Tag: Data Security

The Internet of Things (IoT) represents one of the most significant technological evolutions of our time. With the proliferation of connected devices, from home appliances to complex industrial machinery, IoT has seamlessly integrated into the fabric of our daily lives. This integration has not come without its challenges, particularly in terms of security.

As IoT devices become more ubiquitous, they also grow in complexity. The sensors, connected medical devices, and critical infrastructure systems we rely upon every day are now composed of countless components sourced from an increasing number of providers. This complexity is not just a matter of physical parts but extends deeply into the software that powers these devices.

Amidst this complexity lies a significant concern: data security. Many IoT devices manage data within corporate control environments, but this data is often sensitive and proprietary. The marketplace, unfortunately, is rife with misinformation and misunderstandings, leading to valid concerns about unauthorized access, data breaches, and privacy violations. These concerns are well-founded, as the potential risks include vulnerabilities in critical medical devices, connected vehicles, and key infrastructure systems, which could have significant impacts if exploited.

The Intricacies of IoT Device Software Supply Chains

Embedded devices, which form a substantial part of the IoT ecosystem, consist of intricate layers of third-party software. Unlike cloud or web software, these devices often include proprietary software from various hardware components, making the supply chain more complex and opaque. This complexity is compounded by the fact that these hardware components often come with less available public information than, for example, open-source projects on GitHub. This scenario demands a high level of software transparency, especially given the slower and less frequent update cycles in realms requiring device recertification.

The Critical Need for Software Transparency in IoT

Software transparency in IoT is not merely a best practice; it is a necessity. The complexity and opacity of embedded device supply chains make it nearly impossible to effectively assess and manage security risks without a clear understanding of the software components within these devices. This transparency becomes crucial in light of recent regulatory pushes focusing on IoT and embedded system security, such as the European Union Cyber Resilience Act (EU CRA) and the NIST Cyber Trust Mark.

The future of IoT security is a collaborative effort, one that requires manufacturers, software developers, and security experts to work together. It involves not only implementing robust security protocols but also embracing transparency at every stage of the development and deployment process. As we continue to invest in standards like SBOMs and VEX, and collaborate with industry leaders, we are paving the way for a future where IoT devices are not just functionally robust but also secure and transparent.

To Know More, Read Full Article @ https://ai-techpark.com/enhancing-iot-security-through-software-transparency/

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Safeguarding Business Assets

AI in Mental Health Diagnostics

Black Friday and Cyber Monday are excellent opportunities for customers to get hold of some great deals, while for retailers, it is an outstanding time to clear up their stocks. But, unfortunately, even cybercriminals utilize this time to execute scams and crimes that affect businesses.

According to global collective research in 2022, there is $41 billion in fraud damages reported from the e-commerce industry. However, it is anticipated that by the end of 2023, the loss will surpass $48 billion.

As cyber criminals initiate new routine scams around the time of these events, it is the right time for CISOs and other IT teams to step up their vigilance plan of action to counter such malicious attacks and protect their business as well as the interest of their valued customers.

With the help of this article, we will delve deep into some useful tips to create a secure online shopping experience.

Key Actions for Black Friday Cybersecurity

During such frenzied festive seasons, the CISOs and IT managers should be cautious as threat actors are on their toes to ruin businesses with their scams and deceiving tactics.

So, to prevent such incidents here are four essential key actions you can conduct:

Create a Robust Cybersecurity Plan

Planning a robust cybersecurity plan during events and festivals, like Black Friday or Cyber Monday can involve multiple approaches. It has been witnessed that cyber actors are ahead in the game by using tactics like:

Custom site designs for the event or early bird deals to fool customers into clicking on them and impersonating them as your customers.

It has been seen that customers are attracted to clickbait that forces your company to get their sensitive information, like credit or debit card details, addresses, mobile numbers, and many more.

Thus, chalking out the areas where monitoring is needed or what steps and protocols are needed to eliminate these incidents will save you valuable money and resources in turn giving your customers the retail therapy they deserve.

Implement Automated Data Security and Compliance

You need to ensure that your website or application follows all the rules and regulations in terms of data security and compliance.

Implement automated data security and compliance services that scan your network and notify you in real-time of any suspicious activity, which allows you to promptly act before any damage occurs.

Automated solution tools like Scrut, Vanta, Drata, and Tugboat Logic help employees monitor and report threats promptly.

The only standard approach to implement these tools would require adequate routine team training with appropriate knowledge transfer for personnel to operate these tools and defeat cyber criminals ahead of time!

To Know More, Read Full Article @ https://ai-techpark.com/ai-on-black-friday/ 

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Big Medical Data in Patient Engagement

Effective Machine Identity Management

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AI and AIOps have been transforming the future of the workplace and IT operations, which accelerates digital transformations. The AIOps stands out as it uses machine learning (ML) and big data tracking, such as root cause analysis, event correlations, and outlier detection. According to the survey, large organizations have been solely relying on AIOps to track their performance. Thus, it is an exciting time for implementing AIOps that can help software engineers, DevOps teams, and other IT professionals to serve quality software and improve the effectiveness of IT operations for their companies.

Adoption of AIOps

Most companies are in the early stages of adopting AIOps to analyze applications and machine learning to automate and improve their IT operations. AIOps have been adopted amongst diverse industries, and more enterprises are adopting it to digitally transform their businesses and simplify complex ecosystems with the help of interconnected apps, services, and devices. AIOps have the potential to tackle complexities that are often unnoticed by IT professionals or other departments in a company. Therefore, AIOps solutions enhance operational efficiency and prevent downtime, which makes work easier.

Numerous opportunities can change the way AIOps has been incorporated into the company. To do so, businesses and IT professionals should be aware of appropriate trends and best practices to embrace AIOps technologies. Let’s take a closer look at these topics:

Best Practices of AIOps

To get the most out of AIOps, DevOps engineers and other IT professionals can implement the following practices:

Suitable Data Management

DevOps engineers must be aware that ill-managed data often gives undesired output and affects decision-making. Thus, for a suitable outcome, you should ensure that the gathered data is properly sorted, clean, and classified for seamless data monitoring and browse data through a large database for your enterprise.

Right Data Security

The security of user data is essential for your company, as it is under the guidance of data protection regulation agencies that can impose fines if the data is misused. The DevOps and IT engineers can ensure that the data is properly safeguarded and used within their control to avoid data breaches.

Appropriate Use of Available AI APIs

AIOps’s main aim is to improve the productivity of IT operations with the help of artificial intelligence. Therefore, the IT teams should look for great AI-enabled APIs that improve the tasks they have to accomplish.

To Know More, Read Full Article @ https://ai-techpark.com/future-of-aiops/ 

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Importance of AI Ethics

AI and RPA in Hyper-automation

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In today’s rapidly evolving business landscape, the Banking, Financial Services, and Insurance (BFSI) sector is at the forefront of digital transformation. To succeed in this dynamic environment, industry leaders, executives, and decision-makers must not only recognize the challenges but also harness the opportunities presented by technology. This article is a comprehensive exploration of how Robotic Process Automation (RPA) and Artificial Intelligence (AI) provide strategic solutions to address these challenges, foster innovation, and drive growth within the BFSI sector.

Before delving into their applications, let’s establish a clear understanding of RPA and AI. RPA utilizes software robots to automate repetitive tasks, while AI leverages machine learning and data analytics to replicate human intelligence. In BFSI, these technologies have the potential to reshape the way business is conducted.

Navigating Contemporary Challenges in BFSI

Before embarking on the journey of RPA and AI implementation, it’s crucial to acknowledge the pre-implementation challenges. Data security and regulatory compliance are critical in the financial services industry. Protecting sensitive customer data while adhering to strict industry regulations presents a complex puzzle. Furthermore, upskilling the workforce to adapt to these transformative technologies is a challenge that cannot be underestimated by CFOs, COOs, and industry professionals.

Potential of RPA and AI in BFSI:

RPA holds the power to streamline BFSI operations by automating laborious tasks such as data entry, transaction processing, and report generation. This not only reduces errors but also significantly improves operational efficiency. In parallel, AI ushers in a new era of data-driven decision-making within the sector. AI can predict market trends, detect fraudulent activities in real-time, and offer highly personalized product recommendations to customers. These capabilities lead to better customer experiences and more informed strategic decisions.

Solutions for Post-Implementation Challenges:

BFSI is an industry where every decision counts, embracing technology has become synonymous with staying competitive and relevant. As seasoned COOs, CFOs, banking professionals, and industry leaders, it is important to understand that the transformative power of Robotic Process Automation (RPA) and Artificial Intelligence (AI) can’t be ignored. While the potential of RPA and AI in BFSI is clear, the path to realizing these benefits can be laden with challenges. In this context, we present a strategic roadmap, tailored to your discerning vision, to address solutions to post-implementation challenges.

To Know More, Read Full Article @ https://ai-techpark.com/bsfi-rpa-and-ai/ 

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Digital Patient Engagement Platforms

Importance of AI Ethics

Can you tell us about your background and how it led you to found Cyral?

Cyral is the intersection of my passions and proficiencies. I have been on a long entrepreneurial journey. I started out as an early hire at Aster Data, which was one of the first companies to talk about Big Data, where I ran most of the engineering team. Then I founded Instart, which was in the CDN space where we focused on managing infrastructure at cloud scale. Cyral presented itself as the intersection of these two experiences — managing data at cloud scale. When I saw that companies were moving their sensitive data off-premises to the cloud, I realized they need a different way to manage the security and governance of data, and the answer is Cyral.  

Can you explain the importance of data security governance and its impact on organizations?

The number one thing most security leaders are worried about is a data breach. Companies increasingly gather sensitive information about their customers that they are tasked with keeping out of the hands of hackers. When everything began migrating to the cloud, breaches became much more common since there are so many ways for a hacker to access a database. Data is everywhere, and there isn’t a structured enough system to protect it.

Data security governance is its own category like IT security or application security, and more organizations are finding a need to address it with a specialty team or service dedicated to protecting sensitive information.

How does Cyral’s solution differ from traditional security tools, and how does it address the challenges of securing modern cloud-based environments?

Modern technology solutions are an adaptation of the past. They either take the way a company functioned in a data center and move it to the cloud, commoditize technology from big, enterprise solutions for others, or have developers recreate the work that once belonged to an IT team. Cyral does something new.

Other security tools are not database aware and have no way of knowing what’s in a company’s database or whether a user should be allowed to access a specific field or record—it’s often all-or-nothing access. Cyral addresses this issue with its complete suite of discovery, authentication, authorization, and auditing controls. Several people within the same organization can input a query into their Cyral-protected database, and depending on their role or other defined factors, each would see a different result. In fact, Cyral is the first security solution to provide all the features of database activity monitoring (DAM), privileged access management (PAM), data loss prevention (DLP), and data security posture management (DSPM) for a company’s sensitive datasets from a single platform.

Can you discuss the role of generative AI in data security and the potential risks it poses to organizations?

Generative AI is a reality for technology, so I see it working in data security in two ways. As it stands, security products make a lot of noise. They send alerts and false positives often, driving security leaders to spend time across multiple dashboards and data streams just to understand what’s happening. I anticipate that generative AI will begin to be incorporated into security products to help reduce the noise and make security analysts more productive. It will more accurately pinpoint a threat and where it is then send security teams to the right place to investigate.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-manav-mital/ 

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