Financial scams are everywhere these days and no one is immune. And sometimes it leaves older adults with no way to recoup their losses. Worldwide, people age 60 and over lost a combined $3.4 billion to fraud in 2023 alone.1 Behind that shocking figure? More than 100,000 very real people who have been robbed of their savings and financial security.1

“We all need to work together to make sure our seniors, their caregivers, families, and friends know the signs to look for that a criminal is after your money,” said FBI Criminal Investigative Division Assistant Director Michael Nordwall in a Facebook post.

NCOA is here to help. When it comes to stopping online scammers, knowledge is power. Below, we cover the most common scams targeting older adults. We’ll also tell you what to do if you or someone you know encounters one.

Why do financial scammers target seniors?

Fraudsters and con artists tend to go after older adults because they believe this population has plenty of money in the bank. But it’s not just wealthy older Americans who are targeted. Older adults with low income are also at risk for fraud.

Plus, many people are embarrassed to report financial scams. And they can be tough to prosecute. Criminals therefore consider them “low-risk.” However, these scams can be especially devastating for older adults whose ability to recover their losses is limited.

How common are financial scams targeting older adults?

In 2023, 536 people filed complaints with the U.S. Senate Special Committee on Aging Fraud Hotline. That brings the total number of registered complaints to nearly 12,300 since 2013.

The five scams that top the list of complaints for seniors:2

1. The grandparent scam. The grandparent scam is so effective because it exploits people’s emotions. First, a caller gains trust by tricking their target into volunteering information, like a grandchild’s name. They may say something like, “Hi Gram, do you know who this is?” Then, with that name at the ready, they impersonate the grandchild.

In this scam, fake grandchildren ask for help with car repairs, late rent, a medical emergency, or even to post bond. They pretend to be in distress. They may even beg the grandparent not to tell anyone.

In other versions of this scam, a caller claims to be an arresting police officer, doctor, or lawyer trying to help the grandchild. They prey upon emotions to pressure victims into sending money as quickly as possible. And who among us wouldn’t readily help a cherished relative in desperate financial need? These scams are even harder to identify and resist thanks to artificial intelligence (AI). Today, con artists can clone real voices of real relatives and use them to commit fraud.

People who run grandparent scams often ask to be paid through gift cards or wire transfers. These don’t always require identification to collect, which means victims have no way ever to recover their money. Some victims report that scammers showed up at their homes, posing as “couriers” to pick up the money.

2. Financial services scam. These cons work because they appear to come from a legitimate source: a bank, a mortgage company, or a debt collection agency. Scammers call, text, or send email messages that look and sound perfectly legitimate. They may claim that a checking or savings account has been compromised and ask for personal information, such as a password or Social Security number, to “secure” it. They may promise better rates or terms on a home loan. Or they may threaten arrest for unpaid medical bills—which may or may not exist.

Each of these types of claims is a lie. But scammers know how to be convincing. They can easily fake the information on Caller ID. They know how to make email addresses and links look real. And they often will use threatening language to scare their victims into volunteering sensitive information or sending money. Usually, the people committing this type of fraud will demand immediate payment through a peer-to-peer (P2P) platform.

3. Tech support scams. These scams prey upon the doubts and discomforts that many people have around computers. In fact, when it comes to fraud committed against older adults, tech support scams top the list.2 How do they work? Typically, a person’s computer or phone screen will freeze or go blank. A pop-up message will appear with a phone number to dial for help. When the user calls it, the scammer on the other end will ask for permission to log on to the device remotely. This fake “tech support” representative also may demand a fee to repair the “issue.”

4. Government impersonation scams. In government impersonation scams (also known as government imposter scams), callers pretend to be from the Internal Revenue Service (IRS), Social Security Administration, or Medicare. They threaten to arrest or deport the person who picks up the phone if they don’t pay their “unpaid taxes”. Or, they may threaten to cut off Social Security or Medicare benefits unless the person provides personal details. This information can then be used to commit identity theft.

Government imposters may demand prepaid debit cards, cash, or wire transfers as payment. Using special technology, they often “spoof” the actual phone number of a government agency or call from the same ZIP code (202 for Washington, D.C., for example). This can trick some people into thinking the caller is from a valid source.

5. Romance scams. As more people turn to online dating, con artists are seizing the opportunity. Romance scammers create fake social media profiles and use them to gain trust and steal money. In some cases, these scammers may be (or pretend to be) overseas. They may ask their victims to pay for visas, medical emergencies, and travel expenses to come to the U.S. Romance scams (also called sweetheart scams) can drag out for a long time. As a result, victims often lose a lot of money. The FTC found that in 2023 alone, more than 64,000 people reported a romance scam, with losses totaling $1.1 billion.2 Get tips for avoiding sweetheart scams.

Other popular scams targeting older adults

Sweepstakes and lottery scams . The sweepstakes scam is familiar to many of us. Here, bad actors call with good news: the person answering the phone has won the lottery or a prize of some kind. In order to claim their winnings, that person must send money, cash, or gift cards up front—sometimes amounting to thousands of dollars. Supposedly, this money covers “taxes” and “processing fees”. Scammers may impersonate well-known sweepstakes organizations (like Publishers Clearing House) to build trust among their targets. Of course, no prize is ever delivered. Sometimes, fraudsters convince people to send even more money by telling them their winnings will arrive soon. Many continue to call people for months and even years after defrauding them out of an initial sum of money.

. The sweepstakes scam is familiar to many of us. Here, bad actors call with good news: the person answering the phone has won the lottery or a prize of some kind. In order to claim their winnings, that person must send money, cash, or gift cards up front—sometimes amounting to thousands of dollars. Supposedly, this money covers “taxes” and “processing fees”. Scammers may impersonate well-known sweepstakes organizations (like Publishers Clearing House) to build trust among their targets. Of course, no prize is ever delivered. Sometimes, fraudsters convince people to send even more money by telling them their winnings will arrive soon. Many continue to call people for months and even years after defrauding them out of an initial sum of money. Robocalls and phone scams. One common robocall is the “Can you hear me?” call. When the person who answers says “yes,” the scammer records their voice and hangs up. The criminal then has a voice signature to authorize unwanted charges on items like stolen credit cards. Robocalls use automated technology to dial large numbers of households from anywhere in the world. While there are legal uses for this technology, robocalls can also be used to carry out a variety of phone scams. These include false claims about expiring car or electronics warranties. Just like government impersonation calls, scammers often spoof the number they’re calling from to make it seem like they’re from a trusted organization. Yet another popular phone scam is the “impending lawsuit” scam. In this case, someone receives an urgent, frightening call from a person pretending to be from a government or law enforcement agency (like the IRS or the police). They are told if they don’t pay a fine by a certain deadline, they will be sued or arrested for some made-up offense.

One common robocall is the “Can you hear me?” call. When the person who answers says “yes,” the scammer records their voice and hangs up. The criminal then has a voice signature to authorize unwanted charges on items like stolen credit cards. Robocalls use automated technology to dial large numbers of households from anywhere in the world. While there are legal uses for this technology, robocalls can also be used to carry out a variety of phone scams. These include false claims about expiring car or electronics warranties. Just like government impersonation calls, scammers often spoof the number they’re calling from to make it seem like they’re from a trusted organization. Yet another popular phone scam is the “impending lawsuit” scam. In this case, someone receives an urgent, frightening call from a person pretending to be from a government or law enforcement agency (like the IRS or the police). They are told if they don’t pay a fine by a certain deadline, they will be sued or arrested for some made-up offense. Business imposter scams. The Federal Trade Commission (FTC) has found that at a business imposter scam takes a heavy financial toll on consumers age 60 and older. 3 These criminals pretend to be from a business or charity, which makes them seem trustworthy. Like government imposters, business imposter scammers can fake their caller ID to make it seem like a legitimate communication. These fraudsters will try to convince someone to send money or a gift card or share personal information.

The Federal Trade Commission (FTC) has found that at a business imposter scam takes a heavy financial toll on consumers age 60 and older. These criminals pretend to be from a business or charity, which makes them seem trustworthy. Like government imposters, business imposter scammers can fake their caller ID to make it seem like a legitimate communication. These fraudsters will try to convince someone to send money or a gift card or share personal information. Investment scams. This type of scam involves the illegal or alleged sale of financial instruments that typically offer low risk and guaranteed returns. The use of cryptocurrency (digital assets, such as Bitcoin) is common in investment scams. Cryptocurrency-related investment fraud cost adults age 60 and over $716 million in reported losses in 2023. 1

This type of scam involves the illegal or alleged sale of financial instruments that typically offer low risk and guaranteed returns. The use of cryptocurrency (digital assets, such as Bitcoin) is common in investment scams. Cryptocurrency-related investment fraud cost adults age 60 and over $716 million in reported losses in 2023. Medicare and health insurance scams . Every U.S. citizen or permanent resident age 65 and over qualifies for Medicare. This makes the program a prime tool for fraud. In Medicare scams, con artists pose as Medicare representatives in order to convince older adults to share their personal information. Scammers might also provide bogus services at makeshift mobile clinics, then bill Medicare and pocket the money. Medicare scams often follow the latest trends in medical research, such as genetic testing.

. Every U.S. citizen or permanent resident age 65 and over qualifies for Medicare. This makes the program a prime tool for fraud. In Medicare scams, con artists pose as Medicare representatives in order to convince older adults to share their personal information. Scammers might also provide bogus services at makeshift mobile clinics, then bill Medicare and pocket the money. Medicare scams often follow the latest trends in medical research, such as genetic testing. Internet and email fraud. Some older adults come to technology late, and their learning curve is therefore steep. That makes them easier targets for internet and email scams. These scams include pop-up windows that look like anti-virus software; in reality, these windows install computer viruses when clicked on. These viruses can expose personal information or even disable the computer until a person pays a lot of money to have it fixed. (Sometimes this is called “ransomware.”) Internet firewalls, built-in virus protection, and other safety precautions can help prevent this type of fraud. However, users must know about these tools—and it can be hard to keep up with the latest ones. Another scam, called a “phishing” scam, uses emails and text messages that seem legitimate. They appear to come from a well-known bank, credit card company, or online store. These messages may request personal data, such as a log-in or Social Security number, to verify an account; or they may ask the recipient to update their credit card info. Scammers use this information to steal money or additional personal details. Find out how to protect yourself against phishing scams.

What to do if you think you’ve been scammed

Scams are specifically designed to catch us off guard, and they can happen to anyone. There’s nothing to be ashamed of if you think it’s happened to you. Keep important phone numbers handy, including the local police, your bank, and Adult Protective Services.

“It’s a heartbreaking fact that scams have wiped out people’s retirement savings,” said Lois Greisman, Associate Director, Division of Marketing Practices at the FTC. “If a business, government agency, or even a grandchild in need contacts you, it’s critical to check who you’re really dealing with. Never panic or react quickly. Contact them at a number you know is real to verify.”

To obtain the contact information for Adult Protective Services in your area, call the Eldercare Locator, a government sponsored national resource line, at 1-800-677-1116 or visit their website.

You can also report scams online to the FTC. Sharing your experience can help prevent it from happening to someone else.

Sources

1. Federal Bureau of Investigation. Internet Crime Report 2023. Found on the internet at https://www.ic3.gov/AnnualReport/Reports/2023_IC3Report.pdf

2. U.S. Senate Special Committee on Aging. Fighting Fraud: Scams to Watch Out For. September 2024. Found on the internet at https://www.aging.senate.gov/imo/media/doc/2024_fraud_book_english.pdf

As 2025 begins, cybersecurity continues to evolve at a rapid pace. With each new technological advancement comes an array of emerging threats that pose risks to the university’s digital security.

From artificial intelligence-driven attacks to the relentless rise of ransomware, staying informed about the top cyber threats of the future is more important than ever.

Awareness of these risks empowers all of us to take proactive steps to safeguard sensitive data and maintain digital safety. The Office of Information Technology (OIT) is working diligently to respond to attacks and prepare for new assaults expected in 2025, including:

AI-enhanced phishing scams

Unrecognizable deepfakes

Increased supply chain attacks

Protect yourself

AI phishing

In an era where artificial intelligence (AI) is seemingly everywhere, cybercriminals are also leveraging this technology to create increasingly sophisticated phishing scams.

While most phishing scams still rely on classic tactics like social engineering to manipulate, influence, or deceive us, AI has supercharged their effectiveness.

The good news is, as AI-powered scams become more sophisticated, so do the defenses against them. Advanced security tools are integrated into email systems and online platforms, helping detect and block phishing attempts before they reach your inbox.

However, while technology plays a crucial role, your vigilance remains the most effective defense.

Spot and prevent sophisticated phishing attacks

Fortunately, the principles of staying secure remain consistent, even as threats evolve. Here are actionable steps to protect yourself:

Stay suspicious: Always scrutinize messages that ask for login or financial information. Phishing attempts often create a sense of urgency to pressure you into acting without thinking critically.

Recognize red flags: Phishing emails often include urgent language, suspicious links, or unusual requests. Always verify the sender’s email address. Be wary of subtle misspellings or unusual email domain addresses.

Guard your credentials: Boise State will never ask for your username, password, or multifactor authentication codes through email or unsecured methods.

Leverage your Help Desk: OIT is your ally in defending against phishing scams. If you’re unsure about the legitimacy of a message, contact the Help Desk at (208) 426-4357 for verification or email helpdesk@boisestate.edu.

Deepfakes

Generative AI is revolutionizing technology, but it has also introduced new challenges, including the rise of “deepfakes.” These AI-generated videos or audio clips convincingly mimic real people, making it appear as though someone is saying or doing something they never did.

Deepfakes pose serious risks, from identity theft to misinformation and fraud. For instance, cybercriminals could use deepfaked audio to impersonate you in a call to your bank, or to our Boise State Help Desk.

Even if you don’t actively use AI tools, your publicly shared content—such as photos, videos, or voice recordings—could be scraped from social media or other websites and misused.

Smart practices

Here’s how to reduce your exposure and protect yourself:

Limit public content: Share personal information, high-quality photos, and videos only with trusted individuals. Adjust social media privacy settings to restrict who can view your posts.

Share personal information, high-quality photos, and videos only with trusted individuals. Adjust social media privacy settings to restrict who can view your posts. Watermark media: Apply digital watermarks to images or videos you upload. This discourages misuse by making content traceable.

Apply digital watermarks to images or videos you upload. This discourages misuse by making content traceable. Beware of phishing: Deepfake creators often use phishing schemes to access personal and workplace information. Be cautious with unexpected communications, verify sources, and avoid clicking suspicious links.

Deepfake creators often use phishing schemes to access personal and workplace information. Be cautious with unexpected communications, verify sources, and avoid clicking suspicious links. Verify content carefully: Pay close attention to photos, videos, and audio recordings. Many AI-generated deepfakes have subtle inconsistencies—visual glitches, unnatural speech patterns, or mismatched details. If you receive a suspicious message from someone you know, confirm its authenticity by contacting them directly through a separate, verified communication channel.

Pay close attention to photos, videos, and audio recordings. Many AI-generated deepfakes have subtle inconsistencies—visual glitches, unnatural speech patterns, or mismatched details. If you receive a suspicious message from someone you know, confirm its authenticity by contacting them directly through a separate, verified communication channel. Report suspicious content: Notify the platform hosting deepfake material involving you or others. You can also report personal cases to federal law enforcement for further investigation.

Supply chain attacks

A cybersecurity supply chain attack happens when hackers target workplace suppliers, vendors, or partners to sneak into the company itself. Instead of breaking into the main company directly, they find weaknesses in the systems of the businesses it works with.

It’s a sneaky way of getting in through the “back door” by taking advantage of trusted connections between businesses. This is why universities need to make sure their entire network of partners is secure, not just their own systems.

How you can help prevent supply chain attacks

Staff and faculty are often the primary gateways for malicious code injections in supply chain attacks, as cybercriminals rely on trickery to gain access to systems.

The most common method is phishing emails that appear to come from trusted colleagues. When interacted with, these emails activate malicious code and steal login credentials, which attackers then use to access systems and target higher-privileged accounts.

To prevent such attacks, it’s critical for all staff to recognize and report these threats rather than fall victim to them. Education on identifying common cyberattacks is the first line of defense.

Visit our Phishing and Spam Email Messages page to learn more about identifying and reporting phishing and spam email messages:

Need assistance?

For more details, or to report a cybersecurity incident, please contact the Help Desk at (208) 426-4357 or email helpdesk@boisestate.edu.

By Vasu Jakkal, CVP Microsoft Security

In today’s digital age, the landscape of cybersecurity is evolving at an unprecedented pace. With the rapid advancement of technology, cyber threats have become more sophisticated and frequent. The critical role of artificial intelligence (AI) in enhancing cybersecurity measures and defending our world cannot be overstated.

The Growing Threat Landscape

The threat landscape is the most complex in history. The speed, scale and sophistication of bad actors is alarming. In just one year the number of threat actors tracked by Microsoft jumped from 300 to more than 1,500. The rise of state-sponsored attacks and the proliferation of ransomware are major concerns for businesses of all sizes. In addition, the number of cyberattacks has skyrocketed from 579 attacks per second in 2021 to a staggering 7,000 password attacks per second in 2024.

This alarming increase underscores the urgent need for innovative solutions to combat the growing complexity of cyber threats. Attackers can now breach systems within an average of 72 minutes after a user clicks on a malicious link.

This escalating threat landscape has driven the adoption of AI technologies in cybersecurity, making it an essential component in the defense mechanisms.

AI: A Game Changer in Cybersecurity

Generative AI has emerged as a powerful tool in the fight against cyber threats. Microsoft processes 78 trillion signals daily, enabling the company to identify threats at an unprecedented scale and speed. One of the standout innovations is Microsoft Security Copilot, an AI-driven assistant that helps security teams defend against attacks at machine speed and scale. Since its launch in March 2023, more than 1,400 customers have utilized Security Copilot to investigate threats and manage risks in real-time.

And AI can help with another big challenge in security – the ongoing talent shortage.

Addressing the Talent Shortage

The cybersecurity industry faces a significant talent shortage, with 4.8 million security professionals needed worldwide. AI not only helps mitigate attacks but also supports human teams by simplifying complex tasks and lowering the barriers to entry for new professionals. This dual role of AI is crucial in bridging the talent gap and enhancing the overall security posture of organizations.

While addressing the talent shortage is global, specific regions like South America present unique challenges and opportunities. According to study Building a Skilled Cyber Security Workforce in Latin America, conducted in partnership with the OECD, there is a growing demand for cybersecurity professionals with specific certifications and experience. However, these certifications often require extensive expertise.

In Canada, the Canadian Centre for Cyber Security’s “National Cyber Threat Assessment 2025-2026” highlights that the country faces persistent cybersecurity challenges as financially motivated cybercriminals and state-sponsored actors target its economic prosperity and national security. Geopolitical events and global technological rivalry further shape these threats, with increasingly complex networks of actors pursuing their own interests. However, cyber vulnerabilities and the evolving cyber-threat environment, the intensity and impact of cyber threats to Canada can be mitigated through awareness and best practices in cyber security by both individuals and organizations.

Mobile AI security uses artificial intelligence to protect mobile devices from cyber threats. AI automates detection and response, enhancing security. This article explores AI’s role, key risks, best practices, and future trends in mobile security.

Key Takeaways

AI significantly improves mobile security through real-time monitoring and proactive threat detection, enabling quick responses to potential cyber threats.

Integrating AI into mobile applications introduces various security vulnerabilities that require continuous risk assessments and the implementation of robust data protection practices.

Future advancements, such as blockchain, biometrics, and zero-trust security models, are expected to significantly enhance mobile AI security by improving user authentication and minimizing data leaks.

The Role of AI in Mobile Security

AI significantly enhances mobile security by automating the identification and mitigation of cybersecurity threats. Artificial intelligence AI tools enable real-time monitoring and immediate responses to threats. Picture a system that instantly detects malicious attempts to access your data and takes corrective action autonomously. This automation not only boosts security but also allows security teams to concentrate on more complex issues.

AI-driven threat detection solutions excel at rapidly processing and analyzing vast amounts of data. This capability is essential for identifying patterns and anomalies indicative of security threats. Predictive analytics in AI can foresee future threats based on historical data, offering a proactive security approach. Continuous learning from data inputs ensures AI models become more effective in threat detection over time.

AI effectively reduces false positives, enabling security teams to focus on genuine threats. This accuracy is particularly vital in mobile environments with numerous simultaneous applications and processes. Identifying and prioritizing real threats enhances mobile device security with AI-powered solutions.

Integrating AI into mobile security creates a robust and dynamic defense system that adapts to evolving threats.

Key Security Risks in Mobile AI Systems

Introducing AI into mobile applications brings various security and privacy vulnerabilities that need management. Common threats include data privacy violations, model theft, and unencrypted communications. For example, an attacker could intercept sensitive information through unencrypted data transmissions. The opaque decision-making processes of AI models can also obscure vulnerabilities and biases, complicating security oversight.

Testing mobile applications against OWASP standards can address privacy and security risks associated with AI. Regular updates to threat intelligence databases are crucial for recognizing new vulnerabilities and potential threats in AI systems. Unauthorized use of AI prototypes can lead to intellectual property theft and exploitation of vulnerabilities, posing significant risks to organizations.

Regular security risk assessments and robust traditional security measures are essential to mitigate these data security risks. Understanding potential vulnerabilities and evolving threats allows organizations to develop effective security strategies to address security incidents. This proactive approach ensures secure integration of AI technologies into mobile applications, protecting both user data and proprietary information.

Protecting Sensitive Data in Mobile AI

Data protection is fundamental in AI security, involving measures like encryption and access control to prevent unauthorized data access. Data masking techniques modify sensitive data to prevent unauthorized access while maintaining its usefulness. For instance, a mobile banking app might use data masking to protect user account numbers during transactions. Robust data management practices, including data minimization, are essential to protect sensitive information used in AI model training.

Organizations should avoid using confidential data in training AI models or as inputs to significantly lower the risk of data breaches. Instead, creating anonymized copies of sensitive data for training purposes can help protect user privacy. Controlled disclosure can achieve transparency in AI systems, providing users with necessary details without compromising sensitive information.

Continuous monitoring practices are crucial for maintaining data integrity in AI systems. Compliance with security policies safeguards sensitive information and establishes user trust. Implementing these data protection measures protects sensitive information within mobile AI applications, maintaining user privacy and securing proprietary information.

AI Model Security in Mobile Applications

Training AI models efficiently often demands substantial computational resources, posing a challenge for mobile devices. Integrating AI features can complicate app architecture, requiring careful planning by developers. Ensuring the integrity of learning data throughout the AI lifecycle is critical for preventing security issues. For example, compromised training data may lead to flawed AI model outputs.

Using unverified AI models in software development risks introducing security flaws and vulnerabilities. Adversaries can manipulate AI model outputs, exacerbating security concerns. Insecure AI-generated code increases the attack surface, making models more susceptible to exploitation. Organizations must ensure the security of AI-generated code and keep datasets updated to mitigate these risks.

Regular updates are necessary to maintain the consistency and reliability of AI models amid changing user needs. Developing defensive strategies that encompass traditional and AI-specific security controls is essential for maintaining a robust security posture. Implementing these best practices ensures effective security for AI models in mobile applications, enhancing overall data security.

Counteracting Adversarial Attacks in Mobile AI

Manipulation of AI systems can occur through sophisticated attacks, where input data is subtly modified to confuse the AI. Adversarial AI subtly alters inputs, leading to incorrect predictions. For example, an attacker could slightly alter an image to evade detection by a facial recognition system. Robust model training with high-quality, diverse data helps reduce susceptibility to adversarial manipulation, influencing the AI model’s behavior.

Incorporating adversarial examples during training better equips AI models to recognize and resist attacks. Using ensemble methods by combining different AI models complicates attacks by increasing the difficulty of exploiting common weaknesses. Training models with diverse adversarial examples broaden their exposure, enhancing protection against various potential threats.

Continuous monitoring of AI system behavior allows for the detection of anomalies that may indicate adversarial threats. Real-time adaptive defenses are crucial for countering evolving adversarial attack strategies. Implementing these strategies effectively secures AI systems against adversarial attacks, ensuring the reliability and accuracy of AI-driven decision-making.

Best Practices for Securing AI in Mobile Networks

Securing AI in mobile networks requires a collaborative effort among experts in machine learning, cybersecurity, software engineering, and ethics. AI security focuses on identifying, assessing, and mitigating risks and vulnerabilities. Integrating AI security into the software development life cycle (SDLC) minimizes the risk of introducing security flaws.

The following best practices for securing AI in mobile networks include implementing robust access controls, continuous monitoring, and regular security risk assessments.

Implementing Robust Access Controls

Effective identity verification processes ensure that only authorized users can access sensitive AI system functionalities. Access controls safeguard against unauthorized interactions, ensuring only permitted entities operate within these systems. Multi-factor authentication, for example, enhances security by requiring multiple forms of verification.

Robust identity verification enhances the security posture of AI systems by mitigating unauthorized access risks. Implementing strong access controls, starting with reliable identity verification, is essential for maintaining the integrity and security of AI applications.

Protecting sensitive information and ensuring access for only authorized users significantly improves security practices and security best practices to protect sensitive data and meet security standards. Organizations protect sensitive data effectively through these measures.

Continuous Monitoring and Threat Intelligence

Continuous monitoring of AI models is essential to identify any unusual behavior that may indicate a data poisoning attempt. This provides critical insights that help in timely responses to vulnerabilities and threats. For instance, runtime monitoring can detect and mitigate a potential data poisoning attack before it compromises the AI system.

AI systems improve over time, becoming more effective in identifying threats through continuous learning. Integrating threat intelligence into mobile AI algorithms enhances their effectiveness against emerging threats.

Continuous monitoring and incorporating threat intelligence allow organizations to stay ahead of evolving threats and maintain a strong security posture against threat actors.

Regular Security Risk Assessments

A security risk assessment of AI/ML in mobile telecommunication networks is necessary to understand security measures. Adopting AI/ML technologies in mobile networks requires recognizing the trade-off between benefits and risks and selecting appropriate security controls. Regular security risk assessments help identify vulnerabilities and ensure security measures are effective.

Vulnerability management includes ongoing discovery, prioritization, mitigation, and resolution of security vulnerabilities. Regular AI audits are crucial for identifying vulnerabilities, ensuring compliance with ethical standards, and addressing security gaps. Conducting regular security risk assessments improves security and maintains the integrity of AI systems.

Ensuring Data Integrity in Mobile AI Systems

Data accuracy is crucial in mobile AI applications to prevent severe consequences like unjust bans from services. Manipulation of data in AI systems can lead to flawed outcomes in decision-making, including biased data. For example, data poisoning attacks can manipulate training datasets and compromise AI model performance. Maintaining a secure environment for AI model training is crucial to prevent unauthorized access and data manipulation.

Organizations should monitor performance changes in AI models to maintain reliability. Rigorous data validation and auditing significantly improve security efforts. Robust validation and filtering of input data mitigate risks associated with data poisoning. Ensuring data integrity maintains the accuracy and reliability of AI systems.

Data quality and accuracy should be periodically assessed to ensure ongoing integrity. Processes and tools must fix accuracy issues and validate data collected from reliable sources. Implementing these measures protects AI systems from data manipulation and ensures accurate decision-making.

Regulatory Compliance and Ethical Considerations

Organizations must create internal compliance strategies, including regular legal reviews and audits to ensure adherence to AI regulations. The evolving regulatory landscape of AI necessitates continuous monitoring and adaptation of compliance practices by regulatory bodies. AI governance frameworks guide ethical and legal considerations in AI deployment, establishing policies for accountability and compliance.

Ethical AI practices focus on fairness, transparency, and non-discrimination to prevent biases in AI decision-making. Establishing ethical AI practices guidelines helps organizations align their initiatives with privacy laws and ethical standards. Ethical and privacy issues arise from AI processing large volumes of sensitive data, necessitating careful data management.

Investing in AI security compliance can enhance a company’s reputation and competitive edge by demonstrating a commitment to data protection. Partnering with technology providers that enhance data privacy can help mitigate security risks associated with AI applications. Adhering to regulatory compliance and ethical considerations ensures responsible AI practices and protects user data.

Addressing AI Security Challenges in Mobile Development

Organizations often face challenges in securing AI projects due to the pace of AI innovation exceeding their ability to implement security measures. Enhancing AI security involves integrating security into the software development lifecycle (SDLC), adopting secure coding practices, conducting regular vulnerability assessments, and adhering to established security frameworks.

Automated systems powered by AI can respond to threats instantly, minimizing potential damage to the organization. By integrating security into every stage of AI development, organizations can analyze vast amounts of data to identify vulnerabilities early and implement effective security measures.

This proactive approach ensures that AI technologies are deployed securely, protecting user data and maintaining system integrity.

Enhancing Cybersecurity Operations with AI

AI enhances traditional threat detection in mobile networks by supporting existing methods, identifying new threats, and overcoming the limitations of signature-based detection. AI improves threat-hunting platforms by making them more advanced and efficient, with the ability to analyze large datasets. As attacks driven by AI become increasingly sophisticated, automated intelligence for continuous analysis is crucial to counter this evolving threat landscape.

AI improves traditional vulnerability management systems. It does this by automatically prioritizing vulnerabilities according to their potential impact and likelihood of being exploited. AI has the ability to automate patch management processes. This significantly lowers the risk of exposure to cyber threats. AI streamlines security operations and automates tasks, improving efficiency in response to incidents. By integrating AI into cybersecurity operations, organizations can enhance their overall security posture and respond more effectively to threats.

The integration of AI in security operations allows security analysts to focus on more complex tasks, thereby enhancing their productivity. Implementing AI throughout the development and deployment of AI systems ensures that security measures are embedded within the lifecycle. By leveraging AI technologies, organizations can improve their cybersecurity operations and protect critical infrastructure.

Future Trends in Mobile AI Security

Several emerging technologies are expected to enhance security in mobile AI applications, including blockchain for data integrity and advanced machine learning algorithms for threat detection. The integration of AI with biometrics is anticipated to play a significant role in mobile security by providing robust user authentication. Imagine a mobile device that recognizes you not just by your password, but by your unique biometric signature, ensuring that only you can access your data.

Edge computing is on the rise, allowing data flow processing at the device level, which can minimize data leaks and improve responsiveness in mobile AI applications. Adopting a zero-trust security model is becoming crucial as it ensures strict verification for users and devices accessing AI systems. These advancements will help organizations stay ahead of evolving threats and maintain a strong security posture while also enhancing cloud security.

Implementing regular security audits and risk assessments will help organizations stay ahead of evolving threats in mobile AI environments. Developing AI systems that are capable of self-healing through automated threat responses represents a significant methodology trend.

Future trends will significantly influence how organizations manage security, necessitating the adoption of more proactive and adaptive security measures. By staying abreast of these trends, organizations can effectively secure their mobile AI applications.

Summary

AI security in mobile applications is a multifaceted challenge that requires a proactive and comprehensive approach. By understanding the role of AI in mobile security, identifying key risks, protecting sensitive data, securing AI models, and counteracting adversarial attacks, organizations can significantly enhance their security posture. Implementing best practices, such as robust access controls, continuous monitoring, and regular risk assessments, is essential for maintaining data integrity and compliance with regulatory standards.

Looking ahead, emerging technologies and trends will continue to shape the landscape of mobile AI security. By staying informed and adopting these innovations, organizations can ensure that their AI systems remain secure and resilient against evolving threats. Embracing a proactive and adaptive approach to AI security will not only protect user data but also foster trust and confidence in mobile applications.

AI makes workers more efficient. Trouble is, AI makes criminals more efficient, too.

Thanks to increasingly sophisticated digital tools, bank scams and frauds have become a pervasive threat to consumers and financial institutions alike. From AI-powered deepfakes to elaborate check fraud schemes, criminals are employing a wide array of tactics to separate unsuspecting victims from their hard-earned money.

“Digital services, tied to faster and more efficient payment systems, enable criminals to move stolen money out of the system and across country borders at speed,” says Jason Lane-Sellers, director of Fraud & Identity at LexisNexis Risk Solutions. “This rapid movement makes stopping the flow of funds nearly impossible without proactive detection.

According to Lane-Sellers, a rising volume of scams are targeting U.S. bank customers and the digital financial services that they have come to depend on. As you learn to navigate a complex landscape of financial deception, it’s crucial to understand the latest trends and protect yourself from falling prey to scams.

The rising tide of fraud

Recent data paints a troubling picture of the scale and impact of bank fraud. According to the Federal Trade Commission, consumers reported losing more than $10 billion to fraud in 2023, marking a 14% increase from the previous year. This staggering figure represents the first time fraud losses have reached such a benchmark, and it highlights the growing effectiveness of scammers.

Types of fraud are diverse, but some stand out as particularly prevalent. Investment scams topped the list, accounting for $4.6 billion in losses, followed by imposter scams at $2.7 billion. The banking industry is feeling the impact, with more than a quarter of bank customers experiencing fraudulent activity on their accounts in the past year, according to a study by J.D. Power.

Emerging threats: AI and deepfakes

Artificial intelligence and deepfakes have emerged as significant concerns for the banking sector. In a chilling example from January 2024, an employee at a Hong Kong-based firm was tricked into sending $25 million to fraudsters after participating in a video call with what she believed were her colleagues, including the CFO. In reality, the entire call was a sophisticated deepfake created by scammers.

“Last year we all saw the democratization of AI as a productivity tool, and since then, AI-powered scams now make up nearly half of all fraud attempts,” says Adam Ennamli, chief risk officer at General Bank of Canada. “And the frontier between cyber and fraud is blurrier than ever. We’re seeing everything from deepfake CEOs asking for wire transfers to scammers using cloned voices to fool Bank customer service agents.”

Experts predict that generative AI could enable fraud losses to reach $40 billion in the United States by 2027, growing at a compound annual rate of 32%.

“GenAI allows, for a reduced cost, fraudsters to scale their operations dramatically, creating large volumes of phishing emails and social media profiles that bypass traditional fraud detection systems, thanks to their newfound sophistication and quality,” says Ennamli. “Each message can be perfectly tailored to its target, incorporating personal details scraped from publicly available data, creating compelling social engineering hooks.”

This rapid escalation poses a significant challenge for banks and regulators alike, as existing risk management frameworks may not be adequate to address these emerging threats.

Common scams targeting bank customers

While high-tech frauds grab headlines, many scammers still rely on tried-and-true methods to target bank customers. Some of the most common scams include:

Fake bank fraud warnings. Scammers pose as bank representatives, claiming to investigate suspicious activity on your account.

Scammers pose as bank representatives, claiming to investigate suspicious activity on your account. Check overpayment scams. Victims receive a fake check and are asked to return a portion of the funds before the check bounces.

Victims receive a fake check and are asked to return a portion of the funds before the check bounces. Online lending scams. Fraudsters target those with poor credit, offering easy loans in exchange for sensitive information or upfront fees.

Fraudsters target those with poor credit, offering easy loans in exchange for sensitive information or upfront fees. Imposter scams. Criminals impersonate government officials, tech support workers, or other trusted entities to gain access to bank accounts.

Criminals impersonate government officials, tech support workers, or other trusted entities to gain access to bank accounts. Investment scams. Promising unrealistic returns, these scams often target victims through social media or unsolicited communications.

The human element: Why people fall for scams

Understanding why people fall victim to these scams is crucial for prevention. According to research from YouGov, 61% of victims attribute their vulnerability to data security breaches, while 60% cite a lack of awareness about different types of scams. Other factors include being overly trusting when making purchases (57%) and insufficient safeguarding of personal details (52%).

“Trust serves as the foundation for these scams, as fraudsters build it over time and follow it with an urgent or emotional plea for money,” warns Lane-Sellers.

Romance scams are a prime example of the role that trust plays in making people fall for the trick, says Lane-Sellers. Scammers develop an online relationship with a lonely individual over an extended period. They then invent a heart-wrenching scenario, like a health crisis or an emergency, claiming only the victim can resolve it by instantly sending money, purchasing gift cards or buying airline tickets.

Interestingly, age plays a role in susceptibility to certain types of fraud. While 37% of those aged 65 and older have experienced bank and credit account fraud, only 15% of young adults aged 18-29 report the same. However, younger individuals are more likely to fall victim to employment scams and other frauds involving digital payment platforms.

The role of banks and regulators

Financial institutions and regulatory bodies are working to combat the rising tide of fraud. Banks are investing heavily in AI and other technologies to detect and prevent fraudulent activities. However, the rapid evolution of scam tactics presents an ongoing challenge.

“Banks are actively exploring solutions to the problem, from cutting-edge behavioral analysis to experimenting blockchain verification,” says Ennamli. “But we are constantly playing catch-up with new threat vectors like authorized push payment scams and ownership takeovers—where fraudsters takeover genuine businesses and use them to defraud their suppliers and partners, which often happen to be banks.”

Protecting yourself from bank scams

While banks and regulators play a crucial role in combating fraud, individual vigilance remains the first line of defense.

“Consumers must approach any unexpected and urgent money requests with extreme caution,” says Lane-Sellers. “Take a moment to step away from your phone or computer and question whether the person asking for money is truly who they claim to be or if the offer seems too good to be true.”

Here’s step one: Always verify any offer, deal or urgent request for money through an independent third-party channel. Call the bank directly or consult a friend to get their perspective before taking action. Take the following steps to protect yourself from scams:

Never share personal or financial information in response to unsolicited calls, emails, or texts.

Be wary of requests for immediate action or threats of account closure.

Use strong, unique passwords for all financial accounts and enable two-factor authentication where possible.

Regularly monitor your bank statements and credit reports for suspicious activity.

Be skeptical of investment opportunities that promise unrealistic returns.

Verify the legitimacy of any organization requesting financial information by contacting them through official channels.

Keep your computer and mobile devices updated with the latest security software.

The future of bank fraud

As we look to the future, the landscape of bank fraud is likely to become even more complex. The rise of cryptocurrencies, decentralized finance, and increasingly sophisticated AI tools will present new challenges for both consumers and financial institutions.

However, advancements in technology also offer hope for better fraud detection and prevention. Banks are exploring the use of biometrics, blockchain, and machine learning to enhance security and protect their customers’ assets.

“The latest artificial intelligence and machine learning technology detects hidden behavioral and interaction anomalies, helping to proactively identify high risk situations,” says Lane-Sellers. “Organizations must apply these technologies across the entire customer journey, not just during payment processes or onboarding because fraudsters target every interface and interaction with their scams.”

Ennamli agrees: “AI is certainly part of the problem, but it’s also shaping up to be a key part of the solution—if banks can deploy it effectively. Meaning that it won’t take over the problem for you, it may just help you solve it faster.”

In this ever-evolving battle against financial fraud, education and awareness remain paramount. By staying informed about the latest scams and maintaining a healthy skepticism towards unsolicited financial offers, we can all play a part in protecting our financial well-being.

As we navigate the digital age of banking, remember that vigilance is your best defense against fraud. If something seems too good to be true or raises suspicion, trust your instincts and take the time to verify before taking any action. Your financial security depends on it.