Mitigating DDoS Attacks and Malware Spread

The phishing threat has advanced. Stopping these threats requires a solution that’s built from the ground up using Artificial Intelligence (AI) and Machine Learning (ML). The architecture of yesterday’s rules and signature-based solutions simply are not equipped to handle these threats. In fact, of today’s advanced phishing threats, 51% require AI/ML to identify and stop. AI is clearly essential for cybersecurity. But the type of AI matters.

It has become an established fact that the human factor is the most important element to secure in any organization if security is to be maintained. This case study will take real-life examples (with no names used!) and examine some actual security incidents caused by human error and elaborate on the root cause and prevention tips resulting from these events.

Companies of every size and across every industry need to have the solution to defend against cyber attacks. For medium-sized and budget-constrained companies especially – the array of security technologies and solution and the volume of cyber threats can make the challenge seem overwhelming. Organizations suffer trying to manage raw data, security events and false positive incidents with limited context, overworked staff, and a lack of threat landscape knowledge. There is a better way to improve your security without the time, effort, and cost of purchasing and integrating multiple tools, a traditional SIEM or expensive traditional security outsourcing vendors.

Only with full visibility into employee or third-party activity across a company network can even the earliest indicators of an insider threat be detected. By monitoring both user and file activity, security and compliance professionals can be alerted to risky, out-of-policy activities and any unexplained changes in user behavior in real-time; successfully stopping and investigating any activity before it becomes a full-blown breach. Research from The Ponemon Institute shows that Financial Services organizations face the highest penalty costs of any other industry ($12.05 million annually) when they experience an insider-led incident, though they are closely followed by the Energy & Utilities and Retail sector. This cost alone is a very concrete reason to address what otherwise might seem to be an invisible problem.