Security spending in a downturn is under tight scrutiny. PricewaterhouseCoopers found this to be the case when it surveyed 7,200 executives in over 130 countries for its 2010 “Trial by Fire” report. One of the report’s primary findings states:
Not surprisingly, security spending is under pressure. Most executives are eyeing strategies to cancel, defer or downsize security-related initiatives.
Source: PricewaterhouseCoopers 2010 “Trial by Fire” report.
PricewatershouseCoopers notes that 70% of survey respondents think it is important to consider canceling, deferring or downsizing security-related initiatives if they require capital expenditures while 71% respond similarly for initiatives requiring working expenditures.At the same time, survey respondents overwhelmingly said they considered security strategies to be important, including increasing the focus on data protection, prioritizing security investments on risk, reducing or mitigating major risks and accelerating the adoption of security-related automation technologies to increase efficiencies and reduce cost. With many analysts predicting a slow recovery, the pressure to cut or curb security spending could increase. Meanwhile, security intrusions continue, likely at a more sophisticated scale (consider “Ghostnet” for example).
So, are there any cost-effective solutions available to meet growing security? Yes.The massively parallel-processing horsepower of the Pervasive DataRush™ data processing engine combined with our matching capabilities forms a powerful solution for translating massive amounts of raw data into actionable intelligence. Combined with Pervasive DataMatcher™, a cost-effective robust, innovative solution is available to financial, insurance, healthcare, law enforcement and homeland security organizations that want to leverage powerful, next-generation analytics for detecting fraud and corruption, complying with anti-money laundering controls, and security and compliance monitoring.
The Proof is in the Pudding: MalStone B-10 Benchmark
This year Pervasive DataRush conducted internal testing using the MalStone B. The benchmark examines large volumes of logfiles to look for anomalies that might signal intrusions or attempted intrusions.
The data file for MalStoneB is generated by a Python script and the MalStone records have the format:
Event ID | Timestamp | Site ID | Compromise Flag | Entity ID
These describe a visit by an entity to a site at a particular time. After the visit, the entity sometimes becomes compromised, which is indicated by setting the compromise flag to 1. Each record is 100 bytes. MalStoneB computes a ratio for each week d, and computes for each site w, and for all entities that visited the site at week d or earlier, the percent of visits for which the entity became compromised at any time between the visit and the end of the week d.The Malstone benchmark can use a variable sized dataset, In the experiment a 10 billion row dataset totaling 1 terabyte was used.
Summary of Details:
- 32 core, 4 socket, 2.0 Ghz Intel Xeon X7550
- 1890 seconds (32.5 minutes)
- 5.29 million rows/sec, approx 509 Mbytes/sec
The Result: In just 31.5 minutes, 10 billion records were searched for anomalies using Pervasive DataRush. This result is 26x faster than its competition.
Pervasive DataRush can enable applications that scale seamlessly on a single multicore server (rather than a cluster) to prepare or analyze even massive datasets – at unprecedented speeds. Cost-effective approaches to daunting security challenges – that’s what IT executives seek in the midst of a lingering downturn, and that’s what we want to give them.