators, so that they can focus on the mission at hand. Especially for austere environments, the simplicity and ease of use of our software means that warfighters can easily deploy and manage this system without needing specialised technical training.

ThisCurtiss-Wright/Nutanix solutionprovides a common cloud platform and user experience, whether at the tactical edge or the HQ datacenter. Ideal for JADC2 enablement, the PacStar MDC-NR brings the Nutanix hybrid-cloud model to the tactical edge of the battlefield to integrate with leading cloud providers, such as Amazon Web Services Inc., Google Support Services LLC, Microsoft Corporation, and Oracle, all of which were recently selected by the Department of Defense (DoD) to support itsJoint Warfighting Cloud Capability (JWCC). Nutanix is the only HCI-provider included on the Department of Defense Information Network Approved Products List (DoDIN APL), having passed DISAs rigorous security and interoperability testing.

PacStar MDC-NR meets size, weight and power (SWaP) requirements unmatched by other COTS appliances of its type, which is ideal for defence, education, energy, first responder, and healthcare organisations. It brings NCP to the tactical edge, enabling customers to forward deploy/replicate cloud services and provide edge access to enterprise cloud systems. PacStar MDC-NR enables users to leverage the power of cloud computing in the battlefield to support applications such as video storage and analytics, intelligence analytics, and cybersecurity. PacStar MDC-NR can be used to host and store enterprise or tactical applications, and it delivers the high-performance compute power (Intel Xeon-D processing in 8-core, 12-core, and 16-core variants) demanded by AI and ML applications.

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Curtiss-Wright unveils rugged, full-stack hybrid cloud solution for ... - Asia Pacific Defence Reporter

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