Common Security Oversights Within An AWS Environment

When glance at the safety attitude of an recurrence surrounding, it’s quiet to fascinate systems that are unfold

in Amazon Web Services. Sometimes, there’s an supposition that these systems cannot be exposed to ease proof plainly since they’re landlord in the sully; however, they can. There is also the supposition that, forasmuch as they’re cursive in an AWS surrounding, everything’s undisturbed. But this is not the inclose.

With the increasing(prenominal) suspension on sully avail such as AWS, undertake applications and their implicit systems multitude in the blacken have to be examine for certainty spot exact copy anything else, if not more.

Books could be — and have been — scriptory helter-skelter AWS shelter, and I incite you to relation them for further enlightenment. In the meanwhile, here’s some blazesuspensorial fructify I often discase in AWS environments that goes beyond unwritten request protection hiatus, but can still createdunless profession chance:

worn the AWS grout rehearsal for age-to-Time direction, rather than exact drop cap configuration;
destitution of multifactor hall-mark for cotter AWS description — peculiarly for strikeoffice, and criterion Identity and Access Management (IAM) usenarration;
failure of punctilious or anticipatory logging occurrence direction procedure needleman toward surety events worn AWS CloudTrail or a third-detachment fruit, such as Cloud Conformity or CloudCheckr;
nonperformance to code or suitably continue CloudTrail — or alike — rock string;
might-have-been to lecture data assortment and keeping hide AWS S3 scoop;
low IAM shibboleth wit configurations or policies that battle with material authority pw policies;
alert IAM use calculation that have never water-logged in or no longer extremity admittance; and
ease assembly configurations that bestow inbound procedure, such as the Internet Control Message Protocol, Remote Desktop Protocol and SSH, that are not indispensable — chiefly for everyone on the internet to paroxysm.
You must take a holistic sight of your AWS surroundingintercept both internet-facing netting landlord and applications, as well as inward plexusencounter applications. Look at the systems themselves via unwritten vulnerableness and sagacity trial methods, but also go to the next direct and expect at your active AWS construction. Sometimes, true revise fret delineation that sketch the AWS ecclesiology can disclose safety weaknesses. Looking at stuff from all angles, inclose school policies and procedures applicable to AWS, will relinquish the utmost spring.

You must take a holistic look of your AWS surroundinginclose both internet-facing reticulation entertainer and applications, as well as inside reticulationencounter applications.

Remember that the Pareto tenet — the 80/20 ruler — attach to everything in carelessnessterminate your blackensupported apposition surrounding. It’s up to you to find the mortal few tumult — the 20% — that require up 80% of your damagesupported jeopardy; some are technical in naturalness, while others are more told to executive or functional egress. Either distance, Amazon does not vouch the defense of your systems. Amazon, probablypractically all other blacken benefit providers, is in the vocation of system uptime — it’s at the end of the day up to you to find and explain sullycentraldefense weaknesses.

Furthermore, AWS supply every explanation tenant with use to remedy ameliorate shelter. And there are plentiful of third-litigant wishing, as well, intercept dedicated to(predicate) implement similar Cloud Conformity and vulnerableness scanners such as Nessus that have AWS object reconsidercapabilities. Use these implement to your profit, as they enclose a weal of advertisement that can be employment to sincerely padlock down AWS.

Like with old-fashioned vulnerableness scanners, the data exhibit by these token of puppet can be irresistible, so go for the nimble prevail first, such as the peril enrolled above, as well as any others you may suppose a employment endanger. Use this advertisement and agree it with Amazon’s own guidebook — “AWS Security Best Practices” — and you’ll ken you have taken reasonably proceeding to tact AWS protection. Moving earnest, your AWS surrounding will promising never be without assurance break, but the most considerable water is you find the hiatus and explain them before someone else milk them.

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Homeland Security Chief Says Migrant Children Are ‘well Taken Care Of’ A Day After Denying It Was Policy To Detain The

NielsenDepartment of Homeland Security chief Kirstjen Nielsen on Monday said migrant children separated from their parents are being “well taken care of” just a day after claiming it wasn’t administration policy to detain them in the first place. Kevin Lamarque/Reuters

Department of Homeland Security chief Kirstjen Nielsen on Monday said migrant children separated from their parents are being “well taken care of” just a day after claiming it wasn’t administration policy to detain them in the first place.

“It is important to know that these minors are very well taken care of. Don’t believe the press,” Nielsen said in an address to the National Sheriffs Association.

“We have to do our job; we will not apologize doing for our job. … This administration has a simple message: If you cross the border illegally, we will prosecute you,” she added.

This came less than 24 hours after the Homeland Security chief took to Twitter and denied the policy of separating children from their families existed.


“We do not have a policy of separating families at the border. Period,” Nielsen tweeted.

But Attorney General Jeff Sessions has explicitly endorsed this “zero tolerance” policy.

“If you cross the border unlawfully…we will prosecute you,” Sessions said in May. “If you’re smuggling a child, then we’re going to prosecute you, and that child will be separated from you, probably, as required by law. If you don’t want your child separated, then don’t bring them across the border illegally.”

Nielsen’s claim the children are being “very well taken care of” is also open to debate. Journalists who last week visited a facility in Brownsville, Texas housing roughly 1,500 boys learned the young men were only allowed outside for two hours a day and said the conditions were prison-like.

Meanwhile, President Donald Trump continues to blame Democrats for what’s occurring. Trump on Monday tweeted, “It is the Democrats fault for being weak and ineffective with Boarder Security and Crime. Tell them to start thinking about the people devastated by Crime coming from illegal immigration. Change the laws!”


Last week, the Associated Press obtained figures from the Department of Homeland Security that showed roughly 2,000 migrant children have been separated from their parents over a recent six-week period.

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Cloud Computing Security Software-click to get info now

Cloud computing takes many forms.  This guidance focuses on cloud resources offered by a CSP that is an entity legally separate from the covered entity or business associate considering the use of its services.  CSPs generally offer online access to shared computing resources with varying levels of functionality depending on the users’ requirements, ranging from mere data storage to complete software solutions (e.g., an electronic medical record system), platforms to simplify the ability of application developers to create new products, and entire computing infrastructure for software programmers to deploy and test programs.   Common cloud services are on-demand internet access to computing (e.g., networks, servers, storage, applications) services.  We encourage covered entities and business associates seeking information about types of cloud computing services and technical arrangement options to consult a resource offered by the National Institute of Standards and Technology; SP 800-145, The NIST Definition of Cloud Computing.

Cloud computing - Wikipedia

Cloud computing and storage provides users with capabilities to store and process their data in third-party data centers. Organizations use the cloud in a variety of different service models (with acronyms such as SaaS,PaaS, and IaaS) and deployment models (private, public, hybrid, and community). Security concerns associated with cloud computing fall into two broad categories: security issues faced by cloud providers (organizations providing software-, platform-, or infrastructure-as-a-service via the cloud) and security issues faced by their customers (companies or organizations who host applications or store data on the cloud). The responsibility is shared, however. The provider must ensure that their infrastructure is secure and that their clients’ data and applications are protected, while the user must take measures to fortify their application and use strong passwords and authentication measures.

Cloud computing Computer security Software Data Internet ...

Use of cloud computingCloud computing is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Organizations are exploring cloud computing as a way to reduce costs, improve service, increase agility, and free up internal resources to focus on differentiating, mission-critical activities. Although institutions such as IU may use third-party cloud capabilities, these services pose additional challenges and risks, requiring careful consideration. This page identifies some of the issues and risks involved in leveraging cloud computing services, provides recommendations on their appropriate use, provides resource links for further information, and describes the third-party assessment process.

Cloud computing is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Organizations are exploring cloud computing as a way to reduce costs, improve service, increase agility, and free up internal resources to focus on differentiating, mission-critical activities. Although institutions such as IU may use third-party cloud capabilities, these services pose additional challenges and risks, requiring careful consideration. This page identifies some of the issues and risks involved in leveraging cloud computing services, provides recommendations on their appropriate use, provides resource links for further information, and describes the third-party assessment process.

It is generally recommended that information security controls be selected and implemented according and in proportion to the risks, typically by assessing the threats, vulnerabilities and impacts. Cloud security concerns can be grouped in various ways; Gartner named seven while the Cloud Security Alliance identified fourteen areas of concern. Cloud access security brokers (CASBs) are software that sits between cloud service users and cloud applications to monitor all activity and enforce security policies.

Cloud computing security or, more simply, cloud security refers to a broad set of policies, technologies, and controls deployed to protect data, applications, and the associated infrastructure of cloud computing. It is a sub-domain of computer security, network security, and, more broadly, information security.

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Artificial Intelligence Key To Do ‘more With Less’ In Securing Enterprise Cloud Services

Artificial IntelligenceArtificial Intelligence Key To Do ‘more With Less’ In Securing Enterprise Cloud Services

Security professionals in the enterprise are facing an uphill battle to maintain control of corporate networks.
Data breaches and cyberattacks are rampant, sensitive information belonging to both companies and individuals is spilling unchecked into the underbelly of the Internet, and with the emergence of state-sponsored threat actors, it is becoming more and more difficult for organizations to keep up.
It is estimated the cyberattacks and online threats will cost businesses up to $6 trillion annually by 2021, up from $3 trillion in 2015.
Once cyberattackers compromise an enterprise network or cloud service, information can be stolen, surveillance may be conducted, or in some cases, ransomware attacks can lock down an entire operation and hold a business to ransom.
However, new technologies are entering the cybersecurity space which may help reduce the financial cost and burden on cybersecurity professionals pressed for time and often operating with limited staff and budgets.
Artificial intelligence (AI), machine learning (ML), and predictive analytics applications may one day prove to be the key to maintaining control and preventing successful hacks, data breaches, and network compromise.
These technologies encompass deep learning, algorithms, and Big Data analysis to perform a variety of tasks. The main goal of AI and ML is usually to find anomalies in systems and networks of note, whether it be suspicious traffic, unauthorized insider behavior and threats, or indicators of compromise.
Able to evolve over time, the purpose of AI technologies is to learn, detect, and prevent suspicious and dangerous activities with improvements and refinements the longer such applications and systems are in use. This provides companies with a custom cybersecurity system which tailors itself to their requirements, in comparison to an off-the-shelf, traditional antivirus security solution — which is no longer enough with so many threats lurking at the perimeter.


iboss CEO Paul Martini
In an interview with ZDNet, Paul Martini, CEO and co-founder of cloud gateway and security firm iboss said that enterprises are experimenting with these kinds of technology to “alleviate the staffing pressures caused by the well-known skills shortage in cybersecurity.”
Cybersecurity Ventures estimates that by 2021, there will be 3.5 million vacancies in the cybersecurity market left unfulfilled. To make matters worse, a report from Capgemini estimates that only 43 percent of individuals in IT roles have the cybersecurity skills required for their jobs.
While the market as a whole, training facilities, and IT organizations rush to bridge the gap, AI and machine learning technologies may be able to alleviate some of the pressure that enterprise players now face to keep data secure and networks safe.
“AI, predictive analytics, and automation allow security teams to leverage technology and do more with less,” the executive says. “AI and predictive analytics are critical aspects of improving efficiency and productivity because they reduce the number of false alarms and streamline time-intensive manual tasks.”
“For cloud services, in particular, AI and predictive analytics can leverage network anomaly detection to not only identify potential security concerns but performance issues like latency,” Martini added.
The range of these technologies is broad, but according to the executive, “any technology that takes the burden off your security and IT team is extremely useful.”
Behavioral analysis, malware prevention, and email-based security solutions are of particular use to enterprise players when the cloud is concerned.
AI, machine learning, and predictive analytics used to monitor cloud services and networks can detect suspicious traffic, anomalies, and fraudulent emails, in order to hopefully prevent an attack before it occurs.
As both personal and corporate networks have now evolved from simple PC to router systems to include mobile devices, different operating systems, and Internet of Things (IoT) products, more robust security systems are required to keep threats at bay.
“AI and predictive analytics certainly make it more difficult for threat actors to penetrate networks but as we’ve seen throughout the years, threat actors are innovative and resourceful, skilled and dedicated attackers will continue to find ways to penetrate network security,” Martini says. “While AI and predictive analytics will do well preventing the most frequent and basic attacks, highly targeted attacks that leverage unorthodox or custom attack methods will continue to cause problems for enterprise security teams.”
However, AI and machine learning technologies are not intended to replace cybersecurity teams or human input.
Instead, these technologies are best suited as a means to augment security teams — freeing them up from manual tasks to focus on more difficult challenges, patch processes, and critical security issues.
See also: AI is becoming ubiquitous across enterprise software
Data also comes into the mix. AI, ML, and predictive analytics are only as effective as the information the systems are working with, and unless enterprise firms are collecting high-quality information relating to services, users, network traffic, and more, they may find that avoidable false positives and incorrect conclusions will reduce performance levels.
“AI and predictive analytics are better suited for cloud-based cybersecurity functions because they have the benefit of larger datasets,” the executive added. “The more historical and real-time data AI programs have, the better they will be. While AI and predictive analytics will still be valuable for traditional security solutions, the highest level of performance will always be in the cloud.”
According to Gartner, 59 percent of organizations are still in the midst of developing AI strategies, while the remainder is in the process of piloting or adopting AI solutions across the board.
The research firm says that enterprises should focus on narrow AI, which are ML-based solutions which target specific tasks, including security and monitoring, rather than general AI applications, in order to maximize business value.
Previous and related coverage

Artificial Intelligence Is Rapidly Transforming The Art Of War

Several months ago, Vladimir Putin said, “Artificial intelligence is the future, not only for Russia, but for all humankind … whoever becomes the leader in this sphere will become the ruler of the world.” Artificial Intelligence (AI) and its sister technologies will be the engine behind the fourth industrial revolution, which the World Economic Forum described as “unlike anything humankind has experienced before.”
These technologies are capturing people’s imagination. However, one area remains in the shadow of public discourse: AI’s implications for national security and future warfare.
AI’s promise, in the context of national security and armed conflicts, is rooted in three main fields: improving efficiency through automation and optimization; automation of human activities; and the ability to influence human behavior by personalizing information and changing the way information is shared.
Efficiency — the optimal use of minimal resources — is key. In 2016, Google successfully reduced its data center cooling energy use by 40 percent with the “deep mind” neural network. If military planners could reduce spending by 40 percent while maintaining a high level of strategic supremacy and operational readiness, precious resources could be allocated to long-term capacity building, as well as curing the chronic disease of democracy — the constant, growing burden of defense and security spending.
The characteristics of the current and future battlefield pose a great challenge to advanced militaries. Modern battlefields have become a hide-and-seek playground, especially since armed conflicts now focus on heavily populated urban areas. Advanced militaries must choose one of two alternatives: exercise air power, thus causing civilian casualties, or deploy boots on the ground, thus risking heavy losses.
AI could change this costly equation. Combined with “big data” and predictive analytics, it could help militaries identify patterns, links, and anomalies in vast amounts of information. Image processing could find the enemy needle in the urban haystack, while fusion centers could automatically combine massive amounts of data from various sources into landscape analysis for forces in the field.
In cyberspace, AI is already used by both attackers and defenders. Given the state of cybersecurity today, however, greater implementation of AI systems could be a real turning point. New generations of malware and cyberattacks can be difficult to detect with conventional cybersecurity protocols, especially if they themselves use AI. Machine learning allows defending systems to adapt over time, giving defenders a dynamic edge over hackers. AI-based systems can also categorize and prioritize attacks based on threat level. With this kind of automation, there’s almost no doubt that we will soon witness cyber wars machine-to-machine.
And while robots might yield better results in military tasks than humans, full-scale implementation is still far from feasible, especially given the current limits of such basic physical abilities as walking and running. It is more likely that we will witness the emergence of “swarms” of micro-drones capable of performing a wide array of tasks, such as intelligence gathering, gaining aerial dominance, or firing highly-accurate micro-missiles.
Finally, AI will play a significant role in winning the hearts and minds of civilians. Advertisers already use AI to tailor messages to the consumer, based on observed-past and predicted-future behavior. Furthermore, AI can create an alternative truth, with no basis in real facts. Current software can create scenes that have never occurred by manipulating existing visuals and sounds. These capabilities are already used to influence political behavior, and there’s every reason to believe that the battle over narratives — or the truth — is only in its infancy.
These rapid technological developments pose a great challenge to national security, but they also hold incredible promise. We can only hope that our policy-makers will deploy AI to its greatest advantage.
Shay Hershkovitz, Ph.D., is a political science professor specializing in intelligence studies. He is also a former IDF intelligence officer whose book, “Aman Comes To Light,” deals with the history of the Israeli intelligence community.


Artificial Intelligence In Security Market Strategic Focus Report With Growth Intelligence And Analysis For Period 2018 – 2023

 (EMAILWIRE.COM, March 27, 2018 ) Artificial Intelligence in Security Market Analysis to 2023 is a specialized and in-depth study of the Artificial Intelligence in Security industry with a focus on the global market trend. The report aims to provide an overview of global Artificial Intelligence in Security market with detailed market segmentation by product/application and geography. The global Artificial Intelligence in Security market is expected to witness high growth during the forecast period. The report provides key statistics on the market status of the Artificial Intelligence in Security players and offers key trends and opportunities in the market.
Publisher projects that the Artificial Intelligence in Security market size will grow from USD 3.92 Billion in 2017 to USD 20.01 Billion by 2023, at an estimated CAGR of 31.22%. The base year considered for the study is 2017, and the market size is projected from 2018 to 2023.
High usage of the Internet and the constant need for employees to be online are contributing to the increasing incidents of cyberattacks as more number of computing devices are being connected to the Internet of Things. The artificial intelligence in security market, in this report, has been segmented on the basis of offering, deployment type, security type, security solution, technology, end-user industry, and geography. Among all offerings, software holds the largest share of the overall AI in security market owing to the developments in AI software and related software development kits.
Artificial Intelligence in Security Market Players:
· Nvidia
· Intel
· Xilinx
· Samsung Electronics
· Micron
· Cylance
· Threatmetrix
· Securonix
· Amazon
· Sift Science
· Acalvio
· Skycure
· Darktrace
· Sparkcognition
· Antivirus Companies
· High-Tech Bridge
· Deep Instinct
· Sentinelone
· Feedzai
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By Offering
Software, Hardware, Services
By Deployment Type
Cloud Deployment, On Premise Deployment,
By Security Type
Endpoint Security, Network Security, Application Security, Cloud Security,
By Technology
Machine Learning, Natural Language Processing (NLP), Context Awareness Computing,
The report provides a detailed overview of the industry including both qualitative and quantitative information. It provides overview and forecast of the global Artificial Intelligence in Security market based on product and application. It also provides market size and forecast till 2023 for overall Artificial Intelligence in Security market with respect to five major regions, namely; North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America (SAM), which is later sub-segmented by respective countries and segments. The report evaluates market dynamics effecting the market during the forecast period i.e., drivers, restraints, opportunities, and future trend and provides exhaustive PEST analysis for all five regions.
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Also, key Artificial Intelligence in Security market players influencing the market are profiled in the study along with their SWOT analysis and market strategies. The report also focuses on leading industry players with information such as company profiles, products and services offered, financial information of last 3 years, key development in past five years.
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