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  • Creating a successful bug bounty program

    Listing a bug bounty program can help you crowdsource security vulnerabilities from ethical hackers and researchers, allowing you to improve the security of your software or platform. Here are the steps to list your bug bounty program: Define Program Goals and Scope: Clearly define what you want to achieve with your bug bounty program. Determine the scope of the program, including which assets, platforms, and applications are in-scope or out-of-scope. This helps researchers understand what they can and cannot test. Decide on Rewards: Determine the rewards you will offer for different levels of vulnerabilities. Common rewards include cash, swag, recognition, and sometimes even public acknowledgment of the researcher's contribution. Make sure the rewards are enticing enough to attract skilled researchers. Create a Bug Bounty Policy: Draft a comprehensive bug bounty policy that outlines the rules, guidelines, and procedures of your program. Include details on how to submit vulnerabilities, what's considered valid, responsible disclosure guidelines, and any legal considerations. Choose a Platform: Select a bug bounty platform or service to host and manage your program. These platforms provide a framework for researchers to submit vulnerabilities, track progress, and facilitate communication. Set Up the Program: Register an account on the chosen platform and provide the necessary details about your organization, program goals, and rewards. Customize the program to reflect your branding and specifications. Craft Detailed Briefs: For each in-scope asset, provide detailed briefs that explain the purpose, functionality, and potential vulnerabilities of the asset. This helps researchers understand what to focus on during their testing. Promote the Program: Spread the word about your bug bounty program through various channels. Utilize social media, security forums, newsletters, and your organization's website to announce the program and attract researchers. Engage with Researchers: Respond promptly to researcher inquiries and submissions. Maintain clear and open communication throughout the testing process. Clarify doubts, provide additional information, and acknowledge valid submissions. Review and Validate Submissions: Have a dedicated team within your organization review and validate submissions from researchers. Determine the severity and impact of each vulnerability and assign appropriate rewards. Reward Researchers: Once a vulnerability has been validated, reward the researcher according to your predetermined reward structure. Be prompt in disbursing rewards as a way to encourage ongoing participation. Update and Iterate: Continuously review the effectiveness of your bug bounty program. Update the scope, rewards, and guidelines based on the feedback received from researchers and your own internal evaluations. Showcase Success Stories: Highlight successful bug bounty outcomes on your website or social media channels. This not only acknowledges the contributions of researchers but also enhances your organization's credibility in terms of security. Stay Engaged: Maintain an ongoing relationship with the ethical hacking community. Participate in security conferences, workshops, and webinars to show your commitment to cybersecurity. Legal and Compliance Considerations: Ensure that you have proper legal agreements in place, such as terms of service and data protection policies. Consult with legal experts to address any legal and compliance concerns. Monitor and Learn: Continuously monitor the performance and outcomes of your bug bounty program. Learn from the vulnerabilities discovered and work to improve your security practices based on the insights gained. Launching a bug bounty program requires careful planning and execution. By following these steps, you can create a successful and productive program that enhances the security of your software or platform. Disclaimer : AI Generated Content

  • Getting Started with Penetration Testing

    In today's digital age, cybersecurity is of paramount importance to individuals and organisations alike. As we rely more and more on technology to store sensitive information, it becomes increasingly important to protect it from cyber threats. One approach to testing the strength of a system's security is through penetration testing. Penetration testing, commonly referred to as "pen testing," is the process of simulating an attack on a system or network to identify vulnerabilities that can be exploited by attackers. It is a proactive approach to cybersecurity, designed to uncover weaknesses before they can be exploited by malicious actors. Penetration testing can be performed by either an internal team or an external third-party company. The purpose of a pen test is to identify vulnerabilities in a system that an attacker could potentially exploit to gain unauthorized access or steal sensitive data. Penetration testing involves a series of steps, including reconnaissance, scanning, enumeration, exploitation, and post-exploitation. Reconnaissance is the first step of penetration testing. In this step, the tester gathers information about the target system, such as IP addresses, network architecture, and software versions. This information is then used to identify potential vulnerabilities. The second step is scanning, where the tester uses automated tools to scan the system for vulnerabilities. The tools used in this step include vulnerability scanners and network mapping tools. The results of the scan are then analyzed to identify potential vulnerabilities. Enumeration is the third step, where the tester tries to gather as much information as possible about the target system. This includes identifying users, services, and applications running on the system. This information can be used to identify potential vulnerabilities that can be exploited. Exploitation is the fourth step, where the tester tries to exploit the vulnerabilities identified in the previous steps. This can be done using a variety of techniques, including brute force attacks, SQL injection, and cross-site scripting. If the tester is successful in exploiting the vulnerabilities, they will gain access to the system or network. Finally, the post-exploitation step involves testing the system's ability to detect and respond to an attack. This includes testing intrusion detection and prevention systems, firewalls, and other security measures in place. Penetration testing is an important component of any cybersecurity strategy. It helps organizations identify weaknesses in their systems and take steps to address them before they can be exploited by attackers. By conducting regular pen tests, organizations can stay ahead of potential threats and protect their sensitive data from cyber attacks.

  • Why digital governance is important

    Digital governance is the ability of the government to allow access to various internet services without interference. The ability of the government to enable consumer driven services through consumer owned services. In Digital form, newer and better services will be made available now and then, and the regulator doesn’t have time to vet each and every service that is being rendered to the consumer. In order to protect basic consumer rights, a digital governance system is a must for developing governments. Digital governance refers to the management of digital technologies, processes, and data by organisations and governments in a responsible, ethical, and transparent manner. It involves the creation of policies and guidelines to ensure the safe, secure, and effective use of digital technologies and information, as well as the development of systems to enforce these policies and monitor compliance. The goal of digital governance is to promote digital literacy, protect individuals' rights and privacy, and support the development of a trustworthy and inclusive digital society. Digital Governance helps in many ways. 1. Ensuring data security and privacy: Digital governance policies and procedures ensure that sensitive information is properly protected and managed, reducing the risk of data breaches and identity theft. 2. Promoting ethical behaviour: Digital governance helps organisations and governments act responsibly and ethically with regards to the use of digital technologies and data. 3. Supporting accountability and transparency: Digital governance helps to promote accountability and transparency in the use of digital technologies, data, and processes, which helps to build trust in organisations and governments. 4. Encouraging digital literacy and innovation: By promoting best practices in the use of digital technologies and data, digital governance can help individuals and organisations become more digitally literate, which can support innovation and creativity. 5. Protecting individual rights: Digital governance helps to ensure that digital technologies and data are used in a way that respects individuals' rights, such as privacy, freedom of expression, and equality. Com Olho is IP based analytics startup based out of Gurugram. The company helps organisations and government avert risk from various kind of digital frauds and recently bagged digital governance patent to protect and enhance security of online digital assets.

  • Humans of Com Olho | Shweta Singh

    My name is Shweta Singh, and I am starting as a Founder Staff at Com Olho. My career started working in the development sector with various organisations, where I have worked closely on determinants and data driven decisions. But one thing I was always thinking about was how I could make my work more relevant and professionally grow too. With technology reaching new heights, "big data" is undoubtedly becoming a buzzword and will become a growing need for organisations in the coming years. High quality Data is the foundation for making effective policies and providing the best public service delivery; what’s worse, data is often scarce in the areas where it is most desperately needed. Com Olho proposes and works to implement data priorities for the holistic development of cities. I was also specifically looking for something related to data with development while transitioning to my new job. Well, when "there's a will, there's a way," I met our founder, Abhinav Bangia, and got to know more about Com Olho, project data for development. Com Olho is providing an independent space to work, explore, and experiment with data for development. I am beyond excited to begin my professional journey as a founding member of Com Olho. Connect with me : LinkedIn

  • A $3.3 trillion resource drain is caused by 85% of ROT data stored by businesses.

    What is ROT data? ROT refers to (redundant, obsolete, or trivial) as a term for digital information that companies keep even when the data it contains has no practical or ethical value. Employees generate ROT by storing duplicates of similar documents, out-of-date information, and unnecessary data that hinders the achievement of organizational goals. ROT is harmful in five crucial ways. Expenditures for storage, infrastructure, and maintenance are high. It makes it harder for staff members to prove that they are following regulations or to react to discovery requests. It hinders employees' capacity for quick access to pertinent facts and swift, data-driven judgment. ROT is frequently poorly managed, which leaves it open to data breaches. Information that is kept after its legally mandated time frame also puts the organization at risk of responsibility. Causes of developing ROT data It has been recognized that employees use business IT systems as a repository for their personal data. Files, such as images, games with music including legal documents and personal identification. All of it ultimately coexists alongside sensitive and important business data. Sink and sharing services frequently transfer these files, however, they may not always be the ones approved by management. And not just employees are in possession of data. Still in use is the conventional method of storing everything. In what part of a data Berg does all this data go? Consider this as a mountain of accumulating data that is always increasing and permeates every Organisation. Only 14% of this data, according to research, is crucial for business.32% is of little or no commercial value. This indicates that the majority of data stored by the company is dark or unidentified. Organizations that have amassed data without procedures in place to classify and evaluate what they are holding on to are finding that the ROT data, which has an unknown value, and redundant, outmoded, or inconsequential data are being considered as an enormous burden according to senior IT decision makers. The issue has been exacerbated in part by the quick expansion of data collection methods. Businesses can now gather M2M data, log files, analytics, surveillance, and location information to use it to improve various aspects of their operations. However, the problem is that there are massive volumes of data being saved that have no value or worth that are unknown since they have not been analyzed because there are no procedures in place for the storage and management of such data. Practices to avoid ROT burden A straightforward victory might be achieved through proper data management created by a well-thought-out big data plan, especially because IT is expected to do more with less as a result of decreasing funds. Most people struggle with not knowing what data to start with, what risks it might hold, or where the value is found. They may involve other company stakeholders and go on with a well-thought-out plan faster and with greater confidence if they have visibility into that environment. Given the growing number of data rules, like the EU's General Data Protection Regulation, which will take effect in the next two years, not knowing what is being held can be extremely risky. Businesses will be required by the regulation to conduct mandatory breach notifications and also have to keep in mind the type of data they store. The corporation will have to disclose what data has been breached and inform customers if their data has been exposed in any manner. Full breaches will result in a penalty fee of either €100 million or 4% of the company's yearly revenue. The issue is whether corporations can accomplish that given that 52% of the data is regarded as dark. Even while certain data must be maintained for legal or compliance requirements, a successful data management strategy that integrates business and IT eliminates a lot of superfluous data. "It's an age-old challenge; you have IT saying keep nothing and legal and compliance saying preserve everything so you have to find that balance," said Joe Garber, VP, of Marketing, HPE Software, Big Data Solutions, to CBR. There are two practices to approach the issue: one is to examine historically across time to create the best possible policies, and the other is to get close to those policies and properly analyze them. This entails analyzing the policies to determine what is required and what is not. According to IT leaders, the survey concluded that just 15% of all stored data may be categorized as business-critical data. It is anticipated that storing non-critical information will cost an average midsize company with 1000 TB of data more than $650,000 per year. Financial losses for companies can be seen as a result of these practices and, sure enough, using data that isn't compliant could cost them much more. How therefore can businesses approach the data? Make a move, to archives, make better business decisions Securely erase or anonymize your data. Take command, Improve the information management policies, and influence employee conduct Illuminate ROT data to draw attention to value and reveal risk. Make a taxonomy for your data that is practical. Establish a consistent set of definitions, labels, and groupings with the help of important stakeholders so that you can comprehend the data you have. Establishing best practices and policies to control ROT data. Create routines, for instance, for deleting unnecessary data and old records. For every category of information, establish a single source of truth (SSOT). Preventing the development of ROT Being one step ahead of the development of ROT data requires constant effort rather than a one-time action. Investing in a powerful file analysis system or tools available in the market will help businesses automate important information management processes, assure proper data tagging, and promote strong information management based on smart data evaluation. Following are some steps businesses can follow to prevent ROT development. Recognize ROT data throughout the whole IT infrastructure. Facilitate activities related to legal and regulatory compliance Making data more accessible will boost productivity. Cut back on data management and storage expenses. Lessen the likelihood of security issues and lessen the financial impact of a data breach Accurate search results can help you make better decisions. Conclusion It can be concluded that employees are contributing to generating ROT by storing duplicates of similar documents, out-of-date information, and unnecessary data that hinders the achievement of organizational goals. ROT is detrimental in five key ways. Storage, infrastructure, and maintenance costs are significant. Staff members find it more difficult to respond to discovery demands or to demonstrate that they are adhering to regulations. Employees' ability to quickly access important facts and make timely, data-driven decisions is hampered. ROT typically exhibits inadequate management, which makes it vulnerable to data intrusions. The organisation runs the risk of liability if the information is maintained for longer than the minimum amount of time required by law. By 2020, managing (ROT) Redundant, Obsolete, Trivial, and dark business data might cost corporations $3.3 trillion. Thus, companies are advised to take strict regulatory action to prevent the development of ROT data. Businesses will be required by the regulation to conduct mandatory breach notifications and also have to keep in mind the type of data they store.

  • The Top Ethical Principles for Web Machine Learning

    As the world becomes more dependent on computers and algorithms, artificial intelligence (AI) and machine learning (ML) will play an increasingly important role in our lives, especially as they become smarter and increasingly complex. Because of this, it’s important to create ethical principles that guide the use of AI and ML so that we may avoid catastrophic consequences like those seen in Hollywood movies like Skynet or The Matrix. Here are the top five ethical principles for web machine learning to help guide both your development process and your business decisions. What is Web Machine Learning? Web machine learning is a process of using algorithms to automatically learn and improve from experience without being explicitly programmed. It is mainly used to make predictions or recommendations based on data. The two main types are supervised, where the algorithm tries to predict an outcome, and unsupervised, where the algorithm groups objects together in clusters. Supervised machine learning is most often applied in problems such as spam detection, language translation, autonomous driving systems, etc. Unsupervised machine learning has applications in pattern recognition (e.g., image compression), recommender systems (e.g., movie recommendations), etc. Fairness When it comes to web machine learning, fairness is one of the most important ethical principles to consider. Fairness means that individuals should be treated equally and fairly, without discrimination. Accuracy In machine learning, accuracy is a measure of how well a model predicts outcomes. The higher the accuracy, the better the predictions. However, accuracy is not the only important thing to consider when creating a machine learning model. There are also ethical principles that need to be taken into account. Transparency To maintain trust with users, machine learning systems must be transparent about how they work. This means providing information about the data that was used to train the system, the algorithms that were employed, and the results of any evaluations that have been conducted. Furthermore, it is important to give users control over their data and what happens to it. This includes letting them know when their data is being used to train a machine learning system and giving them the ability to opt-out if they so choose. Privacy One of the most important ethical principles when it comes to web machine learning is privacy. Any data that is collected should be done so with the explicit consent of the individual involved. Furthermore, this data should be anonymized as much as possible to protect the identity of the individual. The data should also be stored securely to prevent any unauthorized access. Finally, when the data is no longer needed, it should be destroyed securely. Security When it comes to web machine learning, security is of the utmost importance. After all, you’re dealing with sensitive data that could be used to exploit individuals or groups. Here are five ethical principles to keep in mind when working with web machine learning How can good ethics have a better future? There's no doubt that machine learning is revolutionizing the way we live and work. But as with any new technology, there are ethical considerations to be taken into account. And these considerations are often overlooked. It's not always easy to separate the good from the bad in this arena of ethics. Case Studies: Insurance Sectors There are a few case studies that show how the insurance sector has been evolving with the changes in technology. In one case, an insurance company started using predictive analytics to identify which customers were more likely to file a claim. The company then proactively reached out to these customers to offer them preventive care options, which helped reduce the number of claims filed. In another case, a different insurance company started using machine learning to automate the process of detecting fraud. This not only helped the company save money, but it also helped them improve customer satisfaction by catching fraudulent claims before they were paid out. Conclusion To improve the accuracy of their algorithms, many companies have begun using machine learning to personalize services and target users with advertising based on their browsing history and other data points like their location or gender. This has raised privacy concerns among consumers and has become a hot-button issue in Congress, but as long as people are willing to give up their personal information to receive tailored ads, this practice isn't likely to change any time soon.

  • Ethical Dilemmas of Digital Marketing

    When it comes to the world of online marketing, many potential ethical dilemmas can arise as you run your business. These issues can affect your clients, your employees, and even yourself – but they don't have to get in the way of being successful with your business if you keep them in mind and make smart decisions when they come up. Here are seven common issues that you should consider when you're starting up your company so that you can avoid any possible problems down the road. What is Digital Marketing? Digital marketing is the process of using online channels to promote and sell products or services. The main goal of digital marketing is to reach a wider audience than traditional marketing techniques and to do so more effectively. However, with increased reach and effectiveness comes increased responsibility. While some ethical dilemmas are relatively easy to solve, others are much harder. For example, when should content be promoted? When should it be taken down? What guidelines should be followed for sponsored posts? What guidelines should be followed for influencer campaigns? These questions have no right answer because they all come down to one's moral compass. A good rule of thumb is to not hurt people; don't intentionally take advantage of them. As marketers, we must always remember that our words and actions will have consequences that can have lasting effects on others. 1) Google Analytics Google Analytics is a powerful tool that can help you track and analyze your website traffic. However, it's important to use this tool ethically, to avoid violating the privacy of your visitors. Here are seven ethical dilemmas to consider when using Google Analytics 2) Tracking Page Visitors vs. Users You want to track who is visiting your website or landing page so that you can adjust your marketing accordingly. However, you also don't want to be accused of invading someone's privacy. This ethical dilemma is a common one in digital marketing. 3) User Experience In a world where companies are constantly vying for our attention, it's important to consider the ethical implications of digital marketing. From bombarding us with ads to collecting our data, there are a lot of ways companies can cross the line. 4) Misleading Ads Ads that are intentionally misleading are not only unethical, but they're also illegal. You could be fined or even sued if you're caught running a misleading ad campaign. Plus, you'll lose the trust of your customers and damage your reputation. 5) Fake Links Digital marketing is one of the most effective ways to reach consumers, but it's not without its ethical dilemmas. From privacy concerns to manipulation, here are ethical concerns you should consider before starting your next digital marketing campaign. 6) Customer Privacy In the digital age, consumer privacy is more important than ever. With so much information available online, it can be difficult to keep track of what data is being collected and how it's being used. As a marketer, it's important to be aware of the ethical implications of collecting and using customer data. 7) Clickbait Headlines Digital marketing is full of ethical dilemmas. From collecting data to using AI, there are many gray areas when it comes to what is considered ethical. How can good ethics have a better future? In a world where technology is constantly advancing, businesses need to be aware of the ethical implications of their marketing practices. By understanding and following the seven ethics of digital marketing, businesses can ensure they're making the best decisions for their customers, employees, and shareholders. Wholesaler Drives: A Case Study As a wholesaler, you're always looking for ways to increase sales and grow your business. You've been using traditional marketing methods for years, but with the advent of digital marketing, you're not sure if it's the right move for your company. After all, there are some ethical concerns associated with digital marketing. Is it worth the risk? Conclusion Digital marketing ethics represent the core values that guide ethical marketers to make decisions when planning, producing, delivering, and evaluating their marketing programs. In today's digital age, brands have more avenues than ever to connect with consumers. This also gives them more opportunities to engage in unethical practices that can harm the health of their organisations and brands over time. That's why marketers need to learn about digital marketing ethics and practice them regularly in their day-to-day work lives.

  • Importance of Ethics in Internet 4.0

    What is ethics in IoT ? The ethics in IoT, or as it is known in its full form, the Internet of Things, refers to a common code of conduct which should be followed and maintained by software and app vendors, corporate organisations and even the government to prevent misuse on the consumers. Due to the widespread reach of IoT, and its usability in all walks of life, with your electronic devices and even your home security, it is necessary that a certain standard of ethics be maintained so that the privacy of the consumers be protected and their data be safe from unscrupulous users. Ethics in IoT refer to maintaining standard encryption for personal chats and profiles not provided in public, not giving away too much data to third party vendors , and overall protecting the safety and security of the consumer who is accessing via a certain application in an electronic device. It refers in general to maintaining an honourable code of conduct, not breaking any government laws, and not leaking or destroying the privacy of its own consumers. Ethical Design for IoT In recent years, ever since the internet evolved to become the Internet of Things, there has been a surging demand to reconsider how privacy and data protection laws are present and how they can be further upgraded from misuse. Most general apps and softwares working with Internet access have hidden fine print where you agree to provide all your personal data provided in the software to third party services. This data is later used by most companies for market research and targeted trends whereby your personal data is utilised to understand what you like and to constantly show you similar things so that you remain a constant consumer. However, in recent years, both Europe and US passed a few laws which reiterated the need for data protection of the consumers by providing an ethical design in the IoT. This included informed consent, where the consumer should be made fully aware of how the data they provide will be used, and context, that the data provided can only be used in the context it was provided. An ethical design of IoT also is supposed to include that the consumers should have higher control over how much data they are willing to share for the third party. An ethical design includes giving consumers more control over their data and their choices and allow them to have a greater say in developing market trend research, or the information they will use. Ethics Challenges in IoT There have been quite a few ethical challenges in IoT regarding the following situations: Owner Identification As IoT continuously keeps tracking the location of the consumers for data collection, the identification of the owners of the electronic devices and the places they go to could be accessed by pervasive means, leading to loss of privacy and potential danger. Public and Private Border Line By continuously accessing our personal data, what we search for, our needs and wants, and sharing and selling the data to other apps, the line between what we keep as public and what we like to find in private has been getting blurred. People’s Life Attacks Due to such breach of privacy and data security, many people have been in danger and have been targeted by stalkers, kidnappers and serial killers often leading to loss of life. Case Study: Smart Cities Smart cities will be cities whereby all electronic devices, roadside assistance devices etc will be used to help in better governance of the city. By collecting the data obtained, whether on traffic or on crime, or general statistics of city life and its population, the government can use this data to improve the life of its citizens. Los Angeles and Singapore have been precursors and current smart cities where similar data has been collected to improve the day-to-day life of its people. Conclusion Thus, the above article shows that the internet of things(IoT) is here to stay. And the current ethics present still have a lot of modifications to be desired in order to maintain the customers trust. However, in the long run it will definitely help to improve lives and improve our connectivity to the world while maintaining our privacy.

  • Building India's first Gene Tech Quantum Computer

    In order for the world to proceed to better technology, a human gene based quantum computer is the need of the hour. How can you system progressively build dreams into reality. This would require an amalgamation of nature science and variable led quantum computation. Energy equation is relatively easy in a human form than in object form. A human form becomes at 0 zero energy when the time v/s truth is infinite. Your brain develops thought process in order for your brain to revive each instance of life. Gene Tech is also important to eradicate bad humans from face of the earth. The non-free minds develop only capability systems which lack performance. Hence the better gene would be able to harness better quantum computations on sheer better brain capability. Digital crimes culprit i.e pirated content, deep-faked pornography, Digital Prostitution, and Media and advertising manipulation. The gene based system would itself corrupt out once bad dreams or mutations are developed in the brain. More coming onto this

  • The emergence of Mobile Ad Fraud in Southeast Asia and India

    The phrase "cybercrime" is not new, but most people would associate it with credit card theft, email scams, or data loss. However, there is another fraud that is even more prevalent today - Mobile Ad Fraud. Mobile ad fraud is a type of ad fraud plaguing mobile based performance campaigns. It is an attempt to exploit mobile advertising technology by defrauding advertisers, publishers or supply partners. The objective of the fraudsters is to burn marketing and advertising budgets. Being able to fight mobile ad fraud demands an understanding of the types of techniques fraudsters use day in and day out. Find below some of the most common types of mobile ad fraud techniques, how they work and what threats they pose. Types Of Mobile Ad Fraud Mobile ad fraud is a constantly changing field, and fraudsters are getting creative with their approach to mimic real consumer behaviours. The same fraudsters that generated nonhuman impressions last year using malware are also capable of misrepresenting desktop impressions as premium CTV this year by using deceptive methods. BOT Fraud - Bots are basically the non-human traffic coming your way and imitating the real traffic. This can be defined as the artificial inflation of clicks and impressions on any website which may affect the revenue of the publisher. It includes unintended clicks or non-human traffic. IVT Fraud - Also referred to as Nonhuman Traffic (NHT), IVT is online traffic generated from machines or other bot activity that interacts with digital ads. This traffic does not fulfil any ad serving quality in terms of ad clicks and impressions. In most cases, clicks and impressions not made with genuine interest are considered invalid traffic. In the world of mobile advertising, IVT disguised as human behaviour is a huge issue. Types of Invalid Traffic (IVT): There are two types of IVT which are: 1. General Invalid Traffic (GIVT): It stays in the background and is a negligibly risky type of IVT. The bots coming from non-threatening places generate this type of IVT. However, these are least risky, but they have their own functions. These help in measuring, iterating and improving the ecosystem. Moreover, GIVT does not have any engagement with ads on a website. 2. Sophisticated Invalid Traffic (SIVT): This is the kind of invalid traffic which actually is ‘invalid’. SIVT is the traffic which is generated to click or view ads, in turn, enhancing the revenue. Along with it, fraudsters use SIVT in order to manipulate location data, to hijack devices, to spoof domains and much more. Fraudsters usually work well on patterns so that their activities don’t get detected easily. Thus, curbing SIVT is essential for reaching your desired revenue. Fraudulent Instals - Fraudulent installs are often driven by incentivised campaigns. Users are lured to install apps and in order are offered some form of points, coupons, cash backs and discounts. These installs are often classified as incent installs. Adware/Malware - Mobile malware are malicious software that impact the mobile operating system. They are intentionally designed to track user’s data and their digital footprint. As more and more users are moving towards mobile operating systems, cyber criminals are changing tactics and designing more prominent malware for financial gains. Mobile Ad Fraud Levels in Southeast Asia and India Mobile ad fraud has evolved from simple actions like claiming impressions into more sophisticated activities that are even more harmful and very well concealed. Although the issue of mobile ad fraud is not new, the expertise of today's "white collar" fraudsters makes them a continuing threat to the digital advertising industry. Southeast Asia has more than 360 million internet users, making it a lucrative target for fraudsters. With a growing digital population and smartphone users in the region, brands are spending exponentially in digital, giving more reasons for fraudsters to be active. With 90% of Southeast Asia's 360 million internet users primarily connecting to the internet through their mobile devices, it’s no wonder that the in-app environment is a key target for the fraudsters. Indonesia and Vietnam, are the two fastest growing digital economies in Southeast Asia also show the second and third highest rates of SIVT, indicating that fraudsters are following the money and momentum. Nonetheless, it’s a common trend that mobile ad fraud prevails globally, not just in Southeast Asia and India region, and it’s going to just disappear. Fraudsters are getting smarter and faster. There are no tools to remove it completely, and it is having a huge impact in both campaign performance and ad spends. Despite understanding all these, combatting mobile ad fraud is often seen as optional rather than necessary arms race. Industry barriers in technology adoption across Southeast Asia and India As digital ad spend grows at a rapid pace in the Southeast Asian and Indian market, the incentives for fraudsters to innovate and find new fraud methods are growing too. Due to its size, growth, and comparatively low investments in technology, the combined region, Southeast Asia is a prime target for fraudsters. This underlines a far greater need for digital marketers to deploy mobile ad fraud detection and prevention measurements. Various factors contributing to this are: Low awareness in the industry: There is a general lack of awareness around sophisticated mobile ad fraud within the wider digital marketing industry, and mobile ad fraud is largely understood only at more senior levels on the brand and enterprise side. Technical challenges: Mobile ad fraud is still considered to be a technical area of expertise across our industry. Only about half of the industry really has an appreciation and understanding of mobile ad fraud in their roles. This means that it is a topic where expertise is reserved to those in more technical roles, ad-tech platforms or senior positions at enterprises. Brand managers, media planners and client-facing staff at social platforms may not be as familiar with or have a deeper awareness of the complexities of fraud and the corresponding tools and technologies available to combat each of these fraud types. Misplaced success and cost metrics: Increase in ad spends on digital channels has resulted in a rise in ‘bad actors’ that lure marketers into buying fraudulent inventory. When compared to legitimate sources of inventory, these ads typically perform well, with high click-through rates (CTRs) and view-ability. These misunderstood success metrics drive marketers to focus on quantity (reach and engagement) more than quality - meaning they often end up overlooking the threat of mobile ad fraud. What’s Next? Digital space is one where fraud gets rewarded easily as there is a lower barrier to entry and a chance of getting caught. Southeast Asia and India face unique challenges in mobile ad fraud, and it is clear that mobile in-app fraud is one of the key areas they need to look into. This is a constant battle with the market’s growth rate far exceeding the ability to keep up with new fraud mechanics in the space, and technical challenges and limitations in the region. Additionally, a focus on click-related KPIs and low media costs further increase the potential for fraudsters. Beyond understanding the potential threat that mobile ad fraud has as well as the limitations we have, the industry also needs to understand that there are many ways to combat mobile ad fraud and it takes the entire ecosystem to do so.

  • The concerning development in Digital Banking Fraud

    The onset of the COVID epidemic in early 2020 necessitated major adjustments in the global economy. Meanwhile, digital technology in the banking and financial sector has made its operations much easier than ever. In fact, mobile banking in the United States increased by 50% in the first half of 2020. Furthermore, another report quoted that more than 8 in 10 Indians with a bank account in metro cities use mobile banking apps amid the pandemic. Although consumers have welcomed the convenience of digital payments and banking services, there has clearly been an increase in digital banking fraud also. Because of the rapid acceptance of digital payments around the world, fraudsters have found a variety of methods to affect the banking industry. Fraudsters have access to cutting-edge technology and in recent years, they have been more effective in exploiting digital channels. It is thus necessary to identify and tackle the growth of digital banking fraud to not only safeguard the consumers but also to strengthen financial institutions as a whole. Internet Banking Fraud Internet banking fraud includes any attempt to steal money fraudulently from one bank account to another. population around the world are using internet banking services for making online purchases, transferring money, and paying bills. And fraudsters will always find their way to steal money from where it is stored. Financial institutions are increasingly subjected to a variety of cyber threats, such as phishing, card skimming, identity theft, spyware, site cloning, and so on. Moreover, consumers have now shifted to mobile devices for all banking operations. And there is always a risk of mobile ad fraud that can infect mobile phones. Furthermore, there are gaming apps that can inject malware and can go unnoticed at times. Fraudsters have also targeted recent innovative banking services, such as mobile wallets. Anyone could easily fall into the hands of cybercriminals due to simple ignorance or carelessness. All of this increases the risk of digital banking fraud, necessitating the development of security measures. Dangers of Digital Banking Fraud With advanced technology in their arsenal, fraudsters are taking advantage of the digital channels to exploit their regular behaviour. There is an increased risk of financial information being compromised. Right after the peak of the COVID pandemic, institutions reported a nearly 35 percent increase in fraud attempts. Meanwhile, global identity fraud losses recorded $56 billion, affecting financial institutions, enterprises, and consumers. The techniques for committing digital banking fraud are becoming increasingly sophisticated and are thus surpassing the tools designed to detect their malicious actions. With advanced technologies, fraudsters are continuously upgrading their methods to evade prevention measures. Phishing, identity fraud, as well as the variety of digital payment options, are continuously assisting bad guys in their objectives. Even though security concerns have developed drastically over the years, fraudsters and bad actors are still a curve ahead of the banking security procedures. The risk is further elevated by external factors such as new technologies, greater consumer use of mobile apps, international data exchanges, and use of third-party data, among other things. More importantly, it is the uninformed and uneducated customers who are mostly targeted by scammers. They frequently threaten consumers' financial insecurity in order to deceive them. Additionally, banks and other financial institutions need to consistently improve consumer awareness of secure online transaction practices. Digital Banking Fraud not only costs businesses losses in monetary terms, but it can also inflict reputational damage to banking institutions. There is a greater risk when clients lose trust in their financial institutions when they are faced with fraud. To prevent these consequences, banks must strengthen their security solutions and also educate their clients about how innovative technology keeps their payments and accounts secure. Securing the digital banking ecosystem Banking institutions require a broader range of digital data and a hybrid, multilayered approach in order to effectively fight this problem. Given this risk, financial institutions must maintain strong security positions. It is high time that banks invest in cutting-edge digital solutions to meet consumers' security and privacy concerns. Further, it is equally important to educate customers on how to secure their accounts, since it is them at the forefront of digital fraud. Without a doubt, user negligence or lack of understanding is another reason for fraud. In today's changing world, consumers have high expectations of their financial institutions, and security is a critical element of their concerns. Institutions must leverage consumers' growing interest in digital banking right now, and they must stick to the following suggestions to remain competitive. Banks must reinforce their security posture by using high-quality security measures that assist limit the frequency and severity of data breaches. It is a must to invest in a broad range of anti-fraud security measures to win the war against bad actors. A security portfolio based on trustworthy identities, data, and payments will ensure their sustainability in these alarming times. Additionally, educating clients and customers is highly important. While customers do not need to understand the intricacies of the security technology, they need to be assured of how institution secures their accounts. Many are aware of basic security features such as username and password, two-factor authentication, and fingerprint recognition, but consumers likely need more education on advanced features such as biometric authentication methods. Furthermore, they must also be guided on precautions necessary to avoid any attempt of digital banking fraud. For instance, it is advisable not to install any suspicious application without first confirming its intended use and potential consequences. Also, avoid using public networks or unsecured wifi for doing digital transactions. Another important tip is never to reveal your PIN to anyone. Final thoughts The financial services business is undergoing a massive digital transformation. It is highly important to detect and prevent banking fraud. Fraud protection techniques must evolve as consumers rely more on digital platforms for financial services. Banks need to build and serve their customers with a strong and user-friendly fraud protection system. This would simply require a new approach to fraud detection that uses machine learning and data analytics to reduce risks and hence can be the right strategy.

  • Anatomy of Mobile Ad Fraud: Bad Bots

    As of 2022, there are approximately 5 billion internet users worldwide. With the majority of the global population residing online today, most companies have started investing in creating digital business infrastructures. Resultantly, data is now considered one of the most essential components for running businesses. The value of data is equalised to treasure in the online world. To simplify their work, many businesses employ bots. A computer program that assists companies in automating several activities to sustain the operation. While utilising bots is considered a fairly normal practice, some internet bots are notoriously popular for malicious intent. The prevalence of bad bots suggests that cybercriminals are engaging in a lot of fraudulent activity and cyberattacks. In fact, even mobile devices are now plagued with bad bot attacks. Alarming patterns reveal an increase in the number of cyber attacks carried out by bad actors utilising bots. Given these advancements, it only makes sense to understand bad bots and learn how to combat them. Internet bots: What Are They and How Do You Use Them? Internet bots or bots are programs that are designed to automate online tasks. Mostly, bots are used to automate monotonous tasks. Numerous internet tools and applications employ them, and they have grown to be an essential component of what makes the internet work. Even Google uses bots as crawlers to analyse web content in its search engine. In another instance, Bots are continuously used to carry out more advanced tasks as a result of artificial intelligence and machine learning. Similarly, bots can also be used to perform questionable activities, such as delivering automated clicks and installs on targeted ads, stealing attributions from traffic sources at the last moment, injecting fake clicks, and so on. It is very clear from the above example that bots can also be, and are very often, used for mobile ad fraud. What makes a bot, a bad bot, and how can it impact businesses, let's discuss? Type of Mobile Ad Fraud: Bad Bots Bots that are being commanded by fraudsters are used in a variety of hacking and fraud schemes, which is concerning. Many enterprises in general, have been dealing with bot activity for years. The traffic from "bad bots," is fake. But more importantly, these automated visitors are draining companies' marketing budgets by stealing money from their ad campaigns. There are many ways through which bad bots are committing mobile ad fraud. Digital ad fraud Bots can be programmed to click on ads on a page, and hackers can manipulate pay-per-click (PPC) ad campaigns. With these false clicks, fraudsters can perform click injection, click spamming, click hijacking, etc. Resultantly, these practices can bring in money for dishonest publishers. Background bots operating on user’s devices Mobile bots are injected into users’ mobile devices when they install any suspicious mobile app. This malware, once installed, secretly functions in the background, draining the battery and performance memory of the device. More sophisticated bad bots can even steal data and confidential information, posing a much greater threat. Web scraping Moreover, hackers can also steal web content by sending bots crawlers to genuine websites. As a result, they can also spoof real websites and deceive visitors by diverting them to fake websites. In addition to stealing the content of entire websites, bots are also employed to gather particular internet data, such as contact, financial, and personal information. Aggressive Bot attack A network or application can be flooded with a huge quantity of traffic by malicious bots attacks. Many websites and mobile apps will stop being accessible to authorised networkers once they are flooded and the allotted resources have been consumed. In addition, spam bots can also post fraudulent comments, product reviews, and app installs in large volumes. Fraudsters and hackers are getting more inventive with bad bots and improving sophisticated bots to keep on practicing mobile ad fraud. They are creating harder-to-detect bots by designing them to get around existing cybersecurity solutions. Hackers are able to carry out fraud activities on a large scale thanks to the usage of vast botnets. Simply put, these bad bots are harming certain businesses, and it's imperative to build precautions that help safeguard the business interest. For marketers, it is highly important to avoid any form of mobile ad fraud, to ensure the best return on their ad spending. Bad Bots: How Do We Combat Them? Getting harmed by malicious bots can have negative effects. Bot traffic can impact how well a business performs in addition to using up computing resources. A bad bot attack can expose networks to other types of cyberattacks, such as data theft. It is obvious that action must be made to stop them from becoming out of control. Here is how you can counteract the bad bots: Identifying non-human visitors Distinguishing between a human visitor and a bot should not be difficult, given that bots are programmed to function artificially. It is also possible for sophisticated bots to imitate actual human behaviour. However, by looking at online analytics and traffic, you can determine whether your networks are being attacked by bots. Anomaly in traffic source, increases in bandwidth usage, or login attempts can be indicators of an increase in bot activity. Potential bot activity can also be discovered by monitoring IP addresses and the geographic locations of traffic sources. Implement improved cybersecurity solutions The advancements in fraudulent techniques call for an equally advanced approach to fight them. After a time, manual intervention to identify mobile ad fraud can get more challenging. It thus necessitates the usage of data and machine learning to safeguard business interests. The cybersecurity solution from Com Olho can help companies stop numerous forms of mobile ad fraud, including bad bots. Start safeguarding your advertising budget right away! Schedule a free demo with Com Olho to protect your advertising campaigns. Final Thoughts Given the prevalence of harmful bots, advertisers and even publishers should pay close attention to their traffic. If left unchecked, poor bot traffic can quickly escalate from a nuisance to a full-fledged cyber attack. A comprehensive understanding of bots can help mitigate malicious bot attacks and protect your business and make the internet more secure for everyone.

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