Skip to main content
  1. Contributor Content

Enhancing security, anonymity, and performance with residential proxies

By , Content Contributor
Proxy cgi logo
Proxy / Proxy

With the rise of e-commerce and digital marketing, companies are seeing the rise of malicious actors who both track their employees’ internet usage and create data breaches in their systems, gaining unauthorized access to proprietary files and data. A report from the Identity Theft Resource Center (ITRC) uncovered more than 3,000 data breaches reported in 2023 alone, and the number of data breaches has been rising annually; in 2024, corporate cyberattacks were up 50% compared to the previous year. This presents multiple risks to businesses and their employees, including identity theft, disrupted operations, exposure of confidential data and plans, and financial losses. According to ITRC, the average cost of a data breach is $4.45 million, up from $3.86 million in 2021, though some experts hope the cost may begin to fall. 

To secure browsing, protect online identities, and gather competitive intelligence, companies need sophisticated and reliable tools. That is what has made Residential Proxies popular recently. Unlike data center proxies that rely on company servers, residential proxies are anonymous IP addresses assigned by Internet Service Providers (ISP) not to the server but to individual devices. This makes residential proxies difficult to detect and block, allowing users to browse the web seamlessly and anonymously and access geo-restricted content for competitive research.

Recommended Videos

Proactively Selecting a Proxy

However, proxy servers are a preventative measure, not a cleanup measure after a data breach has already occurred. Companies that want to add that layer to their security infrastructure need to act ahead of time.

Related: 
Best new movies to stream on Netflix, Hulu, Prime Video, Max (HBO), and more

A proxy server adds an additional barrier between the company’s internal servers and external traffic. Hackers may succeed in breaching the proxy server, but they are unlikely to reach the company’s own server. While proxy servers alone are not a data security cure-all, they can be one effective measure in decreasing the business’s vulnerability. Here are four ways that residential proxies can help companies.

1. Increased Anonymity and Security

Residential proxies mask users’ real IP addresses, making their activities on the Internet extremely difficult to trace. This can be especially important for businesses that are conducting sensitive operations in market research and competitor analysis – as well as for firms handling financial or legal information.

Residential proxies can help a company keep their plans confidential. Masked IPs allow market research teams to conduct more thorough research and gather competitive intelligence without accidentally exposing their online searches and activities.

2. Reliable Web Scraping and Data Collection

Not only can proxies protect against accidental exposure during web scraping and data mining, but they can also help market researchers bypass anti-bot measures, allowing data scraping to proceed uninterrupted and often undetected.

3. Unrestricted Access to Geo-Locked Content

As more online platforms enforce location-based restrictions, residential proxies can allow companies to access region-specific content, giving employees the opportunity to view more accurate and comprehensive data on regional market trends and competitive pricing.

4. Social Media and Ad Verification

Finally, residential proxies can help marketers manage multiple anonymous social media accounts, making it possible to verify ad placements. This can protect companies from losing limited marketing dollars to bad actors in the crowded social media advertising space, some of whom may report impressions and ad clicks fraudulently or inaccurately.

Choosing the Right Residential Proxy Service

Not all residential proxies are created equal, and in selecting a proxy provider, businesses need to consider factors like the size of their IP pool, what regions and locations they provide coverage for, what speed they promise, and their security measures. A higher quality provider will be one that delivers stable connections with minimal downtime and can provide seamless integration for the residential proxy service for varied use cases.

Whether driven to select a residential proxy by the need for widespread data mining or simply the need for more secure browsing, companies can use this newer alternative to proxy servers to maintain their employees’ anonymity, protect their confidential plans, access geo-restricted sites, and conduct more accurate and reliable market research.

Digital Trends partners with external contributors. All contributor content is reviewed by the Digital Trends editorial staff.
Chris Gallagher
Chris Gallagher
Chris Gallagher is a New York native with a business degree from Sacred Heart University, now thriving as a professional…
Complexity’s adversary: how Ishaan Agarwal is building tools that disappear
photo of Ishaan Agarwal

In an industry obsessed with feature bloat, Ishaan Agarwal stands apart. While most product managers race to add capabilities, Agarwal has built his career on a counterintuitive principle: reduction.

"The best products I've worked on are the ones that rigorously removed obstacles rather than adding capabilities," says Agarwal, whose product management career spans Microsoft, Brex, and now Square.
The Foundation for Thinking Differently
This counterintuitive approach didn't materialize from thin air. Agarwal's unusual educational path — completing both bachelor's and master's degrees in computer science at Brown University in just four years — reflects an early talent for efficiency. But the technical foundation alone doesn't explain his product philosophy.

Read more
“AI Alone Cannot Save Disjointed Data Systems,” says Coginiti Founder

Artificial Intelligence has grabbed the attention of every business around the globe, driven by visions of automation and smarter decision-making. This has fueled a race to integrate AI into their operations. And yet, as per Gartner’s latest update, at least 30% of AI initiatives will be abandoned this year.
Why? “It’s not because AI doesn’t work,” states Rick Hall, founder of Coginiti. “It’s because most companies haven’t done the foundational work. They expect AI to clean up their mess, but it can’t. Companies need to clean up their own data before inviting AI in.”
 
Hall believes AI is still in the early phases of a decade-long transformation, one that will redefine nearly every business operation. But for that transformation to succeed, organizations must first tackle three persistent problems: poor alignment to business goals, bad data, and failed integration.
 
Companies often rush to implement AI without understanding how it will actually improve their business. “They start with the technology, not the outcome,” Hall states. “They can’t articulate what success looks like.” Without a clear hypothesis of what AI will do and the value it will drive, the initiative flounders.
 
Messy, redundant, and poorly labeled data is one of the most common obstacles to AI success. One of Coginiti’s clients, for example, had been using a cloud-based sales system for years. They wanted to deploy AI to optimize their sales pipeline. But their sales opportunity record had ballooned to 250 columns with four different fields just for purchase orders.
“Over time, processes change, people add fields, create nicknames, and now AI has no idea which one to use,” Hall explains. “You’re asking an algorithm to make sense of something even your sales team doesn’t fully understand.” Without clearly named, clean, and integrated data, no AI can deliver value.

Even when an AI model is successfully trained in a pilot program, many businesses struggle to scale it. That’s because they haven’t built clear bridges between their test environments and real-world operations. “You might have something that works in isolation, but integrating it into your existing systems, your workflows, your infrastructure, that’s where everything breaks down,” Hall says.
 
To solve these problems, Coginiti helps organizations build a digital twin, a virtual representation of how the business actually works. A digital twin isn’t just a model or a dashboard; it’s a semantic representation that maps your business processes, data, and systems in a structured, meaningful way.
 
“When you have a digital twin integrated into your system,” Hall says, “you can simulate change. You can say: ‘If we improve this process, we’ll see this benefit.’ It aligns your AI efforts to business value from the beginning.”
 
The digital twin acts as a translator between your messy, physical reality and a logical business model that AI can understand. It defines your data layer clearly and exposes it to AI tools in a way that is consistent and scalable.
 
A digital twin starts with understanding how your business actually runs. What are the key value chains? What are the metrics for improvement? This means data will be well-defined, consistently named, and logically organized. “The semantic model is the heart of a digital twin,” Hall says. “It’s what allows AI to interface with your business meaningfully.”
 
A true digital twin links clean, logical models to real-world data across systems: CRMs, ERPs, call centers, data warehouses, and more. A digital twin further pulls from across departments and platforms, ensuring a single, unified source of truth. With the integration in place, businesses can use AI agents to model changes, test new processes, and develop rapid pilots that can easily be deployed in production.
 
Ultimately, AI is not a magic bullet. It’s a powerful tool, but only as powerful as the foundation it rests on. “Think of AI as a new room in your house. If the blueprint is vague and the bricks are cracked, even the best architect can’t build a stable structure,” Hall compares. “The companies that invest in doing this the right way today will be tomorrow’s leaders.” Coginiti can help you with the transformation. 

Read more
Shaping Enterprise resilience through cybersecurity and software quality

The lines between software quality and cybersecurity are starting to blur in the online world. Companies can’t afford to think of them as separate issues anymore. A bug in the code can just as easily become an open door for hackers, and security gaps often trace back to how the software was built. According to Cybersecurity Ventures, cybercrime is expected to cost the world $10.5 trillion annually by 2025, highlighting the significant risks for companies, governments, and national defense systems. Cybersecurity today involves protecting private data, safeguarding critical infrastructure, maintaining public trust, and supporting the stability of economies. Gopinath Kathiresan is working to bridge these critical areas. As a seasoned quality engineering expert, he’s helping businesses build safer, stronger systems.

The Business Imperative: Quality and Security as Two Sides of the Same Coin
With more than 15 years working at the forefront of software quality and automation, Kathiresan understands that getting software ‘right’ is not just about avoiding bugs; it’s also about maintaining trust. Currently, each mistake incurs hundreds of thousands of dollars in the digital economy. Customers do not just want perfection—they expect it. When something goes wrong, they will not just lose users; they will lose their reputation and earnings as well.

Read more