A disturbing upward trend in cyber security data breaches has been uncovered recently by multiple industry research sources. Some noteworthy data breach statistics include:
- 56% of 1,379 incidents with specific malware functionality were ransomware from the 2018 Verizon Data Breach Investigations Report.
- 668 breaches compromised 22,408,258 records between January 1 and July 2, 2018 according to the Identity Theft Resource Center report.
- The average total cost of a data breach is $3.86 million, the average global possibility of a breach in the next 24 months is 27.9%, and the average breach cost reduction for organizations using security automation is $1.55 million according to the 2018 Ponemon Report.
Against this landscape, organizations are asking themselves why attackers are so successful in stealing online data.
Attackers are winning in spite of increasing security investments
There’s little doubt the dark side of the internet is winning at attacking, breaching, and exfiltrating corporate data from too many businesses. In order to combat cybercriminals, organizations are investing in security. But are the investments effective?
There’s an old adage that it’s better to work smarter not harder., The traditional security mindset of many organizations is that they must work hard to build a strong perimeter defense, but this sort of defense on its own is not sufficient to protect cyber assets. In fact many would argue that with corporate assets now on premises, in the cloud, and in hybrid environments, the perimeter is dead. In reality, the perimeter is growing organically.
Adding vendors that enable more efficient business processes expands the data perimeter. With more vendors interacting with more sensitive data, companies need to focus on the risk these vendors pose to their data environment. While service level agreements create promises of protection, companies need to not only trust their partners but verify their partners’ security stances. Indeed a company’s weakest link may not be something in their network, but rather a deficiency in a partner or vendor company’s network.
More contemporary mindsets are beginning to think differently. Companies need to evolve their security solutions to match malicious actor methodologies. Hackers continue to find new attack vectors. Traditional security solutions enable protection but not always continuous monitoring of the constantly evolving threats to a company’s data environment. Intelligent monitoring services are starting to emerge that instead of just physically closing network doors, introduce advanced learning techniques that monitor in such a way to quickly highlight easy-to-compromise security deficiencies. In some regards, they are monitoring from the perspective of a potential hacker. Using this emerging class of solutions, organizations can complement their more traditional security measures with intelligent monitoring that can enable organizations to prioritize security issues, that if left unaddressed can be easy gateways for a successful data breach.
Big data gives big answers
Security automation provides a solution for many organizations. Big data enables companies to collect information from across the internet and aggregate it. Structured data, the kind easily organized in tables, is easy to manipulate. However, the internet includes a variety of information such as text, images, and audio. All of this unstructured data can provide insights but understanding how to aggregate it and use it feels overwhelming.
Increasingly, security automation options enable aggregation, storage, and analysis to provide clear insights into how well a company protects its perimeter. More information and the incorporation of predictive analytics allow companies to find breaches sooner so that they contain the data leakage faster. The 2018 Ponemon Report shares that early containment (less than 30 days) saved $1.16 million on average in 2018 and $94,000 in 2017. The average cost savings for organizations containing the data breach increased between 2017 and 2018 indicating that these numbers may continue to rise.
Using machine learning, artificial intelligence, analytics, and orchestration enables companies to both reduce costs and reduce the likelihood of a breach to their systems and networks. As the old saying goes, “knowledge is power.” Big data and predictive analytics empower organizations by providing information and insights.
Gain more visibility with cyber security vendor risk management solutions
Security ratings services, also known as ecosystem risk management solutions, including SecurityScorecard, can provide active cyberhealth monitoring to help organizations begin a path towards working smarter when building a security program. Using an effective ecosystem risk management solution, businesses can measure overall cyber health for themselves and for an ecosystem of companies of interest (e.g., vendors, partners, a partner’s partners, and M&A targets).
SecurityScorecard’s algorithms enable companies with an automated system that uses big data and predictive analytics. Using signals collected across the entire IPV4 spectrum, SecurityScorecard applies advanced machine learning techniques that turns millions of security data inputs into a prioritized list of security risk factors and issues of concern. Prioritizing security risk factors based on the predictive analytics allows more transparency into the data ecosystem. Instead of a responding to a constant barrage of alerts, information security professionals can triage to treat the most significant threats first. By doing this, they can mitigate threats or contain leaks more quickly which saves time and money.
Working smarter, not harder, means finding tools that streamline the increasing workflow within the information security department. The need for working hard when it comes to cyber security isn’t going away anytime soon as threats evolve. Companies can lower risk and time with intelligent ecosystem risk management solutions like SecurityScorecard to understand and address critical cyber deficiencies and to minimize the risk of becoming a breach statistic in the future.
