Cyber resilience is the ability of a system to recover from an attack with minimal impact on system operations. However, characterizing a network's resilience under a cyber attack is challenging, as there are no formal definitions of resilience applicable to diverse network topologies and attack patterns. In this work, we propose a quantifiable formulation of resilience that considers multiple defender operational goals, the criticality of various network resources for daily operations, and provides interpretability to security operators about their system's resilience under attack. We evaluate our approach within the CybORG environment, a reinforcement learning (RL) framework for autonomous cyber defense, analyzing trade-offs between resilience, costs, and prioritization of operational goals. Furthermore, we introduce methods to aggregate resilience metrics across time-variable attack patterns and multiple network topologies, comprehensively characterizing system resilience. Using insights gained from our resilience metrics, we design RL autonomous defensive agents and compare them against several heuristic baselines, showing that proactive network hardening techniques and prompt recovery of compromised machines are critical for effective cyber defenses.

Dealing with threats and preventing sensitive data loss Recently, Normalyze, a data-first cloud security platform, came out of stealth with $22.2M in Series A funding. This was the perfect time to catch up with co-founder and CEO Amer Deeba. In this interview with Help Net Security, he talks about the path data security as well as visibility challenges. Who are the best fraud fighters? Seasoned fraud expert PJ Rohall has recently become the new Head of Fraud Strategy & Education at SEON.

Technologies such as artificial intelligence (AI), machine learning, the internet of things and quantum computing are expected to unlock unprecedented levels of computing power. These so-called fourth industrial revolution (4IR) technologies will power the future economy and bring new levels of efficiency and automation to businesses and consumers. AI in particular holds enormous promise for organisations battling a scourge of cyber attacks. Over the past few years, cyber attacks have been growing in volume and sophistication. The latest data from Mimecast's State of Email Security 2022 report found that 94% of South African organisations were targeted by e-mail-borne phishing attacks in the past year, and six out of every 10 fell victim to a ransomware attack.

Cyber-attacks are a big business, as highlighted by recent headlines of ransomware attacks on the Colonial Pipeline and on the Taiwanese computer manufacturer Acer, which allegedly paid a ransom of £50 million. According to Harvard Business Review, the total amount of ransom companies paid to hackers grew by 300% over the period of last 12 months – and high-profile victims of cyberattacks are now forking out millions to survive. It's easy to see why small and medium businesses (SMBs) may feel that cyberattacks are reserved for large enterprises with sky-high revenues – but this assumption comes at a cost. With 49% of SMBs impacted each month by cyber-attacks, it's clear all organisations are targets for cyber criminals. Cyberattacks have evolved in complexity amid the challenges of managing remote or hybrid workforces, meaning it's now crucial that businesses improve their understanding of cybersecurity and invest in strong backup and disaster recovery solutions.

Global catastrophes have historically brought moments of truth for all fields of business. In such times, their inner workings, strengths and weaknesses are laid bare for the whole world to see, as organizations rapidly alter their processes to come to terms with the new reality. Businesses that can make bold moves during such challenging times can quickly turn the misfortune into a benefit. So early indications are that businesses that value information as a currency, and have been quick to adapt machine learning and advanced data analytics, have emerged better from the economic aftermath of the pandemic. The coronavirus pandemic that continues to ravage the world has forced small businesses into building online ventures.

Artificial intelligence (AI) and machine learning (ML) give security teams the ability to catch bad guys with the power of math. Through the use of effective analytical methods, organizations can become more cyber resilient. With statistical learning; supervised, semi-supervised, and unsupervised ML; advanced visualizations; and other principled approaches tailored for cybersecurity, you will be one step ahead of the game. Here are six ways AI and ML, along with analytics, can boost your company's cyber resilience. AI and ML can remove friction in managing identities through adaptive authentication, which dynamically escalates the factors needed to verify an identity based on risk.

As IT environments become more dynamic, hybrid, and complex, it's becoming increasingly difficult for security operations center (SOC) teams to quickly detect and address critical threats with traditional tools. SOC staff must process and analyze a massive--and growing--amount of data, as they face ever more sophisticated cyber attacks. To respond effectively, SOC leaders can't keep adding rules-based tools to their already large and often unwieldy security stack. Instead, they need AI technology that analyzes data at scale and in real time and that uses machine learning to spots any anomalies that could signal a breach. That way, SOC teams detect unknown, fast-evolving threats missed by rules-based products configured to spot known attacks.

The dependency on digital and smart technology these days is on the rise, on top of that there are issues of ransomware and distributed denial of service (DDoS), the average number of focused cyberattacks per organization has more than doubled this year compared to the previous 12 months (232 through January 2018 versus 106 through January 2017). A new research conducted by Accenture has concluded that in spite of these growing cyber threats, the organizations are demonstrating far more success in detecting and blocking them. It was revealed that despite making significant progress, only two out of five organizations are currently investing in breakthrough technologies like machine learning, artificial intelligence (AI) and automation, indicating there is even more ground to be gained by increasing investment in cyber resilient innovations and solutions. The study conducted from January to mid-March 2018 investigated focused attacks defined as having the potential to both penetrate network defenses and cause damage, or extract high-value assets and processes from within organizations. Regardless of the increased pressure of ransomware attacks, which more than doubled in frequency last year, the study disclosed that organizations are upping their game and now preventing 87 percent of all focused attacks compared to 70 percent in 2017.

NEW YORK--(BUSINESS WIRE)--With ransomware and distributed denial of service (DDoS) attacks on the rise, the average number of focused cyberattacks per organization has more than doubled this year compared to the previous 12 months (232 through January 2018 versus 106 through January 2017). In the face of these growing cyber threats, organizations are demonstrating far more success in detecting and blocking them, according to a new study from Accenture (NYSE:ACN). Yet, despite making significant progress, only two out of five organizations are currently investing in breakthrough technologies like machine learning, artificial intelligence (AI) and automation, indicating there is even more ground to be gained by increasing investment in cyber resilient innovations and solutions. The study was conducted from January to mid-March 2018 and investigated focused attacks defined as having the potential to both penetrate network defenses and cause damage, or extract high-value assets and processes from within organizations. Despite the increased pressure of ransomware attacks, which more than doubled in frequency last year, the study found organizations are upping their game and now preventing 87 percent of all focused attacks compared to 70 percent in 2017.