1. Secure access control. With a unique verifiable identity, you can determine what level of access to grant to that device. In addition, you can now deny access to anyone who does not have a proper certificate – no cert, no way. In addition, if you find out a certificate has been somehow compromised because it is unique and identifiable, you can revoke its access privileges and that certificate will no longer be granted access.
2. Mutual Authentication. In the days before IoT and autonomous networked devices, the device didn’t need to be authenticated, just the servers. You wanted to make sure that the website you were logging into was actually a bank and not some bogus phishing site. The bank authenticated your identity through your login and password. With IoT, the device needs to be authenticated and the device also needs to authenticate the server it is talking to. With digital certificates and secure elements, this is now practical.
3. Secure Over-the-Air (OTA) Update. The problem with many devices today is that they will accept software updates from anyone. Remember, you want a device to only accept software that is verified and comes from a trusted server. The certificates allow the device to prove it should receive an update and which one, and the cryptography in the secure element allows the device to verify the server as well as the signed code.

As you can see, combined with digital certificates, PKI enables a trusted environment for robust identity protection by authenticating the identity of a device and assuring the integrity of that device.

Reference: https://www.kyrio.com/blog/3-benefits-public-key-infrastructure-pki/

Govt plans to use AI tools for digital forensics. The government is planning to use artificial intelligence-based tools for a digital forensics project currently underway at the Centre for Development of Advanced Computing (C-DAC), said a report in The Economic Times.

The report said that the C-DAC is planning to use artificial intelligence to look out for threats before they breach systems and track hackers to stop repeated breaches. The digital forensics arm of the C-DAC will help small and medium firms roll out commercial solutions for cyber threats, it added.

Finance minister Arun Jaitley had, in last year’s budget speech, said that the C-DAC, in collaboration with Indian Computer Emergency Response Team (CERT-In), would look to develop tools to tackle cybersecurity issues. He had also said that CERTs for different sectors, especially the financial sector, were being contemplated.

After Jaitley’s speech, Union minister for electronics and information technology Ravi Shankar Prasad had said that the C-DAC was working on digital forensics, a branch of forensic science that deals with recovering and analysing information from data storage devices including computers, phones and networks.

The report said that the digital forensics project has a budget of Rs 3.95 crore and that, apart from the C-DAC, the Indian Institute of Technology, Patna will also be involved in its implementation.

The report cited a senior government official as saying that the project will help the C-DAC research on cybersecurity for two years before starting out training programmes for government officials in the field.

The Indian government has taken a number of initiatives in recent years to boost cybersecurity.

Last month, the government said its botnet malware apps had reduced infections in the country by at least 51% after their launch on the web and the Google Play Store in February 2017.

The government had launched the Cyber Swachhta Kendra (Botnet Cleaning and Malware Analysis Centre) under CERT-In in February last year. The government had also launched apps such as AppSamvid, USB Pratirodh and M-Kavach on Google Play Store and on the web to help detect and remove botnet malware, in the same period.

Reference: http://techcircle.vccircle.com/2018/02/15/govt-plans-to-use-ai-tools-for-digital-forensics-report

There are many more possible moves in a Go game than a chess match

Google’s DeepMind says it has made another big advance in artificial intelligence by getting a machine to master the Chinese game of Go without help from human players.

The AlphaGo program, devised by the tech giant’s AI division, has already beaten two of the world’s best players.

It had started by learning from thousands of games played by humans.

But the new AlphaGo Zero began with a blank Go board and no data apart from the rules, and then played itself.

Within 72 hours it was good enough to beat the original program by 100 games to zero.

DeepMind’s chief executive, Demis Hassabis, said the system could now have more general applications in scientific research.

“We’re quite excited because we think this is now good enough to make some real progress on some real problems even though we’re obviously a long way from full AI,” he told the BBC and other journalists.

The London-based artificial intelligence company’s software defeated leading South Korean Go player Lee Se-dol by four games to one last year.

In a game where there are more possible legal board positions than there are atoms in the universe, it was a triumph for machine over man and one that came much earlier than many in the AI world had expected.

AlphaGo followed this with the defeat of the world’s number one Go player, China’s Ke Jie, in May.

As with many advances in this field, the achievements required the combination of vast amounts of data – in this case records of thousands of games – and a lot of computer-processing power.

David Silver, who led that effort, says the team took a very different approach with AlphaGo Zero.

“The new version starts from a neural network that knows nothing at all about the game of Go,” he explained.

“The only knowledge it has is the rules of the game. Apart from that, it figures everything out just by playing games against itself.”

What is Go?

Go is thought to date back to ancient China, several thousand years ago.

Using black and white stones on a grid, players gain the upper hand by surrounding their opponents’ pieces with their own.

The rules are simpler than those of chess, but a player typically has a choice of 200 moves at most points in the game, compared with about 20 in chess.

It can be very difficult to determine who is winning, and many of the top human players rely on instinct.

This has turned out to be far more efficient way of addressing the problem.

Whereas AlphaGo took months to get to the point where it could take on a professional, AlphaGo Zero got there in just three days, using a fraction of the processing power.

“It shows it’s the novel algorithms that count, not the compute power or the data,” says Mr Silver.

He enthuses about an idea some may find rather scary – that in just a few days a machine has surpassed the knowledge of this game acquired by humanity over thousands of years.

“We’ve actually removed the constraints of human knowledge and it’s able, therefore, to create knowledge itself from first principles, from a blank slate,” he said.

Image copyright Moxie Pictures Image caption Google DeepMind’s defeat of champion Go player Lee Se-dol has been made into a documentary

Whereas earlier versions quickly learned from and improved upon human strategies, AlphaGo Zero developed techniques which the professional player who advised DeepMind said he had never seen before.

Many of the team have now moved on to new projects where they are trying to take this technique to new areas. Demis Hassabis mentions drug design and the discovery of new materials as areas of interest.

Whereas some see a threat from AI, he looks ahead with optimism.

“I hope these kind of algorithms will be routinely working with us as scientific experts medical experts on advancing the frontiers of science and medicine – that’s what I hope,” he says.

But he and his colleagues are cautious about how rapidly we will see the wider application of these AI techniques – a game with clear rules and no element of luck is one thing, the messy, random, unpredictable real world quite another.

We need to keep a close eye on the ethical dilemmas involved in developing a machine that, by some definitions, can think for itself – especially when it is controlled by a giant like Google.

But for now, there are few signs that AlphaGo Zero and its ilk will either steal our jobs or threaten to make humanity obsolete.

Reference: BBC news