Jun 30 2025

Artificial Intelligence: The Next Battlefield in Cybersecurity

Category: AI,cyber securitydisc7 @ 8:56 am

Artificial Intelligence (AI) stands as a paradox in the cybersecurity landscape. While it empowers attackers with tools to launch faster, more convincing scams, it also offers defenders unmatched capabilities—if used strategically.

1. AI: A Dual-Edged Sword
The post emphasizes AI’s paradox in cybersecurity—it empowers attackers to launch sophisticated assaults while offering defenders potent tools to counteract those very threats

2. Rising Threats from Adversarial AI
AI emerging risks, such as data poisoning and adversarial inputs that can subtly mislead or manipulate AI systems deployed for defense

3. Secure AI Lifecycle Practices
To mitigate these threats, the article recommends implementing security across the entire AI lifecycle—covering design, development, deployment, and continual monitoring

4. Regulatory and Framework Alignment
It points out the importance of adhering to standards like ISO and NIST, as well as upcoming regulations around AI safety, to ensure both compliance and security .

5. Human-AI Synergy
A key insight is blending AI with human oversight/processes, such as threat modeling and red teaming, to maximize AI’s effectiveness while maintaining accountability

6. Continuous Adaptation and Education

Modern social engineering attacks have evolved beyond basic phishing emails. Today, they may come as deepfake videos of executives, convincingly realistic invoices, or well-timed scams exploiting current events or behavioral patterns.

The sophistication of these AI-powered attacks has rendered traditional cybersecurity tools inadequate. Defenders can no longer rely solely on static rules and conventional detection methods.

To stay ahead, organizations must counter AI threats with AI-driven defenses. This means deploying systems that can analyze behavioral patterns, verify identity authenticity, and detect subtle anomalies in real time.

Forward-thinking security teams are embedding AI into critical areas like endpoint protection, authentication, and threat detection. These adaptive systems provide proactive security rather than reactive fixes.

Ultimately, the goal is not to fear AI but to outsmart the adversaries who use it. By mastering and leveraging the same tools, defenders can shift the balance of power.

🧠 Case Study: AI-Generated Deepfake Voice Scam — $35 Million Heist

In 2023, a multinational company in the UK fell victim to a highly sophisticated AI-driven voice cloning attack. Fraudsters used deepfake audio to impersonate the company’s CEO, directing a senior executive to authorize a $35 million transfer to a fake supplier account. The cloned voice was realistic enough to bypass suspicion, especially because the attackers timed the call during a period when the CEO was known to be traveling.

This attack exploited AI-based social engineering and psychological trust cues, bypassing traditional cybersecurity defenses such as spam filters and endpoint protection.

Defense Lesson:
To prevent such attacks, organizations are now adopting AI-enabled voice biometrics, real-time anomaly detection, and multi-factor human-in-the-loop verification for high-value transactions. Some are also training employees to identify subtle behavioral or contextual red flags, even when the source seems authentic.

In early 2023, a multinational company in Hong Kong lost over $25 million after employees were tricked by a deepfake video call featuring AI-generated replicas of senior executives. The attackers used AI to mimic voices and appearances convincingly enough to authorize fraudulent transfers—highlighting how far social engineering has advanced with AI.

Source: [CNN Business, Feb 2024 – “Scammers used deepfake video call to steal millions”]

This example reinforces the urgency of integrating AI into threat detection and identity verification systems, showing how traditional security tools are no longer sufficient against such deception.

AI and The Future of Cybersecurity: Navigating the New Digital Battlefield

“Whether you’re a technology professional, policymaker, academic, or simply a curious reader, this book will arm you with the knowledge to navigate the complex intersection of AI, security, and society.”

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Tags: AI and Security, artificial intelligence, Digital Battlefield, Digital Ethics, Ethical Frontier


May 15 2025

From Oversight to Override: Enforcing AI Safety Through Infrastructure

Category: AI,Information Securitydisc7 @ 9:57 am

You can’t have AI without an IA

As AI systems become increasingly integrated into critical sectors such as finance, healthcare, and defense, their unpredictable and opaque behavior introduces significant risks to society. Traditional safety protocols may not be sufficient to manage the potential threats posed by highly advanced AI, especially those capable of causing existential harm. To address this, researchers propose Guillotine, a hypervisor-based architecture designed to securely sandbox powerful AI models.

Guillotine leverages established virtualization techniques but also introduces fundamentally new isolation strategies tailored for AI with existential-risk potential. Unlike typical software, such AI may attempt to analyze and subvert the very systems meant to contain them. This requires a deep co-design of hypervisor software with the underlying hardware—CPU, memory, network interfaces, and storage—to prevent side-channel leaks and eliminate avenues for reflective exploitation.

Beyond technical isolation, Guillotine incorporates physical fail-safes inspired by systems in nuclear power plants and aviation. These include hardware-level disconnection mechanisms and even radical approaches like data center flooding to forcibly shut down or destroy rogue AI. These physical controls offer a final layer of defense should digital barriers fail.

The underlying concern is that many current AI safety frameworks rely on policy rather than technical enforcement. As AI becomes more capable, it may learn to bypass or manipulate these soft controls. Guillotine directly confronts this problem by embedding enforcement into the architecture itself—creating systems that can’t be talked out of enforcing the rules.

In essence, Guillotine represents a shift from trust-based AI safety toward hardened, tamper-resistant infrastructure. It acknowledges that if AI is to be trusted with mission-critical roles—or if it poses existential threats—we must engineer control systems with the same rigor and physical safeguards used in other high-risk industries.

 Guillotine: Hypervisors for Isolating Malicious AIs.

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Tags: AIMS, AISafety, artificial intelligence, Enforcing AI Safety, GuillotineAI, information architecture, ISO 42001


Sep 03 2024

AI Risk Management

Category: AI,Risk Assessmentdisc7 @ 8:56 am

The IBM blog on AI risk management discusses how organizations can identify, mitigate, and address potential risks associated with AI technologies. AI risk management is a subset of AI governance, focusing specifically on preventing and addressing threats to AI systems. The blog outlines various types of risks—such as data, model, operational, and ethical/legal risks—and emphasizes the importance of frameworks like the NIST AI Risk Management Framework to ensure ethical, secure, and reliable AI deployment. Effective AI risk management enhances security, decision-making, regulatory compliance, and trust in AI systems.

AI risk management can help close this gap and empower organizations to harness AI systems’ full potential without compromising AI ethics or security.

Understanding the risks associated with AI systems

Like other types of security risk, AI risk can be understood as a measure of how likely a potential AI-related threat is to affect an organization and how much damage that threat would do.

While each AI model and use case is different, the risks of AI generally fall into four buckets:

  • Data risks
  • Model risks
  • Operational risks
  • Ethical and legal risks

The NIST AI Risk Management Framework (AI RMF) 

In January 2023, the National Institute of Standards and Technology (NIST) published the AI Risk Management Framework (AI RMF) to provide a structured approach to managing AI risks. The NIST AI RMF has since become a benchmark for AI risk management.

The AI RMF’s primary goal is to help organizations design, develop, deploy and use AI systems in a way that effectively manages risks and promotes trustworthy, responsible AI practices.

Developed in collaboration with the public and private sectors, the AI RMF is entirely voluntary and applicable across any company, industry or geography.

The framework is divided into two parts. Part 1 offers an overview of the risks and characteristics of trustworthy AI systems. Part 2, the AI RMF Core, outlines four functions to help organizations address AI system risks:

  • Govern: Creating an organizational culture of AI risk management
  • Map: Framing AI risks in specific business contexts
  • Measure: Analyzing and assessing AI risks
  • Manage: Addressing mapped and measured risks

For more details, visit the full article here.

Predictive analytics for cyber risks

Predictive analytics offers significant benefits in cybersecurity by allowing organizations to foresee and mitigate potential threats before they occur. Using methods such as statistical analysis, machine learning, and behavioral analysis, predictive analytics can identify future risks and vulnerabilities. While challenges like data quality, model complexity, and evolving threats exist, employing best practices and suitable tools can improve its effectiveness in detecting cyber threats and managing risks. As cyber threats evolve, predictive analytics will be vital in proactively managing risks and protecting organizational information assets.

Trust Me: ISO 42001 AI Management System is the first book about the most important global AI management system standard: ISO 42001. The ISO 42001 standard is groundbreaking. It will have more impact than ISO 9001 as autonomous AI decision making becomes more prevalent.

Why Is AI Important?

AI autonomous decision making is all around us. It is in places we take for granted such as Siri or Alexa. AI is transforming how we live and work. It becomes critical we understand and trust this prevalent technology:

“Artificial intelligence systems have become increasingly prevalent in everyday life and enterprise settings, and they’re now often being used to support human decision making. These systems have grown increasingly complex and efficient, and AI holds the promise of uncovering valuable insights across a wide range of applications. But broad adoption of AI systems will require humans to trust their output.” (Trustworthy AI, IBM website, 2024)


Trust Me – ISO 42001 AI Management System

Enhance your AI (artificial intelligence) initiatives with ISO 42001 and empower your organization to innovate while upholding governance standards.

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Tags: AI Governance, AI Risk Management, artificial intelligence, security risk management


Jul 17 2023

CISOs under pressure: Protecting sensitive information in the age of high employee turnover

Category: CISO,data securitydisc7 @ 10:29 am

In this Help Net Security interview, Charles Brooks, Adjunct Professor at Georgetown University’s Applied Intelligence Program and graduate Cybersecurity Programs, talks about how zero trust principles, identity access management, and managed security services are crucial for effective cybersecurity, and how implementation of new technologies like AI, machine learning, and tracking tools can enhance supply chain security.

CISOs believe they have adequate data protection measures, yet many have dealt with the loss of sensitive data over the past year. How do you reconcile this apparent contradiction?

The loss of data despite protection measures is not that surprising. We are all playing catchup in cybersecurity. The internet was invented in a government laboratory and later commercialized in the private sector. The hardware, software, and networks were originally designed for open communication. Cybersecurity initially was not a major consideration. That mindset has surely changed due to the explosion of connectivity and commerce on the internet and CISOs are playing a big game of catch up too.

There are a multitude of causes that can account for the exfiltration of sensitive data. The first being that hacker adversaries have become more sophisticated and capable of breaching. The basic tools and tactics hackers use for exploitation include malware, social engineering, phishing (the easiest most common, especially spear-phishing aimed at corporate executives), ransomware, insider threats, and DDOS attacks. Also, they often use advanced and automated hacking tools shared on the dark web, including AI and ML tools that are used to attack and explore victims’ networks. That evolving chest of hacker weaponry is not so easy for CISOs to defend against.

Another big factor is the reality is that exponential digital connectivity propelled by the COVID-19 pandemic has changed the security paradigm. Many employees now work from hybrid and remote offices. There is more attack surface area to protect with less visibility and controls in place for the CISO. Therefore, it is logical to conclude that more sensitive data has and will be exposed to hackers.

The notion of adequate protection is a misnomer as threats are constantly morphing. All it takes is one crafty phish, a misconfiguration, or a failure to do a timely patch for a gap to provide an opportunity for a breach. Finally, many CISOs have had to operate with limited budgets and qualified cyber personnel. Perhaps they have lower expectations of the level of security they can achieve under the circumstances.

As the economic downturn pressures security budgets, how can CISOs optimize their resources to manage cybersecurity risks effectively?

CISOs must enact a prudent risk management strategy according to their industry and size that they can follow to allow them to best optimize resources. A good risk management strategy will devise a vulnerability framework that Identifies digital assets and data to be protected. A risk assessment can quickly identify and prioritize cyber vulnerabilities so that you can immediately deploy solutions to protect critical assets from malicious cyber actors while immediately improving overall operational cybersecurity. This includes protecting and backing up business enterprise systems such as: financial systems, email exchange servers, HR, and procurement systems with new security tools (encryption, threat intel & detection, firewalls, etc.) and policies.

There are measures in a vulnerability framework that are not cost prohibitive. Those measures can include mandating strong passwords for employees and requiring multi-factor authentication. Firewalls can be set up and CISOs can make plans to segment their most sensitive data. Encryption software can also be affordable. The use of the cloud and hybrid clouds enables implementation of dynamic policies, faster encryption, drives down costs, and provides more transparency for access control (reducing insider threats). A good cloud provider can provide some of those security controls for a reasonable cost. Clouds are not inherently risky, but CISOs and companies will need to recognize that they must thoroughly evaluate provider policies and capabilities to protect their vital data.

And if a CISO is responsible for protecting a small or medium business without a deep IT and cybersecurity team below them, and are wary of cloud costs and management, they can also consider outside managed security services.

How can organizations better safeguard their sensitive information during high employee turnover?

This goes to the essence of the strategy of zero trust. Zero trust (ZT) is the term for an evolving set of cybersecurity paradigms that move defenses from static, network-based perimeters to focus on users, assets, and resources. Organizations need to know everything that is connected to the network, devices & people.

Identity access management or IAM, is very important. IAM the label used for the set of technologies and policies that control who accesses what resources inside a system. A CISO must determine and know who has access to what data and why. If an employee leaves, they need to immediately revoke privileges and ensure that nothing sensitive was removed from the organization. There are many good IAM tools available from vendors on the market.

Certainly, with employee turnover, there are ethical and trust elements involved. Employee insider threats are difficult to detect and manage. Some of that can be addressed upfront in employment contracts with an employee understanding of the legal parameters involved, it is less likely that they will run off with sensitive data.

We’ve seen increased CISO burnout and concerns about personal liability.

Yes, the burnout is a direct result of CISOs having too many responsibilities, too little budget, and too few workers to run operations and help mitigate growing cyber-threats. Now the personal liability factors exemplified by as the class action suit against Solar’s Wind’s CISO, and the suit against Uber’s CISO for obscuring ransomware payments, has heightened the risk. In an industry that is already lacking in required numbers of cybersecurity leaders and technicians, CISOs need to be given not only the tools, but the protections necessary for them to excel in their roles. If not, the burnout and liability issues will put more companies and organizations at greater risk.

How are these challenges impacting the overall efficacy of CISOs in their roles, and what measures can be taken to address them?

Despite the trends of greater frequency, sophistication, lethality, and liabilities associated with incursions, industry management has been mostly unprepared and slow to act at becoming more cyber secure. A Gartner survey found that 88% of Boards of Directors (BoDs) view cybersecurity as a business risk, as opposed to a technology risk, according to a new survey, and that only 12% of BoDs have a dedicated board-level cybersecurity committee.

“It’s time for executives outside of IT to take responsibility for securing the enterprise,” said Paul Proctor, Chief of Research for Risk and Security. “The influx of ransomware and supply chain attacks seen throughout 2021, many of which targeted operation- and mission-critical environments, should be a wake-up call that security is a business issue, and not just another problem for IT to solve.”

CISOs not only need a seat at the table in the C-Suite, but they also need insurance protections comparable to other executive management that limits their personal liability. There is no panacea for perfect cybersecurity. Breaches can happen to any company or person in our precarious digital landscape. It is not fair or good business to have CISO go at it alone. In a similar context, cybersecurity should no longer be viewed as a cost item for businesses or organizations. It has become an ROI that can ensure continuity of operations and protect reputation. Investment in both the company and the CISO’s compensation and portfolio of required duties need to be a priority going forward.

As supply chain risk continues to be a recurring priority, how can CISOs better manage this aspect of their cybersecurity strategies, especially under constrained budgets?

Ensuring that the supply chain is not breached including the design, manufacturing, production, distribution, installation, operation, and maintenance elements is a challenge to all companies. Cyber-attackers will always look for the weakest point of entry and mitigating third-party risk is critical for cybersecurity. Supply chain cyber-attacks can be perpetrated from nation-state adversaries, espionage operators, criminals, or hacktivists.

CISOs require visibility of all vendors in the supply chain along with set policies and monitoring. NIST, a non-regulatory agency of the US Department of Commerce has a suggested framework for supply chain security that provides sound guidelines from both government and industry.

NIST recommends:

  • Identify, establish, and assess cyber supply chain risk management processes and gain stakeholder agreement
  • Identify, prioritize, and assess suppliers and third-party supplier partners
  • Develop contracts with suppliers and third-party partners to address your organization’s supply chain risk management goals
  • Routinely assess suppliers and third-party partners using audits, test results, and other forms of evaluation
  • Complete testing to ensure suppliers and third-party providers are able to respond to and recover from service disruption

Other mitigation efforts can be done with the acquisition of new technologies that monitor, alert, and analyze activities in the supply chain. Artificial intelligence and machine learning tools can provide visibility and predictive analytics, and stenographic and watermark technologies can provide tracking of products and software.

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Tags: artificial intelligence, Chief Information Security Officer, CISO, Protecting sensitive information, security ROI, supply chain attacks