Cybersecurity expert Chuck Brooks discusses the top five issues in threat detection and how organizations can reduce the risk of cyber-attacks in 2024.
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Interview by Brian Kelly
I recently sat down with Chuck Brooks, President of Brooks Consulting International, who is a globally recognized thought leader and subject matter expert in the areas of Cybersecurity and Emerging Technologies. We discussed the top five challenges and solutions in threat detection today, and how knowing how to safeguard against them can help organizations mitigate the impact of cyber-attacks.
Brian Kelly: How do threat detection systems like DDoS Protection work?
Chuck Brooks: A distributed denial-of-service (DDoS) attack is an attack in which multiple compromised computer systems attack a target and cause a denial of service. The flood of incoming messages, connection requests, or malformed packets to the target system forces it to slow down or even crash and shut down, thereby denying service to legitimate users or systems. These attacks are often orchestrated via bots.
A bot defense needs to be able to quickly find data that looks like it came from a known botnet or piece of malware. It also needs to rapidly spot actions that can only be done by software, like getting a lot of requests. Especially if the traffic behaved in a way that wasn't natural, like mouse movements, keystrokes, or visitation trends that weren't normal. An all-around bot defense should also be able to tell if traffic tried to directly access the application interface (API) when it wasn't supposed to or if it tried to stop the signal collection from happening.
Brian Kelly: How is the role of Artificial Intelligence (AI) impacting the cybersecurity space?
Chuck Brooks: AI is a powerful tool for enabling cybersecurity. By prioritizing and acting on data, AI and machine learning (ML) can help make decisions more efficiently. This is especially true for larger, more sophisticated networks with many users and variables.
AI and ML can increase the speed at which new attacks are discovered, draw statistical conclusions, and send that information to endpoint protection systems. You can get real-time data on deviations and other problems using network monitoring and horizon scanning. Continuous diagnostics and forensics analysis are possible for optimal protection, and the defense framework layers (firewalls, payload, endpoint, network, and antivirus) are updated automatically.
Prioritizing and acting on data using AI algorithms can help people make better choices, especially in bigger networks with many users and variables. Locating, sorting, and combining data is a capability for reducing online threats. As a result, predictive analytics can conclude from statistics with fewer resources and send this information to endpoint security platforms.
Generative AI technology can also help write secure code more quickly. Better AI tools, platforms, and technologies can aid writers in composing safer code from the start. This also makes it easier to fix problems as they happen.
AI can also monitor aberrations happening in the network, find new threats without clear signs, and take the right action. In addition, it can be used to connect data from different silos to figure out the types of attacks that are happening and to analyze network risks and weaknesses. As a key part of zero trust cybersecurity, identity, and access management may benefit from AI that checks the validity of data across many distributed systems.
AI can spot things that aren't normal or don’t follow the rules. It can do this by looking at data and files and seeing network activities in real-time to find unapproved connections, unwanted communication attempts, strange or malicious password use, brute force login attempts, strange data transfer, and data exfiltration. Further, AI could significantly change cybersecurity efficiency by automating and orchestrating security. Combining ML and advanced analytics, AI can automate and coordinate many security tasks, such as incident reaction and vulnerability management.
When it comes to adapting to new, sophisticated digital environments, AI and ML become key tools or innovative chess pieces in a cybersecurity strategy game. It will depend on the accuracy, speed, and quality of the algorithms and supporting technologies to stay safe against growing asymmetrical threats.
Also, because there just aren't enough skilled cybersecurity workers, AI can fulfill security tasks that would have been done by adding people in the past. That is a significant benefit.
Brian Kelly: Are there security challenges inherent in using cloud computing?
Chuck Brooks: Both the public and private sectors are quickly moving to cloud and hybrid cloud settings, which is bringing computing closer to the edge. More businesses and government bodies are storing their data in the cloud or a hybrid cloud setup.
The cloud will handle more than 90% of all data handling tasks, according to predictions. Setting up a secure cloud is an important part of protection. As cloud-based services become more common, cybersecurity issues have grown. Issues that businesses must deal with include cloud settings that aren't set up correctly, APIs that aren't safe, and data breaches caused by cloud vulnerabilities.
Rapid migration to the cloud raises new security concerns due to the complicated systems that need to be kept up to date and protected from zero-day threats. Thus, integration should be the main security focus for mixed cloud setups. Achieving integration requires being able to see everything in the environment, including public, private, and on-premises areas. It also requires having the right tools, rules and, in many cases, a managed services partner to make sure that all security standards are met.
Brian Kelly: What are some effective strategies for securing IoT (Internet of Things) devices?
Chuck Brooks: Securing IoT devices is a monumental challenge. The IoT, of course, refers to the emerging connectivity of embedded devices to the internet that are readable, recognizable, locatable, addressable, and/or controllable. That is a big universe of devices. The most at-risk electronics are networked cameras and storage devices, smartphones and tablets, laptops, computers and streaming video devices.
Hackers can potentially obtain data through any IoT-connected device. Many are particularly open to attack, as most of these devices have not had their default passwords changed. People just use them without changing the default passwords, which is an invitation to a data breach. An organization implementing an IoT security framework needs to immediately address how to change the default passwords on purchased, manufactured devices.
There are solutions ranging from homegrown to expert managed service providers with all-in-one solutions for IoT security. They include improving situational awareness, enforcing security policies for technology integration, threat information sharing, and having a cyber resilience strategy are all important parts of a good IoT risk management plan. For example, it should investigate how separating or segmenting IoT devices can lower risk and attack areas. To reach the end goal, solutions and services must be optimized, and the necessary amount of security must be determined.
Brian Kelly: Can you discuss strategies for managing supply chain cybersecurity risks?
Chuck Brooks: Cyber-attackers are always looking for the weakest link in the chain, and reducing the risk of third parties in supply lines is now seen as necessary for cybersecurity. Cyberattacks on supply lines can come from hackers, spies, thieves, or enemies of the country. Most of the time, this is done by breaking into networks with fake or hacked hardware and software, using providers' weak security measures, or using insider threats.
New technologies, like AI and blockchain, are now being used to keep track of, alert, and evaluate supply chain processes. To protect against cyber-threats, you can use Data Loss Prevention (DLP), encryption, log management, identity, access control tools, and SIEM (Security Information and Event Management) platforms. Another specific step companies can take is to audit the security measures that their suppliers and vendors use to ensure that the end-to-end supply chain is secure. The Department of Homeland Security (DHS), the Department of Defense (DOD), and the White House have all recently implemented supply chain security measures. The Department of Commerce’s NIST (National Institute of Standards and Technology) has suggested a practical one for supply chain security that provides sound guidelines from both government and industry. Brian Kelly: Thanks for your time and your insights today, Chuck.
Chuck Brooks: Thanks Brian, I enjoyed our discussion.
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My new book: Inside Cyber: How AI, 5G, and Quantum Computing Will Transform Privacy and Our Security 1st Edition
Now available for pre-order on Amazon !
by Chuck Brooks
* Discover how to navigate the intersection of tech, cybersecurity, and commerce
In an era where technological innovation evolves at an exponential rate, Inside Cyber: How AI, 5G, and Quantum Computing Will Transform Privacy and Our Security by Chuck Brooks emerges as a critical roadmap for understanding and leveraging the next wave of tech advancements. Brooks, a renowned executive and consultant, breaks down complex technological trends into digestible insights, offering a deep dive into how emerging technologies will shape the future of industry and society.
In the book, you’ll:
* Gain clear, accessible explanations of cutting-edge technologies such as AI, blockchain, and quantum computing, and their impact on the business world
* Learn how to navigate the cybersecurity landscape, safeguarding your business against the vulnerabilities introduced by rapid technological progress
* Uncover the opportunities that technological advancements present for disrupting traditional industries and creating new value
Perfect for entrepreneurs, executives, technology professionals, and anyone interested in the intersection of tech and business, Inside Cyber equips you with the knowledge to lead in the digital age. Embrace the future confidently with this indispensable guide.
Order here: Amazon.com: Inside Cyber: How AI, 5G, and Quantum Computing Will Transform Privacy and Our Security: 9781394254941: Brooks, Chuck: Books
The Race for Quantum Cybersecurity
by Chuck Brooks
You can access the full magazine here: https://thecyberexpress.com/supply-chain-security-editon/
Supercharging DevOps with AI: The Ultimate Technology Dream Team
AI and DevOps: A Symbiotic Relationship In today’s fast-moving world, creating and updating computer programs quickly is super important for businesses. That’s where DevOps and Artificial Intelligence (AI) come in handy. DevOps is like a team strategy that helps computer programmers and operation folks work better together so they can make software faster and keep them running smoothly. And AI? Think of AI as a really smart helper that can learn and make decisions to take on heavy-duty tasks without much human help.When you mix DevOps and AI, it’s like creating a superhero team for technology. AI can help DevOps by spotting problems before they happen, which means fewer headaches and less downtime for the software. Also, with AI’s help, DevOps teams can manage many different tasks at the same time and make smarter decisions, super fast.For example, AI can look at lots of data to find patterns that might show when something’s about to go wrong. It’s like having a super sense that can smell a problem a mile away! This means that companies can fix issues before they become big dramas, keeping their software running like a dream.Plus, with AI’s ability to learn and adapt, it can help teams become better and more efficient over time. It takes notes on what works best and helps the team get even faster at building and fixing software. It’s always getting smarter and helping the DevOps team do their best work.For those who are interested in how smart technology can make software development zippier and more reliable, have a look at this deep dive into the collaboration between AI and DevOps over here: www.getambassador.io/blog/ai-devops-symbiotic-relationship-deep-dive.For more information on how your organization can accelerate your code modernization, check out the following whitepaper from Copper River at copperrivermc.com/devops/But what if you need some extra help getting started with this power duo of AI and DevOps? That’s where Diversified Outlook Group comes into play. They understand how important it is for businesses to keep up with tech trends and can guide you through the process. Their experts are ready to support you in harnessing the power of AI to boost your DevOps efforts. Reach out to them at support@diversifiedoutlookgroup.com to see how they can help your organization thrive
"The advent of artificial intelligence has many aspects to consider including ethics, regulations, and its many types of applications." ...
Source: BIZCATALYST 360° Artificial Intelligence And Security – Collective Thoughts (bizcatalyst360.com)
Artificial Intelligence and Security – Collective Thoughts
BY Chuck Brooks
I teach a course at Georgetown University’s Cybersecurity Risk Management Program called Disruptive Technologies and Organizational Management. I gain from the give-and-take of my student’s insights. As we are now at the onset of an exponential era of technological growth amplified by artificial intelligence in almost every way and industry vertical.
Regarding cyber risk management, artificial intelligence is a powerful enabler and accelerator for cybersecurity in our networked world. AI systems are designed to mimic human characteristics and computational abilities in a computer, enabling them to outperform humans in terms of speed and capacity. AI machine learning provides the quickest way to identify new attacks, draw statistical inferences, and provide that information to endpoint protection systems in the context of cybersecurity.
The advent of artificial intelligence has many aspects to consider including ethics, regulations, and its many types of applications. I asked several of my students to share their insights which are featured below.
Student Insights:
- How can safeguards be put on AI to ensure ethics, effective governance, and mitigate bias, and poisoned data?
Safeguarding AI: Ethics, Governance, and Mitigating Risks
Artificial intelligence (AI) offers immense transformative potential, but its unchecked development poses significant risks. Robust safeguards are essential to realize the benefits of AI while minimizing potential harm. Here is how we can approach this multifaceted challenge:
Ethical Frameworks: Industry-wide standards around fairness, transparency, accountability, and non-discrimination are a must. These principles should guide AI design, development, and deployment, ensuring alignment with societal values.
Governance Structures: Independent review boards, bias audits, and accountability can minimize risks. Regulations at the governmental level are also needed to define acceptable uses of AI, enforce standards, and protect individual rights.
Continuous Bias Evaluation: AI systems often learn from real-world data, which can carry deeply ingrained societal biases. Mitigating this requires an initial evaluation, continuous bias auditing, and techniques such as de-biasing algorithms to help train models to be less prone to discriminatory outcomes.
Protection Against Poisoned Data: AI can be manipulated through data poisoning attacks, where bad actors subtly alter training data. Data validation, exposing models to poisoned data sets, and understanding how AI reaches its decision can enhance security.
The Path Forward Collaboration between technology professionals, ethicists, policymakers, and the public is vital to ensuring that AI develops in a way that benefits society as a whole.
By Joshua Cushing https://www.linkedin.com/in/joshuacushing/
- What needs to be in a Risk Management Framework to address the cyber threat of AI?
There needs to be several key components in a Risk Management Framework (RMF) to effectively address the cybersecurity threat of Artificial Intelligence (AI). It should start by identifying risks such as data manipulation, model theft, and malicious attacks. The framework must conduct a risk assessment to assess the probability and impact of these risks focusing on AI’s features like algorithm transparency. In addition, incorporating threat intelligence tailored for AI is crucial for predicting and mitigating threats. The framework should also enforce security measures including encrypting data and limiting access along with security checks to prevent attacks targeting AI systems. Having a response plan specifically designed for AI related breaches will ensure a timely response and containment. Adhering to data protection laws and understanding the ramifications of using AI are equally important. Finally, ongoing training for employees on AI risks in the RMF will help strengthen defenses against evolving AI technologies.
Leonard Field
- How will AI impact cyber threats and cyber defenses? (i.e. using Generative AI and predictive analytics)
Artificial Intelligence will have a significant impact on the safety of society from a physical and cyber security perspective. AI will greatly impact the capability of threat detection mechanisms as well as cyber defensive countermeasures through its use of Generative AI and predictive analytics. The use of Generative AI will allow cyber analysts to rapidly detect and respond to anomalies in their systems due AI ability not only analyze changes in a baseline, but continuously evolve as the landscape changes. Predictive analytics will be able to assist in this effort by being able to collect and succinctly digest large datasets and identify trends, risks, and patterns that will help analysts in being proactive with the implementation of safeguards that both prevent and deter threat actors. While capabilities will exist for defensive efforts, there must be an equal understanding that malicious actors will also have this same capability. Threat agents will use AI in reconnaissance efforts to find vulnerabilities in systems and understand how defensive measures respond to specific intrusion attempts. The cyber security industry as well as cyber security professionals must continuously analyze and develop tools within the AI space that increase in capacity and capability to mimic the ever-changing landscape.
By Shelley White III www.linkedin.com/in/shelley-white-56a6001a2
- What is Artificial Intelligence Bias?
Regardless of one’s place of origin, inherent bias exists. Bias is not innate but taught. Bias can exist in the forms of race, religion, language, age, culture, or location. Therefore, AI Domain Team members tasked with labeling AI training data or designing AI algorithms for models must come from diverse backgrounds. Artificial Intelligence bias can be implemented purposely or without malice. The outcome of both is an unethical AI model.
By Darryl W. Hicks
- ·How AI will transform the agriculture sector?
The integration of AI and the Internet of Things (IoT) is poised to revolutionize the agriculture sector, offering unprecedented opportunities to enhance efficiency, productivity, and sustainability. Leveraging IoT-enabled monitoring systems, AI algorithms provide farmers with real-time insights into soil conditions, moisture levels, and crop health, enabling data-driven decisions on irrigation, fertilization, and pest control for optimized resource usage and improved yields. Additionally, IoT-equipped wearable sensors and smart collars offer smart livestock management solutions, monitoring the health, behavior, and feeding patterns of animals to detect early signs of illness and enhance animal welfare. Through IoT-based management systems, the entire agricultural supply chain can be streamlined, with AI analytics tracking storage conditions, transportation routes, and product quality to reduce waste and ensure the freshness and safety of agricultural products from farm to market.
Furthermore, AI-driven control systems automate farming operations by leveraging IoT data to regulate irrigation, nutrient management, and crop spraying, while unmanned machinery like drones and robotic tractors perform precision tasks with minimal human intervention, increasing operational efficiency and reducing labor costs. Moreover, UAVs equipped with IoT sensors and AI algorithms monitor crops from above, identifying signs of disease, nutrient deficiencies, and pest infestations to provide actionable insights for targeted interventions, thereby improving crop health and maximizing yields. However, alongside these transformative benefits, the integration of AI and IoT in agriculture presents cybersecurity challenges that must be addressed to ensure the safe and secure adoption of these technologies.
Privacy concerns arise due to the passive nature of IoT data collection, necessitating robust encryption and access controls to safeguard sensitive agricultural data and prevent unauthorized access. Additionally, cybersecurity threats such as ransomware, denial of service (DoS) attacks, and social engineering exploits pose risks to IoT devices in smart farming, highlighting the need for AI-powered cybersecurity solutions to detect and mitigate these threats in real-time. Moreover, supply chain vulnerabilities must be addressed through the implementation of security measures such as blockchain technology and authentication mechanisms to protect against cyber-attacks and data breaches. In conclusion, while AI-driven IoT applications hold immense promise for transforming agriculture, addressing cybersecurity concerns is imperative to ensure their safe and secure adoption in smart farming practices.
References
Barreto, L., & Amaral, A. (2018, September). Smart farming: Cyber security challenges. In 2018 International Conference on Intelligent Systems (IS) (pp. 870-876). IEEE.
Kim, W. S., Lee, W. S., & Kim, Y. J. (2020). A review of the applications of the internet of things (IoT) for agricultural automation. Journal of Biosystems Engineering, 45, 385-400.
Kumar, N., Dahiya, A. K., Kumar, K., & Tanwar, S. (2021, September). Application of IoT in agriculture. In 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) (pp. 1-4). IEEE.
Tao, W., Zhao, L., Wang, G., & Liang, R. (2021). Review of the internet of things communication technologies in smart agriculture and challenges. Computers and Electronics in Agriculture, 189, 106352
By Shavinyaa Vijaykumarr linkedin.com/in/shavinyaa-vijaykumarr-3314922a9
- How will AI transform industries such as healthcare, finance, commerce, transportation, agriculture, space, robotics, and energy?
Artificial Intelligence has the potential to introduce essential contributions to the healthcare sector. This includes administrative processes, such as adherence to compliance standards as well as automation in tasks such as diagnosis and treatment.
By Emanuel Dos Santos https://www.linkedin.com/in/emanuel-dos-santos-506b1b275/
- How can safeguards be put on AI to ensure ethics, effective governance, and mitigate bias, and poisoned data?
Ensuring the safety of artificial intelligence (AI) necessitates a comprehensive strategy, which notably involves government regulation and adherence to industry best practices. The European Parliament’s adoption of the AI Act (AIA) underscores the significant role of external oversight in protecting fundamental rights and addressing ethical advancements in AI (Gasser, 2023). Given the crucial aspects of safeguarding information systems by ensuring confidentiality, integrity, and availability, it is imperative for AI to be trustworthy. This entails being valid and reliable, safe and secure, resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with managed harmful bias (Tabassi, 2023, p. 12). To achieve these characteristics, the AI model must undergo training, receive feedback on ethical dilemmas, and be supervised and rewarded for accurately distinguishing between different types of fairness and implementing them.
References
Gasser, U. (2023). An EU landmark for AI governance. Science, 380(6651), 1203. https://doi.org/10.1126/science.adj1627
Tabassi, E. (2023). Artificial Intelligence Risk Management Framework
(AI RMF 1.0). https://doi.org/10.6028/nist.ai.100-1
By Reginald Kiryowa
- What key elements are necessary to make a framework effective?
The critical aspect of any framework is stakeholder buy-in. A well-thought-out framework backed by solid data and research has a higher chance of success, but even the most well-crafted plan will fail if the people involved do not believe in it. To achieve this, leaders must maintain open communication throughout the implementation process and address any issues that may arise to ensure that stakeholders remain engaged and invested in the plan’s success.
By Hunter Patterson www.linkedin.com/in/hunter-patterson-2315641ba
4 Practical Ways for Businesses to Manage Cyber Risk
by Chuck Brooks
Link: 4 Practical Ways for Businesses to Manage Cyber Risk in 2024 (forbes.com)
Cyberattacks are becoming more common in the digital ecosystems we utilize for both personal and professional reasons. In the past year alone, hundreds of millions of private records from banks, ISPs, and retail establishments have been made available to the public.
The Covid pandemic's impact on work habits may be partly to blame for this rise in violations. The previous few years have seen a sharp shift in work to remote and hybrid workplaces. The evidence indicates that hackers took advantage of the gaps and vulnerabilities in the company's security after accepting this adjustment. The last two years have surpassed all prior records in terms of data lost due to breaches and the sheer volume of cyberattacks on people, corporations, and governments.
Businesses and governments are starting to grasp the seriousness and complexity of these cyber threats. Some of the biggest concerns are ransomware attacks, data breaches, DDoS attacks, misconfiguration, and major IT failures.
The recent wave of major industrial and government cyberattacks serves as an example of the growing threat. The usage of cutting-edge technologies like 5G, AI, and machine learning, as well as growing tactical cooperation among hacker organizations, poses new risks due to their increasingly sophisticated threats.
The reactive mindset has changed as a result of a series of wake-up calls, including significant intrusions by highly skilled threat actors against multiple high-profile targets (including Solar Winds, Colonial Pipeline, OPM, Anthem, Yahoo, and many more). These revelations have exposed a flawed approach to data defense and operating with passive preparedness.
For businesses, there are four basic ways to manage cyber risk in a growing digital threat environment. They include being 1) proactive in security, 2) continuously testing software code and applications, 3) having a risk management and resilience plan, and 4) preparing for the new landscape of emerging technologies.
The Need for Businesses to be Proactive in Security
Being proactive in the ever-evolving digital landscape means doing more than just hiring people and buying new equipment. Creating a cybersecurity framework is also essential since specific circumstances could necessitate the use of biometrics, analytics, encryption, authentication, tactical measures, and ongoing diagnostics and mitigation. Proactive cybersecurity helps to ensure business continuity, to put it briefly.
To maintain continuous business operations, risk assessment and incident handling are the main components of effective methods for minimizing the consequences of cyberattacks. It's critical to keep up with changes in the dangerous landscape and to be ready for anything that might happen. A risk management strategy needs to give top priority to situational awareness assessment, information sharing, and resilience planning.
A proactive cybersecurity commitment requires the completion of a cyber vulnerability risk assessment. This action item is one of the most crucial first steps in cybersecurity best practices. A risk assessment can help you improve overall operational cybersecurity and quickly deploy solutions to protect critical assets from malicious cyber attackers by quickly identifying and prioritizing cyber vulnerabilities.
A comprehensive risk management plan should include cyber-hygiene best practices, instruction, and training; use policies and permissions; network access configuration; code and application testing; device management; application limits; and regular network audits.
A security strategy's specifics can vary based on the circumstances, but the threads that hold it all together are situational awareness and meticulous communication skills for critical communications in an emergency. The United States government and businesses adhere to the National Institute of Standards and Technology's (NIST) slogan, which is "Identify, Protect, Detect, Respond, Recover."
The Importance of Testing Software Code and Applications
Software code testing is a crucial part of information technology product validation. If the testing process is not followed, the final product may include flaws that put a business or organization in danger. One way to ensure the ultimate quality of the goods in software development is to locate and fix errors and misconfigurations. The early detection and correction of flaws and misconfigurations in the software development lifecycle enable planning and cost savings.
Application security testing, which searches for potentially exploitable malware, misconfigurations, or code vulnerabilities in programs and apps, needs to be the first step in that assessment process. Preventiveness and preparedness start with identifying the knowns and unknowns in the code that underpins the different operating networks and applications that will define our digital future.
New code, especially third-party software, needs to be thoroughly identified, assessed, and validated before it is put on the network. The members of your cyber security team should monitor third-party advisory websites such as US-CERT and BugTraq for newly found vulnerabilities.
Even if there is a danger associated with fresh code, many apps and programs may already be operating on antiquated hardware that has security flaws and open doors. Thus, in addition to any new code, legacy code also needs to be checked for patches as part of a vulnerability assessment.
Every program is built on software code, and standards are required to maximize performance and spot flaws. Penetration testing and visibility scanning, which entail confirming and validating the susceptible source code, can accomplish this. The primary objective of the testing and validation techniques is to identify issues before they can contaminate devices and networks.
Software testing, evaluation, and validation are made considerably more difficult by the need to foresee the unknown threats that are typical of cybersecurity breaches, even though the known may be physical. One of these unknowns is locating concealed malware that is outside the reach of sandboxes, signature-based systems, and other behavioral detection methods.
The grim reality is that cyber-breaches are a dynamic threat since criminal hackers are always refining their tactics and skill sets. Cybercriminals these days employ increasingly complex evasion techniques, some of which can even disable malware detection tools. To get past machine learning code and evade anti-malware detection, these thieves usually employ stolen certificates that are sold on the dark web or underground market. Code injection and memory space alteration are used as an exploit kit is injected into the target system. Generative AI is significantly enhancing criminal hacker capabilities in those areas. The government and business sectors must work harder to address and contain cyber threat issues.
Beyond the use of conventional vulnerability scanners and manual penetration testing, testing needs to account for the tactical, behavioral, and ever-more-complex attack surface that hackers are targeting. It also needs to be automated to keep up with the speed at which the ever-evolving cyber world is changing. Developing defensive strategies and anticipating the moves of malicious cybercriminals are prudent measures to improve cybersecurity. It is accomplished through continuous validation testing.
Ongoing behavioral validation testing based on digital and human intelligence inputs makes it possible to close the gap in protection and discovery. Simulation results can be obtained quickly, frequently, and independently of the tester's skill level—a point that may introduce vulnerability.
Having A Plan for Business Continuity and Cyber-Resilience
Remedial measures are essential to continuity since breaches will always happen. To maximize resilience, industry and government entities should set up incident response plans that include mitigation, business continuity planning, and secure backup procedures in case networks and devices are compromised. Training and tabletop exercises can assist in implementing incident response plans in the event of a genuine incident.
Training information security personnel, establishing automated detection and backup systems, and optimizing response processes, cyber-resilience, and company continuity after an intrusion require ongoing development.
Since information sharing keeps the corporate and government sectors updated on the latest ransomware, viruses, malware, phishing, insider threats, and denial of service attacks, it also plays a critical role in resilience and business continuity. Sharing information also results in the creation of working procedures for resilience and lessons learned, which are essential for the success of commerce and the prosecution of cybercrimes.
Meeting The Security Challenges of Emerging Technology
Emerging technology is a tool that both threat actors and cyber-defenders can employ. The current state of cyber threats includes artificial and machine intelligence, quantum computing, the Internet of Things, 5G, virtual and augmented reality, and more.
A possible cybersecurity route that blends machine and artificial intelligence is automation. Artificial intelligence (AI) will significantly speed up security. It will enable real-time analysis and threat identification. Companies will be able to monitor activity within their system and spot any strange activity.
Artificial intelligence (AI) may be used by malevolent hackers to find vulnerabilities and automate phishing attempts, which will jeopardize continuity and resilience if it is not employed, or its implications are not recognized. AI and numerous other cutting-edge technologies will soon drastically change operational models and security. To preserve cyber-resilience and business continuity over the next 10 years, it will be imperative to tackle new and more sophisticated attacks.
Cybersecurity needs to take center stage if businesses are to thrive in today's complicated emerging technology threat environment. Being proactive instead of reactive makes sense for everyone working in the digital environment. Many proven cyber risk management approaches can be used to fortify defenses and plug holes. One theme runs through all risk postures: do not risk becoming complacent in the face of growing cyberthreats and dangers.
3 #Cybersecurity Trends to Watch - #AI #QuantumComputing & #SpaceTech
Chuck Brooks highlights how AI aids in threat detection, while quantum computing poses new risks & opportunities. Are you prepared for these trends?
Link: Avrohom Gottheil on X: "3 #Cybersecurity Trends to Watch - #AI #QuantumComputing & #SpaceTech @ChuckDBrooks highlights how AI aids in threat detection, while quantum computing poses new risks & opportunities. Are you prepared for these trends? Reach out to get featured on the #AskTheCEO Podcast! https://t.co/Av1kiILkO8" / X
The Growing Cyber Threat to Industrial OT
Link to podcast: https://www.canva.com/design/DAGKqeyu_ec/vtnURgNtbzgXBR8atKPEqQ/edit
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