Automation Deserves Skepticism

While automation might be the next great tech wave, lets take some time to consider it.

Garbage in, garbage out is a maxim nearly as old as computers themselves. As automation becomes a greater factor in security, is it possible that we need to add garbage in, security out to the list of variants?
From the
first recorded instance in 1963
, garbage in, garbage out (or GIGO) has been a critical reminder that processing power is only as useful as the data that goes into the process. The best algorithms and programs will return useless information if theyre fed bad data.
Bad data and the results that follow are hazardous enough when humans will read the information and perform additional analysis before acting; humans can (though the often dont) serve as a quality control agents for the process before things get wildly out of hand. In an automated system, though, the human QC agent is out of the loop and bad data can lead very quickly to bad action.
When it comes to security, automation is seen by many as the only
rational path to meet future needs
. The reasons are fairly straightforward; the number of attacks is going up as the volume of data in each attack also goes up. Add to that the rapid environmental changes that flow from virtualization, cloud computing and hybrid architectures, and youre at a situation where humans are simply too slow to keep up with all the activity.
The problem with relying on automation for enterprise security is that it means relying on massive amounts of data and complex algorithms to protect networks, compute assets and data. We rely on similar data sets and algorithms for many enterprise functions, but there is reason to be cautious when placing safety, economic health and corporate reputation in the hands of automated systems.
About a week ago
a mathematician named Cathy ONeil
had a TED talk published. ONeil is a frequent columnist for news organizations like Bloomberg and she is known for having a skeptical view of the way in which many organizations rely on data (especially big data) and algorithms. The title of her new book,
Weapons of Math Destruction
, says a lot about her attitude toward these tools.
Whether you agree with ONeil or not, one of her major points is indisputable: If youre going to put your trust in an algorithm, you should fully understand the algorithm and thoroughly test the software that implements the algorithm. Next, you must insure that the data feeding the algorithms is meaningful and accurate. This is especially important when using big data as the foundation of security operations because its entirely too easy to collect data that represents noise more than information.
Youre invited to attend Light Readings
Virtualizing the Cable Architecture event
– a free breakfast panel at SCTE/ISBEs Cable-Tec Expo on October 18 featuring Comcasts Rob Howald and Charters John Dickinson.
Theres no reason to completely avoid automation, but like any new application of technology it must be implemented with caution and care -- qualities that may or may not be abundant when cyber attacks are occurring all around you. Be careful out there -- whether fully automated or not.
— Curtis Franklin is the editor of
SecurityNow.com
. Follow him on Twitter
@kg4gwa
.

Last News
▸ Making use of a homemade Android army ◂ Discovered: 23/12/2024 Category: security	▸ CryptoWall is more widespread but less lucrative than CryptoLocker. ◂ Discovered: 23/12/2024 Category: security	▸ Feds probe cyber breaches at JPMorgan, other banks. ◂ Discovered: 23/12/2024 Category: security

**Cyber Security Categories**
Google Dorks Database	Exploits Vulnerability	Exploit Shellcodes

CVE List

Tools/Apps

News/Aarticles

Phishing Database

Deepfake Detection

Trends/Statistics & Live Infos

Tags:
Automation Deserves Skepticism