Big Data. Big Decisions
InformationWeek
Special Coverage Series


4 Steps For Proactive Cybersecurity

Tired of having malware punch you in the face? The time's not right to hit back, but here are moves to make now.

InformationWeek Green - Jan. 21, 2013 InformationWeek Green
Download the entire Jan. 21, 2013, issue of InformationWeek, distributed in an all-digital format as part of our Green Initiative
(Registration required.)
We will plant a tree for each of the first 5,000 downloads.

Storage Innovation

In our dive into the theory behind offensive cybersecurity, Gadi Evron summarized the legal and ethical problems of fighting back against an attacker. There are also some purely tactical problems: How do you know you're not blasting some grandmother in Akron whose PC is a zombie? Are you prepared to come under the glare of organized criminals?

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

I share Evron's outlook that for most, if not all, nongovernmental entities it's too soon to go down the path of all-out, offensive security counterattacks. Many other security professionals agree, and you can get a good summary of the academic and government research on cyber espionage, cyber deterrence and cyber offense by reading a recent post by Dave Dittrich, a member of the HoneyNet Project: "No, Executing Offensive Actions Against Our Adversaries Really Does Have High Risk (Deal With It)."

But you can do a lot more than read and hope. Here are some ways to take action now that will at least let your team start taking a more offensive security mindset.

Step 1: Do active risk analysis to know what attackers may strike at, and how.

Intelligence gathering is an arduous task for even well-funded government agencies, so it is highly unlikely that your company can achieve the level of detail required for true cyber intelligence about attackers. Further complicating intelligence gathering is that private-sector chief information security officers don't share details of successful breaches, even though such collaboration would be critical to understanding and linking methods and attackers. But that's another article.

For now, focus your effort on the intelligence gathering you do control: knowledge of your own systems, networks and business.

Our full report on offensive cybersecurity free with registration.

This report includes 21 pages of action-oriented analysis. What you’ll find:
  • Strategic Security Survey data on the top reasons for increased vulnerability
  • Top breach/espionage threats: cybercriminals tied for No. 1
Get This And All Our Reports

Conventional cyber defense involves security engineers trying to figure out what attackers can do, how they might break in and what system holes could be exploited. But this is where IT could learn from traditional engineering disciplines, which take a more proactive approach. For example, mechanical engineers are taught to approach problems using failure analysis. This technique involves identifying the conditions where a failure can occur instead of trying to figure out what failures can occur. Think of an explosion caused by an oily rag. Without oxygen, oil, the rag and fire that ignites everything, an explosion won't happen. Yet most security engineers trying to keep their networks from being blown wide open look for flames via log data (the attack) rather than finding the oxygen, oily rags and sparks -- what must be present for an explosion.

Your intelligence gathering needs to focus on identifying hazardous conditions. You will then learn each condition also has a subset of conditions, and this chain continues until you have an addressable condition. For example, instead of trying to detect or prevent a zero-day exploit from installing malware on a machine, ensure that the conditions for a breach are not present. Eliminate easily guessed passwords, weak permissions on files and folders, and administrative permissions, all which are under your control, instead of trying to figure out where and how any given piece of malware, which you don't control, might strike.

This approach requires that your security team know how attackers accomplish their mischief once inside, and that means spending time learning how exploits, penetration testing and underlying applications work. This isn't easy, but it's why mechanical engineers spend years being trained about potential conditions.

While there are several failure-analysis methods, including Alex Hutton's Risk Fish, discussed recently in Dark Reading, here's how we recommend you go about it:

To read the rest of the article,
Download the Jan. 21, 2013 issue of InformationWeek



Related Links

Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.