Self-healing Security Systems - CloudIOTEnterpriseSystems-Group5.pptx
BiplabRoy71
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14 slides
Jul 13, 2024
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About This Presentation
Project on Self Healing
Size: 18.28 MB
Language: en
Added: Jul 13, 2024
Slides: 14 pages
Slide Content
Self-Healing Security Systems Advanced concepts in Enterprise Security CloudIOTAssignmentGroup 5: Biplab Roy, Mohit Gupta, Sathish Kumar, Vimal K V Cloud IoT and Enterprise Security (S1-23_SSCSHZG570)
Agenda: Understanding Self-Healing Security Systems Unleashing Autonomous Security Proactive Threat Detection Swift Solutions: Remediation Without Human Intervention Self-Healing Security Systems: A Paradigm Shift in Cybersecurity Fortifying Defences: A Real-World Self-Healing Security Triumph Navigating Challenges in Self-Healing Security Empowering Self-healing Security Systems: The Future Landscape Q & A
Understanding Self-Healing Security Systems The ability of a security system to automatically detect, analyze, and respond to cyberattacks using a set of predefined rules and actions. It also implies that the security system can learn from the incidents and update its rules and actions, accordingly, improving its security posture and resilience over time. Evolution From Reactive to Proactive Adaptive and Learning Systems Machine Learning and Artificial Intelligence (AI). Continuous Improvement. Context-Aware Security. Threat Intelligence Integration. Self-healing Security System Infrastructure
Unleashing Autonomous Security Significance of Autonomous security Reducing the human workload and error. Improving the system performance and availability. Enhancing the system adaptability and flexibility. Real-time threat detection & The role of Continuous Monitoring Allows organizations to proactively assess and strengthen an organization’s security posture by quickly accessing, filtering, and visualizing security data. These insights allow security teams to identify risk trends proactively. It decreases MTTK and MTTR simultaneously by more effectively investigating and responding to risk across their cloud infrastructure and applications. Improved Security. Better Record-keeping of Threats and Compliance Issues. Avoid Downtime. Areas Where We Can Implement Continuous Monitoring.
Proactive Threat Detection D etecting S ecurity V ulnerabilities Determine Critical and Attractive Assets. Conduct Vulnerability Assessment. Vulnerability Analysis and Risk Assessment. Remediation & Mitigation. Re-Evaluate System with Improvements. Report Results. Behavioural analytics and Anomaly detection One of the clearest anomaly detection examples is for preventing fraud. For example, a credit card company will use anomaly detection to track how customers typically use their credit cards. If a customer makes an abnormally large purchase or a purchase in a new location, the algorithm recognizes the anomaly and alerts a team member to contact the customer. The system may also automatically block a suspicious charge. Machine Learning Algorithms In the digital age, as our networks grow smarter, so must our guardians. Machine learning isn’t just an upgrade; it’s a necessity for survival in a world woven with invisible threads of data.
Swift Solutions: Remediation Without Human Intervention Remediation processes without human Intervention AI and automation to predict , detect and respond to IT operations issues, such as delays, workload failures and outages. ML to identify anomalies in cyber–physical systems, such as power grids, automobiles, medical devices, and smart industrial systems. AIOps to predict and prevent issues using machine learning to identify anomalies, then proactively take a fully automated action. Examples: Automated response mechanisms and system updates User Account Lockdown Real-time Policy Adjustments Threat Intelligence Integration Incident Response Playbook Updates Monitor the login attempts to a user account and lock it if it detects too many failures or anomalies. Unlock the user account after a certain period of time or after verifying the identity of the user. Notify the user and the administrator about the user account lockdown and provide instructions on how to restore the access. Monitor the network traffic and adjust the firewall rules or the intrusion detection system settings based on the current threat level or the user behavior. Update the security policies or the encryption keys based on the latest security standards or the data sensitivity. Use threat intelligence feeds from various sources, such as logs, events, network traffic, and threat intelligence platforms, to enrich its data and identify the most relevant and urgent threats and attacks. To prioritize and optimize its remediation actions, such as choosing the best countermeasure or patch for a given threat or vulnerability.
Self-Healing Security Systems A Paradigm Shift in Cybersecurity Safeguards individuals and organizations against cyberattacks and theft or loss of sensitive and confidential information. Cyberattacks can cause millions in economic costs, disrupt business operations, compromise critical infrastructure, endanger public health and safety, and undermine national security. Cyber attacks can be costly and damaging to both individuals and organizations, resulting in financial loss, reputational damage, and legal liabilities. Cyber attacks are increasing in frequency, sophistication, and complexity, posing significant risks to all types of organizations and individuals, especially smaller ones with fewer resources. Importance of Cybersecurity in the Digital Age? What is the i mportance of cybersecurity and the need for advanced solutions?
Fortifying Defences: A Real-World Self-Healing Security Triumph Secure its 750+ locations. Reduce malware infections by 90%. Save 40 hours per week on IT management. To build an integrated security stack to protect company data. To block 1.4 million threats per month. Improve network performance by 25%. Reduce IT costs by 30%. To manage its IoT infrastructure and retail operations securely. A unified security platform that reduced complexity. Increased visibility. Enhanced threat protection. Cisco Umbrella Overview: Cisco Umbrella is a cloud-delivered security service that offers DNS-layer security and threat intelligence, also a Secure Service Edge (SSE) solution that converges multiple security functions into one cloud-delivered architecture. Self-Healing Feature: It uses machine learning algorithms to analyze internet activity and identify malicious domains or IPs. If a user inadvertently attempts to connect to a malicious site, Umbrella can block the connection and prevent the threat from spreading within the network.
Navigating Challenges in Self-Healing Security Contd …
Balancing Act: Automation and Human Oversight Fine-Tuning Detection Algorithms Loss of human oversight and control. Increased attack surface &complexity. Reduced adaptability and flexibility. Risk Navigating Challenges in Self-Healing Security Importance Monitor and validate. Intervene and override. Update and improve. The complexity and diversity of cyber–physical systems (CPSs), which are systems that integrate physical processes with computing, sensing, and communication capabilities. The sophistication and evolution of cyberattacks. Challenge Measures: Sensitivity and specificity Using machine learning techniques. Using multiple detection methods. Using a priori determined smallest effect size of interest (SESOI).
Empowering Self-healing Security Systems: The Future Landscape Summarized key points: A new perspective and a competitive advantage in the continuous battle between cyber attackers and defenders, by reducing the need for manual interventions and improving the reliability and consistency of the system. Leverage emerging technologies , such as artificial intelligence, machine learning, blockchain, smart contracts, fuzzy logic, neural networks, multi-agent systems, and swarm intelligence, to enhance their capabilities and performance. Benefit from a human-centric approach , which engages and empowers employees to improve security, and which provides human oversight and control over the system's actions and outcomes. Face several challenges, such as hardware and software component vulnerabilities, adversarial machine learning attacks, complexity and scalability issues, and the risks associated with excessive dependence on automation. Require advanced techniques and tools to cope with the challenges and to balance the sensitivity and specificity of the detection algorithms, such as behavioral analytics, intrusion detection and prevention systems, encryption and authentication, and a priori determined smallest effect size of interest. Potential benefits despite challenges: Reducing the human workload and error. Improving the system performance and availability. Enhancing the system adaptability and flexibility.