Visitors

Sunday, November 26, 2017

High-speed quantum encryption could stop hackers: Study

WASHINGTON: To fight back against the common security attacks, scientists have created a high-speed encryption system to stop hackers.

The system is capable of distributing encryption codes at megabit-per-second rates, five to 10 times faster than existing methods and on par with current internet speeds when running several systems in parallel.

In a study, published in the journal Science Advances, the researchers demonstrate that the technique is secure from common attacks, even in the face of equipment flaws that could open up leaks.

"We are now likely to have a functioning quantum computer that might be able to start breaking the existing cryptographic codes in the near future," said Daniel Gauthier, from The Ohio State University in the US.

"We really need to be thinking hard now of different techniques that we could use for trying to secure the internet," he said.

To a hacker, our online purchases, bank transactions and medical records all look like gibberish due to ciphers called encryption keys.

Personal information sent over the web is first scrambled using one of these keys, and then unscrambled by the receiver using the same key.

For this system to work, both parties must have access to the same key, and it must be kept secret.

Quantum key distribution (QKD) takes advantage of one of the fundamental properties of quantum mechanics - measuring tiny bits of matter like electrons or photons automatically changes their properties - to exchange keys in a way that immediately alerts both parties to the existence of a security breach.

Though QKD was first theorised in 1984 and implemented shortly thereafter, the technologies to support its wide-scale use are only now coming online.

The problem with many of these systems, said Nurul Taimur Islam, from the Duke University in the US, is that they can only transmit keys at relatively low rates - between tens to hundreds of kilobits per second - which are too slow for most practical uses on the internet.

Like many QKD systems, Islam's key transmitter uses a weakened laser to encode information on individual photons of light. But they found a way to pack more information onto each photon, making their technique faster.


By adjusting the time at which the photon is released, and a property of the photon called the phase, their system can encode two bits of information per photon instead of one.

This trick, paired with high-speed detectors developed by Clinton Cahall, from the Duke University, powers their system to transmit keys five to 10 times faster than other methods.


"It was changing these additional properties of the photon that allowed us to almost double the secure key rate that we were able to obtain if we hadn't done that," said Gauthier.

BlackBerry Expands Embedded Software Design and Delivery with New Partners in Japan

Fujisoft and Hitachi Industry & Control join BlackBerry Partner Program to deliver safety-critical and secure software solutions for Japanese industry
TOKYO, JAPAN and WATERLOO, ONTARIO--(Marketwired - Nov. 21, 2017) - BlackBerry Limited (NYSE:BB)(TSX:BB) today announced it is expanding its network of embedded technology experts with two new partners in Japan - Fujisoft Incorporated and Hitachi Industry & Control Solutions, Ltd. The companies have joined a new, specialized Value-Added Integrator (VAI) program announced by BlackBerry in March 2017, which aims to build a worldwide network of experts trained on BlackBerry QNX and Certicom technologies. The VAI program allows partners to deliver integration services and build upon BlackBerry's embedded technologies to design and develop secure, mission-critical solutions - ultimately accelerating product time to market.
Kaivan Karimi, senior vice president and head of sales for BlackBerry Technology Solutions says, "Japan is at the cutting edge of the Internet of Things and embedded software systems, which presents a significant opportunity for companies delivering security and software solutions in industries such as automotive, manufacturing and healthcare. By using trusted BlackBerry software and cryptography-based solutions, companies around the world can develop safety-certified embedded systems and devices that are not just secure, but BlackBerry Secure. We are very pleased to grow BlackBerry's VAI partner program with Fujisoft and Hitachi Industry & Control, and look forward to helping their customers to further accelerate the design, development, integration and testing of mission-critical, next-generation systems in Japan and around the world."
VAI partners in the program provide support for technologies and services including BlackBerry's QNX Neutrino Realtime OS, QNX Momentics Tool Suite, QNX Hypervisor, QNX SDK for Apps & Media, QNX Wireless Framework, QNX OS for Safety, QNX OS for Medical, QNX CAR Platform for Infotainment, QNX Platform for Acoustics, and QNX Platform for ADAS, Certicom Toolkits, Certicom Managed Public Key Infrastructure and Certicom Asset Management System. Applications include automotive systems, medical surgical robots, smart grids, train control systems and industrial automation.
"Fujisoft provides one stop solutions from hardware to middleware and to application development, taking advantage of over 45 years of development experience in the automotive, medical equipment, industrial equipment and consumer markets. With the participation in the VAI program at this time, we further strengthen our technical cooperation with BlackBerry QNX. Fujisoft with more than 6,000 engineers, offers complete technologies and services with reliable expertise for customer system development that requires safety and high reliability," said Masaki Shibuya, Director & Executive Operating Officer of Fujisoft.
"Hitachi Industry & Control is pleased to be able to participate in BlackBerry's global VAI program. Hitachi Industry & Control is a mainstay company supporting the Hitachi group's industrial solution business, providing solutions to a wide range of industrial, security and embedded fields. Collaborating our advanced embedded technologies such as camera application, image processing, robotics, network, functional safety, design platform utilization with the highly secure and safe BlackBerry QNX embedded platform, Hitachi Industry & Control will contribute to customers' development and business expansion," said Shin Nakano, General Manager, Embedded Systems Engineering Group of Hitachi Industry & Control.
Other partners participating in the VAI program include: Archermind TechnologyMcloudwareMicon GlobalMission EmbeddedThunderSoftWitekio Corporation and Tata Elxsi, all of whom are working with BlackBerry to accelerate innovation in sophisticated and secure mission critical embedded systems.
To learn about VAI program, please visit: https://ca.blackberry.com/partners.
About BlackBerry
BlackBerry is a cybersecurity software and services company dedicated to securing the Enterprise of Things. Based in Waterloo, Ontario, the company was founded in 1984 and operates in North America, Europe, Asia, Australia, Middle East, Latin America and Africa. The Company trades under the ticker symbol "BB" on the Toronto Stock Exchange and New York Stock Exchange. For more information, visit www.BlackBerry.com.
BlackBerry and related trademarks, names and logos are the property of BlackBerry Limited and are registered and/or used in the U.S. and countries around the world. All other marks are the property of their respective owners. BlackBerry is not responsible for any third-party products or services.

Cyber Security Firms Turn To Artificial Intelligence As Hacking Threats Rise

Machine learning can be used to detect suspicious behavior and minimise threats to cyber networks.


Helsinki: Cyber security companies are turning to artificial intelligence and machine learning tools to ward off growing number of attacks on networks, Finland-based internet security firm F-Secure said.

As the world is fast moving towards Internet of Things and connected devices, deployment of artificial intelligence (AI) has become inevitable for cyber security firms to analyse huge amount of data to save networks from infiltration attempts, F-Secure's Security Advisor Sean Sullivan said. Networks are persistently exposed to threats like malware, phishing, password breaches and denial of service attacks.

On a daily basis, F-Secure Labs on an average receives sample data of 500,000 files from its customers that include 10,000 malware variants and 60,000 malicious URLs for analysis and protection, Sullivan said. 

For humans, it is a big task to go through such huge amount of data and machine learning tools and AI are lending a helping hand at this stage, he said.

Machine learning can be used to train logic designed to detect suspiciousness based on the structure of a file or its behaviour or both, another Security Advisor Andy Patel said.

Sullivan said any abnormal behaviour of a file is flagged by AI which helps in detecting threats at an early stage without much damage being done to the network.

Patel claimed behaviour models enable them to take preemptive steps to save their customers from ransomware attacks like 'Locky'.

When asked if machine tools and AI can make people's jobs in cyber security redundant, Patel said it is unlikely as attacks through malwares are designed by humans who think creatively to bypass automated security solutions. So, there is need of humans who can think creatively to defend networks from such attacks.

He also said AI and machine learning are at an evolving stage and there is a long way to go for widespread adoption of such tools in cyber security as only big players at present can afford building such systems and improving them every day.

Saturday, November 25, 2017

History of artificial intelligence

The history of Artificial Intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with "an ancient wish to forge the gods."
The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.
The field of AI research was founded at a workshop held on the campus of Dartmouth College during the summer of 1956. Those who attended would become the leaders of AI research for decades. Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation and they were given millions of dollars to make this vision come true.
Eventually it became obvious that they had grossly underestimated the difficulty of the project due to computer hardware limitations. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence, and the difficult years that followed would later be known as an "AI winter". Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned by the absence of the needed computer power (hardware) and withdrew funding again.
Investment and interest in AI boomed in the first decades of the 21st century, when machine learning was successfully applied to many problems in academia and industry due to the presence of powerful computer hardware. As in previous "AI summers", some observers (such as Ray Kurzweil) predicted the imminent arrival of artificial general intelligence: a machine with intellectual capabilities that exceed the abilities of human beings.

Precursors 

McCorduck (2004) writes "artificial intelligence in one form or another is an idea that has pervaded Western intellectual history, a dream in urgent need of being realized," expressed in humanity's myths, legends, stories, speculation and clockwork automatons.

AI in myth, fiction and speculation

Mechanical men and artificial beings appear in Greek myths, such as the golden robots of Hephaestus and Pygmalion's Galatea.In the Middle Ages, there were rumors of secret mystical or alchemical means of placing mind into matter, such as Jābir ibn Hayyān's Takwin, Paracelsus' homunculus and Rabbi Judah Loew's Golem.By the 19th century, ideas about artificial men and thinking machines were developed in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R. (Rossum's Universal Robots), and speculation, such as Samuel Butler's "Darwin among the Machines." AI has continued to be an important element of science fiction into the present.


Artificial intelligence (AI)

Artificial intelligence (AI, also machine intelligence, MI) is Intelligence displayed by machines, in contrast with the natural intelligence (NI) displayed by humans and other animals. In computer science AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip "AI is whatever hasn't been done yet."For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology. Capabilities generally classified as AI as of 2017 include successfully understanding human speech, competing at a high level in strategic game systems (such as chess and Go), autonomous cars, intelligent routing in content delivery networks, military simulations, and interpreting complex data, including images and videos.
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,followed by disappointment and the loss of funding (known as an "AI winter"),followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other.
The traditional problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate objects.General intelligence is among the field's long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, neural networks and methods based on statistics, probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience, artificial psychology and many others.
The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it". This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence, issues which have been explored by myth, fiction and philosophy since antiquity. Some people also consider AI a danger to humanity if it progresses unabatedly.
In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science.

Friday, November 24, 2017

Hi,Our Subscribers today our talking will be about the Security in AI and Its important role 
stay tuned ;)

Monday, October 2, 2017

Relentless Cyber Attacks Make These A Screaming Buy

President Donald Trump’s bed-ridden, 400-pound hackerand his friends have been relentless in making 2017 a banner year for digital disruption of the worst kind. In light of the cyber attack pandemic -- Equifax breachWannaCryPetya --  cybersecurity companies are a screaming buy for long-term investors. There’s no better time to invest than October as it is National Cyber Security Awareness Month.

Each new trend in technology – cloud computing, big data, internet of things – creates new weaknesses for hackers to exploit with malware, ransomware, leakware. The two exchange-traded funds to invest in the hottest tech sector are ETFMG Prime Cyber Security ETF with the symbol HACK, formerly called PureFunds ISE Cyber Security ETF; and First Trust NASDAQ Cybersecurity ETF, which trades under the ticker CIBR.


“The internet security market is an attractive area even during recessionary times because of the increasing online traffic,” Zacks Equity Research wrote in a report about Symantec Sept. 21.

Double-Digit Growth Rate




“The major forces driving the cybersecurity market are strict data protection directives and cyber terrorism,” Markets and Markets said in a report. “The cybersecurity market is growing rapidly because of the growing security needs of internet-of-things (IoT) and bring-your-own-device (BYOD) trends, and increased deployment of web and cloud-based business applications.”


Gartner forecasts the number of Internet-connected devices will expand from 8.4 billion worldwide in 2017 to 20.4 billion by 2020. Total consumer and business spending on IoT devices globally is projected to vault from $1.7 trillion in 2017 to nearly $3 trillion in 2020.

The need to better detect and respond to security breaches has created a new class of security products such as deception, endpoint detection and response (EDR), software-defined segmentation, cloud access security brokers (CASBs), and user and entity behavior analytics (UEBA), according to Gartner, a global research and advisory firm.
“These new segments are creating net new spending, but are also taking spend away from existing segments such as data security, enterprise protection platform (EPP) network security and security information and event management (SIEM),” Gartner wrote in a report.
In May, President Trump signed an executive order in hopes of improving U.S. cybersecurity in the wake of huge data breaches at the Office of Personnel Management and the Internal Revenue Service. The order called for federal agencies to review their security systems and update antiquated systems.
A 2017 survey of security industry vendors and practitioners conducted by Thales, a data security firm, found that more than two in three respondents, 67.8%, said their organizations were breached at one point, a jump of nearly 7% over the prior year. More than one in four, 26%, were breached in the last year, up from 22% the previous year. A majority of respondents, 88%, feel vulnerable to data threats. Some 73% of respondents expect security spending hikes in the next 12 months, a sharp rise from 58% last year.

HACK Vs. CIBR

ETFMG Prime Cyber Security ETF, the first to market and larger of the two funds with $1.1 billion under management, rose 13% year to date, through Sept. 30, according to Morningstar. First Trust NASDAQ Cybersecurity ETF, with $314 million in assets, climbed 14% year to date. Their returns were on par with the stock market but they lagged the tech sector.
SPDR S&P 500 ETF returned 14% year to date. The biggest tech ETF, Technology Select Sector SPDR® Fund, vaulted 24% the first three-quarters of the year.