What are the most promising areas of research and innovation in security incident response?

Incident response is the structured approach taken by organizations to address and manage the aftermath of a cybersecurity incident. There's considerable scope for research and innovation in all areas. Automation plays a pivotal role in streamlining incident response, particularly given the volume of data and alerts analysts face. Fine-tuning alerts is essential to alleviate analysts' workload. By automating alert filtering, analysts can prioritize and address critical alerts more efficiently."

Após anos como principal gestor de tecnologia de grande empresas, agora estou atuando em segurança da informação. E agora vendo como algumas estruturas são frágeis. Não precisa de uma ameaça sofisticada para derrubar um site. Isso se deve a falta de experiência, especialização e priorização dada a segurança por algumas empresas. Felizmente a IA vem ajudando a cobrir algumas destas lacunas. Um ótimo exemplo é o CoPilot da Checkpoint, não apenas identificando problemas como os resolvendo. Até a configuração do WAF ele pode fazer para você. As ameaças são cada vez mais rápidas. Uma vulnerabilidade descoberta passa a ser ativamente explorada em média em 8 dias. É fundamental equipes mais ágeis e a IA vem para ajudar neste tempo de resposta.

The most promising areas for security incident response improvement involve automation, artificial intelligence, data protection, security training, and ongoing cybersecurity research. Key initiatives include MITRE ATT&CK, CISA, and NIST frameworks. Organizations must stay informed about these advancements to effectively combat ever-changing security threats.

A automação da resposta a incidentes pode ajudar a acelerar a detecção, a análise e a mitigação de incidentes de segurança. Isso envolve o uso de ferramentas e tecnologias para automatizar tarefas repetitivas, como a coleta de dados, a análise forense e a implementação de medidas de segurança corretivas.

Some of the most promising areas of research and innovation in security incident response include: 1. Automation and Orchestration: Developing automated tools and processes to streamline incident detection, analysis, and response, reducing manual effort and response times. 2. Threat Intelligence Sharing: Improving collaboration and information sharing between organizations to facilitate early threat detection and response. 3. IoT and OT Security: Researching strategies for detecting and responding to security incidents in Internet of Things (IoT) and Operational Technology (OT) environments, which present unique challenges due to diverse device types and protocols.

Another key aspect of security incident response is the ability to collect, analyze, and share relevant and actionable information about attackers, their tactics, techniques, and procedures, and indicators of compromise. Threat intelligence and analysis are technologies that can help enrich and contextualize data from various sources, such as logs, network traffic, endpoints, and external sources, and provide insights and recommendations for security incident response. Threat intelligence and analysis can also help identify and prioritize the most critical and relevant threats, as well as detect and prevent emerging and advanced attacks.

Effective incident response relies on identifying and collecting logs from diverse sources, both internal and external, to correlate data and understand the incident lifecycle comprehensively. Threat intelligence (TI) and threat hunting are integral components of incident response, aiding in processes such as proof of concept (POC) and identifying tactics, techniques, and procedures (TTPs).

NLP technologies can assist security analysts in quickly understanding and responding to security incidents by analyzing unstructured data sources such as security incident reports or threat intelligence feeds and extracting relevant information from them.

I feel AI is like a smart assistant that can quickly spot and stop cyber threats, making our defenses faster and smarter. Quantum computing is another exciting area; it's like having a super-powered brain that can solve complex security problems in seconds, potentially revolutionizing how we protect our digital world. Both are at the forefront of making the internet a safer place, turning science fiction into reality for cybersecurity.

With the rapid chang of technology used for the same threats used by different adversies, which some already are using AI (I.e. AI Worm), only if we use same tools and will train our AI based defenders, we may have a chance for early ditction and automated response

Most promising and frightening, AI. We thought 'click to hack' was bad, when anyone with a browser could launch an attack, with little or no tech skills. now, that same bunch can build attacks using AI. From the protection front, chatgpt4 can be used to filter out 'noise' both on the web and in your own data.

Artificial intelligence and machine learning are technologies that can help enhance the capabilities of human analysts and improve the performance of security incident response. Artificial intelligence and machine learning can assist in automating the detection and classification of incidents, as well as the generation and execution of response actions. They can also aid in learning from historical data and feedback, and adapt to changing environments and scenarios. Artificial intelligence and machine learning can further help in uncovering new patterns and anomalies, as well as providing predictive and prescriptive analytics for security incident response.

In the realm of cyber incident response, while many focus on prevention, I advocate for prioritizing cyber resilience. Grounded in business continuity, this approach recognizes the inevitability of evolving cyber threats. By centering research and innovation on resilience, we can enhance our ability to recover swiftly and minimize disruption from incidents. Cyber resilience ensures businesses can quickly return to normal operations, minimizing losses despite any threats. This focus is vital for maintaining operational continuity in the face of cyber challenges, making it a crucial area for future research and innovation in cyber security.

Cyber resilience and recovery are indispensable for organizations facing cyber threats.These concepts encompass various dimensions of security IR, including technical,organizational,cultural, and strategic aspects.Through meticulous planning, testing, and continuous improvement, organizations can enhance their ability to withstand, adapt to,and recover from cyberattacks while minimizing financial,operational,reputational,and legal risks.Promising areas include AI-driven threat detection,behavioral analytics,Zero Trust Architecture,cyber threat intelligence,and incident response automation. These advancements is crucial for organizations seeking to bolster their cyber resilience and recovery capabilities in today's dynamic threat landscape.

We are yet to come to terms with being breached, resilience takes a posture that compromise is a high probability, which is today's reality. Wish to see the preparedness of security professionals being appreciated and investments given their rightful place. Bravo sir for your thoughts.

The amount of information available to cloud service providers that they subsequently make available to you using their APIs is absolutely mind boggling. Following on Nvidia's recent GTC conference in which multiple vendors discussed using machine learning to assess the infrastructure, one can imagine how this is already shaping up for cloud providers to deliver natural language IR. Lots to still do... but just wait for it. How quickly it is - and will - change for the better. It's a wonderful time to have an enormous amount of information when you have access to cloud native and distributed security that's empowered to identify and solve problems with natural language processing.

User and Entity Behavior Analytics (UEBA) technologies stand at the forefront of promising research and innovation areas in incident response. These tools monitor and analyze user and entity activities, including interactions with devices, applications, and services within an organization. By doing so, UEBA can detect and address internal threats from malicious, compromised, or negligent users, as well as external threats like phishing, malware, or credential theft. Additionally, UEBA systems establish behavioral baselines and benchmarks to identify normal and abnormal activities This capability is crucial for providing alerts and feedback for security incident responses, making UEBA a vital component in strengthening cybersecurity defenses

In the evolving field, one promising area is the integration of quantum computing. Quantum technology, with its potential for high-speed computation, could revolutionize incident response by rapidly identifying threats and implementing countermeasures. For instance, a quantum-enabled security system could detect a data breach attempt in real-time and instantly neutralize it, significantly reducing the window of vulnerability. However, it's a double-edged sword as quantum computers could also pose new threats, necessitating the development of quantum-resistant algorithms. This dynamic interplay between quantum computing and cybersecurity presents a fascinating avenue for research and innovation.