Harikrishna PrabhuCOO, Technobind Solutions As cyber threats evolve at an unprecedented pace, organizations find themselves entangled in a web of fragmented security solutions, each promising protection but collectively creating chaos. From endpoint security and cloud protection to identity access management and compliance tools, the sheer complexity of managing multiple platforms often leaves security teams overwhelmed and vulnerable. This disjointed approach not only increases operational inefficiencies but also widens security gaps – offering adversaries an opportunity to exploit weaknesses. A unified platform can bridge these security silos, transforming risk management from a reactive burden into a proactive, intelligent defense mechanism that simplifies operations, enhances threat response, and fortifies an organization’s cybersecurity posture. The Complexity Conundrum Traditional cybersecurity strategies rely on disparate security solutions, forcing security teams to juggle multiple dashboards, policies, and alerts. This siloed approach creates blind spots, delays incident response, and increases the risk of misconfiguration – often the weakest link in cybersecurity defenses. The Shift to Centralized Risk Management A centralized risk management platform consolidates security functions into a single pane of glass, providing real-time visibility, streamlined workflows, and automated threat intelligence. By integrating risk assessment, compliance tracking, and threat detection into one ecosystem, organizations can proactively manage vulnerabilities before they escalate into breaches. The Benefits: Efficiency, Accuracy, and Compliance As cyber threats grow in sophistication, businesses must transition from reactive defense to proactive risk mitigation. A centralized security platform isn’t just a convenience – it’s a necessity for organizations looking to simplify security operations while fortifying their cyber resilience. By embracing centralized cybersecurity risk management like ESET Protect Platform, enterprises can reduce complexity, cut costs, and ensure a more resilient security posture in an era of relentless cyber threats. ● Holistic Visibility – Security teams can correlate data across endpoints, cloud environments, and networks, reducing the time to detect and respond to threats. ● Automation and AI-Driven Insights – Leveraging AI and machine learning, centralized platforms can identify anomalies, prioritize risks, and automate remediation, reducing human error.● Regulatory Compliance – Organizations can maintain compliance with industry standards (e.g., GDPR, NIST, ISO 27001) by aligning security policies across the enterprise in a structured manner. ESET PROTECT Platform: A Paradigm of Centralized Cyber Risk Management In the quest for streamlined and effective cybersecurity, the ESET PROTECT Platform stands out as a quintessential example of centralized cyber risk management. This cloud-first, AI-native cybersecurity platform integrates a comprehensive suite of tools designed to provide robust protection while simplifying security operations. Key Features of ESET PROTECT Platform ● Unified Security Management: Offers a centralized console that provides real-time visibility and control over all endpoints, facilitating seamless policy enforcement and incident response. ● Advanced Threat Defense: Utilizes proactive, cloudbased defenses to guard against zero-day and never- before-seen threats, ensuring that emerging vulnerabilities are promptly addressed. ● Extended Detection and Response (XDR): Enables comprehensive threat hunting and incident response capabilities, allowing security teams to investigate and remediate sophisticated threats effectively. ● Multi-Factor Authentication (MFA): Ensures that access to organizational data is protected through seamless MFA, enhancing security compliance and reducing unauthorized access risks. ● Vulnerability and Patch Management: Actively tracks and addresses vulnerabilities in operating systems and applications across all endpoints, mitigating potential security threats from unpatched systems. As cyber threats evolve at an unprecedented pace, organizations find themselves entangled in a web of fragmented security solutions, each promising protection but collectively creating chaos. From endpoint security and cloud protection to identity access management and compliance tools, the sheer complexity of managing multiple platforms often leaves security teams overwhelmed and vulnerable In conclusion, the future of cybersecurity lies in simplification without compromise. As businesses continue their digital transformation journeys, embracing a centralized risk management approach is no longer optional—it’s a critical imperative. Platforms like ESET PROTECT exemplify this strategy by unifying security functions, automating threat detection, and providing real-time risk insights. By adopting such comprehensive solutions, organizations can transition from fragmented defenses to a streamlined, proactive security posture, effectively mitigating cyber risks while freeing up valuable resources to focus on innovation and growth. About TechnoBind TechnoBind is the first Specialist Distributor in the Indian IT channels space offering a hybrid distribution model placed synergistically between broad-based and niche distribution, to deliver high business value for its reseller partners. TechnoBind helps partners to implement solutions, which solve specific business pain points arising out of the rapidly changing facets of technology for businesses. TechnoBind’s sole focus is to help enterprises manage and make the most of their most precious asset which is data. The portfolio of thirty cutting-edge brands spanning Access, Management, Security, Infrastructure and Cloud enables TechnoBind to uniquely address data management. Read More

Sergio BertoniLeading Analyst atSearchInform 71% of small and medium-sized businesses experienced attempts by employees to leak data, SearchInform research states. However, employees often leak data accidentally and without any malicious intent, for example, because of negligence or cyber illiteracy. Today, establishing control over employees’ actions with data is a common practice, but it is impossible to ensure without specialized software – DLP systems, which have become a basic tool for protecting companies against data breaches caused by insiders. DLP systems are also used to avoid data misuse, improve the level of work discipline, and retain valuable staff. Control within the Law The employer has the legal right to control employees to protect sensitive information such as personal data, banking and commercial secrets, data collected by state information systems, and data in industrial control systems at critical infrastructure facilities. For example, an employer is responsible for keeping passport scans and other documents of employees, the company’s partners, and clients’ data safe as well. This is enshrined in the laws of many countries, as well as in international legislation such as GDPR. However, personnel must be informed that the organization where they are employed is using an automated monitoring system (like DLP). The fact that an organization uses specialized software for employee control must be documented in corporate policies. Employees, in their turn, should be informed about what the protective system is used for, and sign a consent for their activity to be monitored. For the employer it is necessary to draw up an additional agreement to the employment contract and outline all the tasks of using the system which could be the following: ● Oversee employees’ compliance with job descriptions and internal labour regulations; ● Control the appropriate use of the company’s information resources and technical means to fulfill job duties; ● Ensure protection of commercial, trade, official, and other secrets as required by national and international regulations. The DLP systems are also deployed to maintain discipline and evaluate staff productivity. In case of such system implementation in corporate IT infrastructure, the employer should take measures to avoid conflicts and misunderstandings between the team and management. Introducing corporate regulations on working with information will help solve this task. Besides, a separate policy on how documents need to be stored, and whether it is permitted to use clouds and personal email to communicate work-related tasks and other questions is a must. This way employees will understand what is allowed to do at work and what is prohibited for them. For example, an employer may not allow an employee to use a corporate PC for non-work related activity on social networks, storing personal photos etc. What are the benefits of being monitored? The issue is that employees often interpret various monitoring systems as excessive control and distrust. In this case, it is crucial to communicate to the team the advantages employees receive from being monitored by protective software. Providing employees with real life cases will help in this regard. The first case from SearchInform practice proves that DLP systems help employees avoid being accused of a crime they never committed: ● The security department specialists found on the employee’s corporate PC confidential data that he did not have access to. Investigation revealed that the remote access tools were regularly run on his computer, however, the employee hadn’t noticed it. It turned out that the network administrator temporarily stored confidential data on the ‘victim’s’ PC before transferring it to third parties. Thus, the DLP system helped identify the real intruder and save the honest employee from being dismissed. 71% of small and medium- sized businesses experienced attempts by employees to leak data, SearchInform research states. However, employees often leak data accidentally and without any malicious intent, for example, because of negligence or cyber illiteracy. If our client did not have a DLP system, it would have been very difficult for the guiltless worker to avoid suspicion and prove that he was not involved in the data leak. Unfortunately, such cases are not uncommon. In this way, modern control systems help to avoid situations when staff members need to justify themselves. In some organizations where DLP is not implemented, in the same cases, the employees may be required to undergo polygraphs or other stressful procedures. DLP at employees’ service There are major ways, how DLP system brings important benefits to the employees. Firstly, the DLP system reduces the risk of accidental data leakage, which could lead to sanctions against the employee. The system is equipped with proactive blocking functionality, which is fine-tuned by an Information Security specialist. The feature reduces the chances of confidential documents intentionally or unintentionally leaving the company’s information perimeter. DLP also notifies the user (InfoSec specialist or another professional in charge) about suspicious employee activity. In addition, DLP systems can be equipped with the open mode of operation that empowers the user not to commit dangerous actions with the help of special notifications. It is also possible to customise alerts about dangerous actions or enable the user interface – a visible window on the taskbar so that personnel can communicate freely with the InfoSec professionals. ● Case: The employee of the research institute was preparing documentation containing data from clinical trials of the drug. Out of habit, he sent the documents for review to a former manager, who at the time was already working for a competitor. The incident that occurred by mistake severely damaged the reputation of the institute. However, it could have been avoided if the DLP was deployed. Secondly, DLP ensures confidence that all incidents will be investigated objectively and thoroughly. This applies not only to prevent false accusations but also to verifying complaints from employees about arbitrary behavior by the company’s top management. ● Case: One of our clients, a retail company deployed a DLP system. Then, a suspicious email to the CFO from one of the dismissed employees was found. Ex-worker accused the CFO of taking full advantage of the CEO’s trust to fire valuable…

By Milind BorkarMD, Systematica Suyog Security Consultants(Sr. Consultant & Security Expert) Surveillance and Security in the traditional sense is now moving forward in leaps and bounds. Gone are the days of CCTV using analog cameras that are being replaced by digital cameras that enable video analytics to be performed on an incoming digital stream. Also, between year 2005 and year 2010 there was a massive push to standardize the interface between the camera and the software that talks to it over an ethernet cable. This standard is ONVIF (Open Network Video Interface). Though many camera manufactures claim ONVIF compliance one must check the following link prepared by onvif.org – https://www.onvif.org/conformant-products/. This development disrupted the stranglehold of camera manufactures with their partners and allowed many other players to enter the market as proprietary protocols were no longer required. Most of the terabytes of stored video is useless as it does not carry any useful information. Manual searches need to be conducted to find the relevant information one is looking for. This turns out to be a time-consuming process and by the time information is found it might be out of date. This is where Video Analytics can help to some degree by looking for only relevant information thereby saving time and resources. Even though Video Analytics saves a considerable amount of time, it still does not avoid the manual process involved in looking at video instead of data. Here is where Artificial Intelligence (AI) and Machine Learning come in. AI/ (neural networks) builds a model based on a few initial parameters that are input by the user. Without getting into the details, it quickly builds a neural network and tells you the confidence level of each object found in the video frame. This is a highly mathematical process involving convolution, calculus, probability and statistics. Based on the confidence level of each object found in the frame, one can fine tune the neural network by changing the input parameters. This fine tuning is called Machine Learning by which the neural network gives confidence levels above 95% for each object found. We have done this in our product where object confidence levels went from as low as 60% to as high as 98%. One can now put the neural network in training mode telling it what the target end result the user wants. The machine then self learns by varying the hundreds of input parameters till the end target is met. At this stage the model is what the user was expecting and he now continues to use this highly accurate model to build his or her applications to solve problems specific to their market vertical. So, what AI/ ML has done is that video examination is no longer required but extracted data from the video stream is examined. This is a far more intelligent way of examining video streams and far more efficient allowing the end user to build multiple intelligent applications on top of this. This is the WAVE of the future as multiple PETABYTES of data cannot be examined after the fact. With the number of cameras increasing exponentially all across the globe, the best way to process video is on the fly in real time as it saves time, money and resources across the board. However, for a particular use case some time and money have to be invested to fine tune the neural network model. Once this process and methodology is mastered, one can use it for other use cases. In our case, some of our models took up to 30 minutes to bring up the confidence level above 95%, while in other cases it has taken up to a week. Factors that affect this training period are following: (a) Lighting, (b) Number of objects in the frame, and (c) Complexity of the shape of the object. Diagram describing our Object Classification Engine We will now describe a couple of used cases to make this clear: Used case 1: Implementing Standard Operating Procedure (SOP) Suppose a SOP is defined for a drug testing methodology in a pharmaceutical laboratory. Requirements are as follows: ● Capture and time stamp when an employee enters and exits the laboratory. ● Measure procedure when the drug testing starts. ● Identify colored flasks and test tubes and their movement from one step to the next.● Identify microscopes and other medical instruments used in measurement and how they are being used. ● Flag any deviation from SOP and report to administrators. As one can see, one can use identifying objects in the video stream and determine whether the SOP is being followed. This can be used by the laboratory management team to improve overall efficiency of the laboratory and its’ employee performance without looking at video streams. A snapshot of our current Object Classification Engine for illustrative purposes Used Case 2: Measuring queue lengths at bank counters, airport check in lines, hospitals etc. ● Determine queue lengths to determine arrival and service rates. ● Queue lengths will increase if service time is greater than person arrival time. ● Flag these so the service efficiency can be improved. Summary The neural network model has over 25 million pre-defined objects in the database. These have been developed using artificial intelligence techniques. In a typical end user case, a very small subset of these 25 million predefined objects is required. New objects are continuously being added to the database. The model also allows itself to be put in training mode based on what the end user really wants Our Object Classification Engine takes advantage of this and provides interfaces so that end user case applications can be developed rapidly and be put to use. We provide extracted data, interface to the ML neural network model as well as we provide application development services for the customer. Read More

Its Total Cost of Ownership May Surprise You! By Gaurav TaywadeDirector, India Operation, Vicon On-premise enterprise video management systems (VMS) can be a huge investment – one of the priciest elements of a company’s physical security technology infrastructure. They’re also one of the most critical. Without eyes on a property, there’s no way to ensure that other systems are doing their job. Since the pandemic, spending on VMS solutions has continued to rise. Commercial office space vacancies are high, hybrid and remote work models have businesses operating with far fewer onsite workers, crime is up, and security guards are in short supply. Building and security managers are determining that existing cameras provide insufficient coverage under these new conditions, and are therefore seeking to expand their systems. Quickly evolving technology is complicating matters, making legacy VMSs obsolete. Companies unable to leverage the latest generation of cameras, analytics, and integration opportunities are deciding that it’s time to upgrade to a new platform rather than continue to throw money into a substandard solution. After 5-10 years, the actual cost of one system may be as much as 50% lower than another As stakeholders wrestle with how to upgrade or replace their VMS network, performance and operational needs take top priority. However, once specifications are agreed upon, and various manufacturers have been identified that meet a project’s requirements, price can become the deciding factor. Unlike the straightforward comparison of technical specs between offerings, calculating and comparing the total cost of system ownership is much more elusive. The total-cost-of-ownership (TCO) is affected by many factors – some of which come as an unwelcome surprise to system owners after their VMS is up and running. At that point, it’s too late to reevaluate the wisdom of their investment. There is no magic formula for estimating TCO. Manufacturers structure their licensing, warranties, upgrades, maintenance, training, and other policies in different ways, and their promotional materials rarely spell out these distinctions. After 5-10 years, the actual cost of one system may be as much as 50% lower than another. To accurately evaluate TCO, decision-makers must know where to look for hidden expenses and the right questions to ask. We hope this whitepaper helps readers do just that. Device Licensing Practices are Sometimes Tricky Licenses are part of any on-premise VMS solution. The licensing model makes systems scalable; users pay more for larger deployments. In enterprise systems with hundreds or thousands of cameras, licensing represents a significant expense. That said, there is tremendous variation in how much licensing will cost a company throughout its VMS’s lifespan. The price-per-license differs by manufacturer, but that is only part of the story. Some manufacturers require a license for each camera. Others charge licensing fees for servers, workstations, storage, and edge devices. Licensing tied to NVRs and servers can pack a disproportionate financial wallop – especially when NVR licenses are calculated based on the number of streams supported. For example, let’s take one 12MP camera that features triple-streaming. With NVR licensing, the camera requires three licenses if all three streams are used, even if the same NVR records all three. Recording redundancy doubles the price. With two servers recording each of the three camera streams, that single camera represents six licenses! By contrast, a camera-only licensing model would require one license for this device, period. Consider how this policy substantially impacts a network with hundreds of cameras. When NVRs are licensed, adding or upgrading cameras also becomes more expensive. Let’s say a customer wishes to replace several 1MP cameras with 5MP models. The 5MP devices will impose more demand on the server. VMS systems may be infinitely scalable, but individual NVRs or servers have their limits. Adding new cameras, or replacing existing ones with higher resolution models, can result in the need for more network hardware. Once again, paying per camera – and only per camera – keeps TCO in check as systems grow. By contrast, when VMS software is free and licensing is only required for cameras, the options for keeping systems current remain uncomplicated and less expensive However, even with camera-only licensing models, there are still ‘buyer beware’ issues to consider. Some manufacturers link each license to the MAC address of a specific camera, making the license non-transferable. Limiting software in this manner is an antiquated approach that takes advantage of the user. When hardware needs to be replaced, there’s no reason the software license should need replacing too. Imagine if your laptop died and Microsoft said you must buy all new software rather than transfer your licenses to the new device. You would be irate. Finally, some manufacturers charge premium licensing fees, per device, to access certain VMS features. A camera’s specifications may indicate it “can do” certain things, but it’s possible that they are not included with a basic license. When calculating a system’s TCO, make sure you understand what your licenses include and what they don’t! Keeping Current is Critical; It Shouldn’t Be Costly Like any software, VMS platforms are constantly improving. The DevOps process used by many software development teams, with its focus on continuous feedback, collaboration, and communication, has accelerated the speed and frequency with which updates are released. Unlike business software for sales or marketing – for which new releases may be helpful but unnecessary – security software provides a mission-critical function. It should be kept current at all costs. How VMS manufacturers charge for updates affects TCO. Some updates, like those addressing bugs and vulnerabilities, may be free, but others come with a fee. Before purchasing a system, prospective owners should understand what to expect. Are upgrades mandatory? How frequently do they typically happen? Are upgrade protection plans available? How is the price calculated? Even if manufacturers do not mandate upgrades, they may ultimately discontinue support of earlier software versions, rendering the NVRs and servers running them obsolete unless the customer invests in an enterprise-wide software upgrade and relicensing. Without a systemwide update, the system owners cannot even add a single new camera….