#SecureWorld

[amigoways]

Celebrate #NationalComputerSecurityDay with Amigoways! 🔐 Stay safe online by prioritizing cybersecurity. From secure browsing to protecting your data, we’ve got you covered. 💻💡

[jcmarchi]

A strategic shift to AI-powered and cloud-delivered solutions - CyberTalk

New Post has been published on https://thedigitalinsider.com/a-strategic-shift-to-ai-powered-and-cloud-delivered-solutions-cybertalk/

A strategic shift to AI-powered and cloud-delivered solutions - CyberTalk

EXECUTIVE SUMMARY:

AI is revolutionizing businesses worldwide. Enterprises are being reinvented through artificial intelligence. AI is also separating the industry leaders from the industry followers. 

In the U.S., 73% of companies have already adopted artificial intelligence. Within certain sectors, experts expect that, on an annual basis, AI could contribute $4.4 trillion to the economy.

But, despite the promise and potential, a number of enterprises have slowed their AI adoption, citing compliance and data privacy concerns as barriers to rapid deployment.

What a lot of enterprises aren’t aware of is that there’s a strategic shift happening…AI has become an integral part of the cyber security landscape.

Diverse IT environments

Imagine an intelligent shield that dynamically protects data by adapting to emerging threats, ensuring that your organization always stays one step ahead of hackers.

AI-based cyber security tools, such as Check Point Infinity AI Copilot, can provide this type of flexible and comprehensive security for diverse IT environments.

Closing the talent gap

Another advantage of AI-powered cyber security tools is that they can help close the cyber security talent gap.

Worldwide, there’s a shortage of roughly three million cyber security professionals.

AI-based tools, like Check Point’s Infinity AI Copilot can enhance analysts’ speed and accuracy, bridging the gap.

AI-based cyber security tools like Infinity AI Copilot enable protection of data centers, networks, cloud, branch offices and work-from-anywhere users. Admins can now easily obtain capabilities that allow for streamlined management via a unified management console.

Collaborative communication

Platforms like Infinity ThreatCloud AI can also provide rapid, real-time threat intelligence. The intelligence is seamlessly woven into the fabric of the platform. Automation and orchestration features ensure that threat responses are fast and effective.

Get more information

AI-powered cyber security engines enable organizations to proactively prevent and defend against threats by offering complete coverage of a security estate, real-time insights, automated processes and greater efficiency.

Enhance your knowledge. Join me at SecureWorld Boston, a premiere cyber security conference that offers a wealth of learning opportunities for CISOs and other security professionals. We’ll talk more about AI-powered cloud-delivered cyber security, addressing specific use-cases in which AI-powered engines offer exceptional value. Register now and make the most of this event.

[anthonybatow]

Немного об Астане... Красиво, дорого, богато, но по-прежнему пустовато, простовато и безоснованияпонтовато 😁, но думаю еще лет 10 и это будет шикарнейшая жемчужина степи😉 #астана #казахстан #выставка #korme #secureworld (at Korme Exhibition Center)

[emailknowitall-blog]

What Do You Need to do after a Phishing Attack

Phishing is a type of social engineering attack often used to steal user data, including login credentials and credit card numbers. It occurs when an attacker, masquerading as a trusted entity, dupes a victim into opening an email, instant message, or text message.

Sometimes, you click these phishing emails or visit malicious websites which can compromise your personal and professional information. Here are some tips that will help you know what you need to do after a phishing attack.

Take A Deep Breath

Phishing schemes have become increasingly sophisticated, so don’t beat yourself up if you fall for one. Take a few deep breaths to calm down, clear your head, and plan your next steps. Remember that falling for a phishing scheme doesn’t necessarily mean that your identity will be stolen. Phishing schemes vary, so what you’ll do next depends on what kind of phisher targeted you.

If you downloaded a fraudulent attachment, turn off Wi-Fi and disconnect from the internet, stat. If you remove the phisher’s access to your computer quickly enough, you may be able to stop the phisher from installing malware or gaining remote access to your computer. And if you clicked on a link to a fraudulent website, try to remember exactly what information (username, password, address) you entered. Take screenshots of the phishing email or jot down details such as the sender’s email address, the content of the email, and the URL that you clicked...and more info over at - metalfloss.com.

Notify your supervisor if you have one

This is the difficult part, as many people are embarrassed about their mistake and worry they will get in trouble. Don’t be afraid: a company with a good phishing policy should not blame the employee. Additionally, every second you delay can potentially make the problem worse.

Change usernames and passwords

If the phishing email sent you to a phony site and asked you to enter your credentials, it probably captured that info. To be on the safe side, change all user/passwords for important sites like work email, bank accounts and social media...go to - resources.infosecinstitute.com.

Notify Credit Agencies

Contact one of the three major credit bureaus as soon as possible and let themknow your account was potentially compromised. Place a fraud alert on your account until the issue has been resolved.

Contact Credit Card Companies

Alert credit card companies and explain the situation. Your credit cards might not have been used yet, but if you feel unauthorized charges are in your future, it’s essential to freeze or cancel your cards. Let your bank know what happened so they can further protect your credit line.

Update Your Software

Update your software to the newest version and run a comprehensive virus scan if you think you’ve infected your system with a virus or other malware. Additionally, you should use encryption, ensure you have a firewall enabled, and regularly back up personal information on an external hard drive. Avoid using public Wi-Fi networks whenever possible, and if you must use a public connection, select the most secure option, such as a Virtual Private Network (VPN). Also, make certain to turn your computer off when not in use, as it’s inaccessible to hackers when powered down...to know more, visit - Norton.

Obtain a copy of the email with complete headers and any original attachments

Make sure that you get the email message with full headers showing routing info, etc. Take note of the originating IP address that the message; in most cases it will be from a compromised machine of some sort — either an end user’s desktop acting as a bot for the message or from a compromised or vulnerable server. These types of details will help with your investigation.

Search the web for threat intelligence

There are a lot of threat intel and lookup sites out there. Take any URLs, attachments, etc., to sandbox and lookup sites out there. Take domains, IPs, etc., to sites like IPVoid.com. Google the IP, hostnames, URLs, files, etc., of what you see.

Be careful, however, that you don’t actually go to malicious sites. If you paste an IP into your browser, it will change it to a URL and go to the IP. That’s embarrassing (and potentially dangerous). Instead, put the IP address in quotes to ensure that your browser and Google know you are just searching...visit - secureworld to know more.

A Phishing attack is the most common and one of the worst cyber attacks. To protect against it, you will need to get the help of good phishing protection tools that will keep your email safe against these threats. Click here to know more about phishing attacks and how to get rid of a phishing email. 

[jobwerld]

Full Time Security Jobs

Job Details: SecureWorld Corp is hiring professionally minded fulltime security supervisors, armed and unarmed security officers for a new location in Trelwany and Negril and existing locations in St. Ann. Barracks are available in Negril and St. Ann. Our staff have always been treated as employees and not contractors. Apply in person at our offices at ATL Plaza in Bogue, Montego Bay or Apply…

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[expomahal-blog]

SecureWorld - Seattle 2019 at United States(Seattle) 2019-November

plants contact list, herbs contact info, gardens Shows, garden technology Meetings, garden piece of furniture contact list, gardening accessories companies, terracotta Exhibitors, ceramics Trade Shows, well info, ponds companies contacts, conservatories companies contacts, gardening service Exhibitors Directory, traders contact links, distributors contact list, retailers contact info, importers Shows, key decision makers Trade Shows 2019, November, United States, Mesa

Women's Day Out Expo - Mesa Fall 2019 at United States(Mesa) 2019-November

Women's Day Out Expo - Mesa Fall 2019 trade show event mainly focuses on:

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related products/services/industry/business. This trade show opens top business opportunities to exhibit products and services from plants Trade Shows, herbs Exhibitors, gardens business opportunities, garden technology info, garden piece of furniture business, gardening accessories business opportunities, terracotta B2B Opportunities, ceramics Exhibitors, well business opportunities, ponds contact links, conservatories Exhibitors, gardening service contact list, traders Business events, distributors Business events, retailers Events, importers Events, key decision makers info industry.

Find More Details about Women's Day Out Expo - Mesa Fall 2019 event...

We help you to grow your business by providing the required contact details of all companies participating in this event and you can download the same data in excel format using the above links. Location of the Event:United States(Mesa) Year-Month:2019-November Official Website:Event Website source https://www.expomahal.com/2019/10/secureworld-seattle-2019-at-united.html

[ericvanderburg]

SecureWorld cybersecurity conference in Denver Oct. 29-30

http://securitytc.com/RCc45b

[yogeshmalik]

Cybersecurity in Focus at 3rd Annual Secureworld Chicago - EIN News http://bit.ly/30V8NYW

[aioftheday]

Latest on #AI #Economy #Policy #BasicIncome https://t.co/u1sPiyInTz Thanks to @Superiadigital @SecureWorld @pingmicro #artificialintelligence #ai

Latest on #AI #Economy #Policy #BasicIncome https://t.co/u1sPiyInTz Thanks to @Superiadigital @SecureWorld @pingmicro #artificialintelligence #ai

— AI Of The Day (@AIofTheDay) August 8, 2018

from Twitter https://twitter.com/AIofTheDay August 08, 2018 at 11:23AM via IFTTT

[kpmgtoday]

5 Key Security Responses from Massive New CIO Study

By SecureWorld. The Harvey Nash/KPMG survey of Chief Information Officers bills itself as the largest IT leadership survey in the world. And its CIO ... Delivered by KPMG Today (@KPMG_TO) Read more here Follow @KPMG_TO on Twitter to get latest updates

[nationalcybersecurity-blog1]

SecureWorld Chicago

General Cybersecurity Conference  June 7, 2018 | Chicago, Illinois, United States

Cybersecurity Conference Description

Join your fellow security professionals for affordable, high-quality training and education. Attend featured keynotes, panel discussions, and breakout sessions, all while networking with local peers. Earn 6 – 12 CPE (Continuing Education Credits; also known as CPD/ CEU) credits…

[securitynewswire]

Bruce Sussman SecureWorld Boston Pauls Security Weekly 549

SNPX.com : http://dlvr.it/QJnvWD

[lbcybersecurity]

toolsmith #129 – DFIR Redefined: Deeper Functionality for Investigators with R – Part 2

You can have data without information, but you cannot have information without data. ~Daniel Keys Moran

Here we resume our discussion of DFIR Redefined: Deeper Functionality for Investigators with R as begun in Part 1. First, now that my presentation season has wrapped up, I've posted the related material on the Github for this content. I've specifically posted the most recent version as presented at SecureWorld Seattle, which included Eric Kapfhammer's contributions and a bit of his forward thinking for next steps in this approach. When we left off last month I parted company with you in the middle of an explanation of analysis of emotional valence, or the "the intrinsic attractiveness (positive valence) or averseness (negative valence) of an event, object, or situation", using R and the Twitter API. It's probably worth your time to go back and refresh with the end of Part 1. Our last discussion point was specific to the popularity of negative tweets versus positive tweets with a cluster of emotionally neutral retweets, two positive retweets, and a load of negative retweets. This type of analysis can quickly give us better understanding of an attacker collective's sentiment, particularly where the collective is vocal via social media. Teeing off the popularity of negative versus positive sentiment, we can assess the actual words fueling such sentiment analysis. It doesn't take us much R code to achieve our goal using the apply family of functions. The likes of apply, lapply, and sapply allow you to manipulate slices of data from matrices, arrays, lists and data frames in a repetitive way without having to use loops. We use code here directly from Michael Levy, Social Scientist, and his Playing with Twitter Data post.

polWordTables =    sapply(pol, function(p) {     words = c(positiveWords = paste(p[[1]]$pos.words[[1]], collapse = ' '),                negativeWords = paste(p[[1]]$neg.words[[1]], collapse = ' '))     gsub('-', '', words)  # Get rid of nothing found's "-"   }) %>%   apply(1, paste, collapse = ' ') %>%    stripWhitespace() %>%    strsplit(' ') %>%   sapply(table) par(mfrow = c(1, 2)) invisible(   lapply(1:2, function(i) {     dotchart(sort(polWordTables[[i]]), cex = .5)     mtext(names(polWordTables)[i])   }))

The result is a tidy visual representation of exactly what we learned at the end of Part 1, results as noted in Figure 1.

Figure 1: Positive vs negative words

Content including words such as killed, dangerous, infected, and attacks are definitely more interesting to readers than words such as good and clean. Sentiment like this could definitely be used to assess potential attacker outcomes and behaviors just prior, or in the midst of an attack, particularly in DDoS scenarios. Couple sentiment analysis with the ability to visualize networks of retweets and mentions, and you could zoom in on potential leaders or organizers. The larger the network node, the more retweets, as seen in Figure 2.

Figure 2: Who is retweeting who?

Remember our initial premise, as described in Part 1, was that attacker groups often use associated hashtags and handles, and the minions that want to be "part of" often retweet and use the hashtag(s). Individual attackers either freely give themselves away, or often become easily identifiable or associated, via Twitter. Note that our dominant retweets are for @joe4security, @HackRead,  @defendmalware (not actual attackers, but bloggers talking about attacks, used here for example's sake). Figure 3 shows us who is mentioning who.

Figure 3: Who is mentioning who?

Note that @defendmalware mentions @HackRead. If these were actual attackers it would not be unreasonable to imagine a possible relationship between Twitter accounts that are actively retweeting and mentioning each other before or during an attack. Now let's assume @HackRead might be a possible suspect and you'd like to learn a bit more about possible additional suspects. In reality @HackRead HQ is in Milan, Italy. Perhaps Milan then might be a location for other attackers. I can feed  in Twittter handles from my retweet and mentions network above, query the Twitter API with very specific geocode, and lock it within five miles of the center of Milan. The results are immediate per Figure 4.

Figure 4: GeoLocation code and results

Obviously, as these Twitter accounts aren't actual attackers, their retweets aren't actually pertinent to our presumed attack scenario, but they definitely retweeted @computerweekly (seen in retweets and mentions) from within five miles of the center of Milan. If @HackRead were the leader of an organization, and we believed that associates were assumed to be within geographical proximity, geolocation via the Twitter API could be quite useful. Again, these are all used as thematic examples, no actual attacks should be related to any of these accounts in any way.

With the abundance of data, and often subjective or biased analysis, there are occasions where a quick, authoritative decision can be quite beneficial. Fast-and-frugal trees (FFTs) to the rescue. FFTs are simple algorithms that facilitate efficient and accurate decisions based on limited information. Nathaniel D. Phillips, PhD created FFTrees for R to allow anyone to easily create, visualize and evaluate FFTs. Malcolm Gladwell has said that "we are suspicious of rapid cognition. We live in a world that assumes that the quality of a decision is directly related to the time and effort that went into making it.” FFTs, and decision trees at large, counter that premise and aid in the timely, efficient processing of data with the intent of a quick but sound decision. As with so much of information security, there is often a direct correlation with medical, psychological, and social sciences, and the use of FFTs is no different. Often, predictive analysis is conducted with logistic regression, used to "describe data and to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables." Would you prefer logistic regression or FFTs?

Figure 5: Thanks, I'll take FFTs

Here's a text book information security scenario, often rife with subjectivity and bias. After a breach, and subsequent third party risk assessment that generated a ton of CVSS data, make a fast decision about what treatments to apply first. Because everyone loves CVSS.

Figure 6: CVSS meh

Nothing like a massive table, scored by base, impact, exploitability, temporal, environmental, modified impact, and overall scores, all assessed by a third party assessor who may not fully understand the complexities or nuances of your environment. Let's say our esteemed assessor has decided that there are 683 total findings, of which 444 are non-critical and 239 are critical. Will FFTrees agree? Nay! First, a wee bit of R code.

library("FFTrees") cvss cvss.fft plot(cvss.fft, what = "cues") plot(cvss.fft,      main = "CVSS FFT",      decision.names = c("Non-Critical", "Critical"))

Guess what, the model landed right on impact and exploitability as the most important inputs, and not just because it's logically so, but because of their position when assessed for where they fall in the area under the curve (AUC), where the specific curve is the receiver operating characteristic (ROC). The ROC is a "graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied." As for the AUC, accuracy is measured by the area under the ROC curve where an area of 1 represents a perfect test and an area of .5 represents a worthless test. Simply, the closer to 1, the better. For this model and data, impact and exploitability are the most accurate as seen in Figure 7.

Figure 7: Cue rankings prefer impact and exploitability

The fast and frugal tree made its decision where impact and exploitability with scores equal or less than 2 were non-critical and exploitability greater than 2 was labeled critical, as seen in Figure 8.

Figure 8: The FFT decides

Ah hah! Our FFT sees things differently than our assessor. With a 93% average for performance fitting (this is good), our tree, making decisions on impact and exploitability, decides that there are 444 non-critical findings and 222 critical findings, a 17 point differential from our assessor. Can we all agree that mitigating and remediating critical findings can be an expensive proposition? If you, with just a modicum of data science, can make an authoritative decision that saves you time and money without adversely impacting your security posture, would you count it as a win? Yes, that was rhetorical. ->->

Note that the FFTrees function automatically builds several versions of the same general tree that make different error trade-offs with variations in performance fitting and false positives. This gives you the option to test variables and make potentially even more informed decisions within the construct of one model. Ultimately, fast frugal trees make very fast decisions on 1 to 5 pieces of information and ignore all other information. In other words, "FFTrees are noncompensatory, once they make a decision based on a few pieces of information, no additional information changes the decision."

Finally, let's take a look at monitoring user logon anomalies in high volume environments with Time Series Regression (TSR). Much of this work comes courtesy of Eric Kapfhammer, our lead data scientist on our Microsoft Windows and Devices Group Blue Team. The ideal Windows Event ID for such activity is clearly 4624: an account was successfully logged on. This event is typically one of the top 5 events in terms of volume in most environments, and has multiple type codes including Network, Service, and RemoteInteractive.

User accounts will begin to show patterns over time, in aggregate, including:

Seasonality: day of week, patch cycles, 

Trend: volume of logons increasing/decreasing over time

Noise: randomness

You could look at 4624 with a Z-score model, which sets a threshold based on the number of standard deviations away from an average count over a given period of time, but this is a fairly simple model. The higher the value, the greater the degree of “anomalousness”.

Preferably, via Time Series Regression (TSR), your feature set is more rich:

Statistical method for predicting a future response based on the response history (known as autoregressive dynamics) and the transfer of dynamics from relevant predictors

Understand and predict the behavior of dynamic systems from experimental or observational data

Commonly used for modeling and forecasting of economic, financial and biological systems

How to spot the anomaly in a sea of logon data?

“Triple Exponential Smoothing (Holt-Winters method) is one of many algorithms used to forecast data points in a series, provided that the series is “seasonal”, i.e. repetitive over some period.”

Winters improved on Holts double exponential smoothing by adding seasonality in 1960 and published Forecasting sales by exponentially weighted moving averages 

Let's imagine our user, DARPA-549521, in the SUPERSECURE domain, with 90 days of aggregate 4624 Type 10 events by day.

Figure 9: User logon data

With 210 line of R, including comments, log read, file output, and graphing we can visualize and alert on DARPA-549521's data as seen in Figure 10. 

Figure 10: User behavior outside the confidence interval

We can detect when a user’s account exhibits  changes in their seasonality as it relates to a confidence interval established (learned) over time. In this case, on 27 AUG 2017, the user topped her threshold of 19 logons thus triggering an exception. Now imagine using this model to spot anomalous user behavior across all users and you get a good feel for the model's power. Eric points out that there are, of course, additional options for modeling including:

Seasonal and Trend Decomposition using Loess (STL)

Handles any type of seasonality ~ can change over time

Smoothness of the trend-cycle can also be controlled by the user

Robust to outliers

Classification and Regression Trees (CART)

Supervised learning approach: teach trees to classify anomaly / non-anomaly

Unsupervised learning approach: focus on top-day hold-out and error check

Neural Networks

LSTM / Multiple time series in combination

These are powerful next steps in your capabilities, I want you to be brave, be creative, go forth and add elements of data science and visualization to your practice. R and Python are well supported and broadly used for this mission and can definitely help you detect attackers faster, contain incidents more rapidly, and enhance your in-house detection and remediation mechanisms. All the code as I can share is here; sorry, I can only share the TSR example without the source. All the best in your endeavors! Cheers...until next time.

The post toolsmith #129 – DFIR Redefined: Deeper Functionality for Investigators with R – Part 2 appeared first on Security Boulevard.

from toolsmith #129 – DFIR Redefined: Deeper Functionality for Investigators with R – Part 2

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[expomahal-blog]

Polymers In Footwear 2019 at Germany(Berlin) 2019-November

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SecureWorld - Seattle 2019 at United States(Seattle) 2019-November

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related products/services/industry/business. This trade show opens top business opportunities to exhibit products and services from leveraging big data analytics for business value Shows, evolving analytics in financial services beyond regulatory compliance business, developing analytical capability Trade Shows, machine learning Trade Fairs, deep learning and artificial intelligence for strategic innovation. Meetings, managers Expos, ceo companies list, coo network, directors business opportunities, vp's contacts list, key decision makers business opportunities industry.

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We help you to grow your business by providing the required contact details of all companies participating in this event and you can download the same data in excel format using the above links. Location of the Event:United States(Seattle) Year-Month:2019-November Official Website:Event Website source https://www.expomahal.com/2019/10/polymers-in-footwear-2019-at.html