The importance of intellectual property rights

It was a while ago that I was reading through an article or a blog that had been published online, and I thought it seemed familiar. Some of the phrases used in it seemed like something I might write. And, in fact, it was a rewrite of a blog that I’d published a little while before. Although parts of it were new, large chunks were pretty much word-for-word what I’d put in my original article. Two questions sprung to mind. Had I lost any money because they’d re-used large parts of my text? How did it make me feel?

In my case, I usually don’t get paid for blogs that are attributed to me. Articles are usually paid for and that often means that someone else has copyright on the text. So, I hadn’t lost any money. When it came to my feelings, I wondered whether I ought to be very cross that someone was passing off my work as their own. Or should I simply be cross because they’d been too lazy to write their own words? Or did I feel quite pleased that they thought my work was so good it was worth copying? The truth was that I felt a strange mix of all three – and did nothing about it. And it has happened more than once since then.

So, no legal fees, no team of lawyers working on my case. Through mental confusion, indolence, and a feeling of powerlessness because the Internet is rife with plagiarism, I did nothing. But don’t take that as permission to steal all my published work!

In 2007, my company started doing some work for Neon Enterprise Software, a software company with some IMS products. In fact, because of that relationship, in December of that year, the very first Virtual IMS user group meeting was held. Neon’s Kristine Harper gave a presentation entitled, “Why Assembler is a 21st century language”.

Neon went on to develop a product which they called zPrime. It allowed users to run applications on IBM specialty processors, zIIP (z Integrated Information Processor) and zAAP (z Application Assist Processor), rather than on the more expensive central processors. There was even a version for IMS. IBM wasn’t best pleased at this because, I assume, they would lose revenue. They told customers not to use it. As a consequence, Neon sued IBM, saying that IBM was unduly restricting users by forcing them to run workloads on more expensive processors. IBM fairly promptly, countersued. They said that Neon was infringing IBM’s patents. Eventually, the argument was settled out of court in 2011, but zPrime was no longer available and eventually Neon ceased trading. However, a US District Court barred Neon and some members of staff from reverse engineering, reverse compiling, and translating certain IBM software. In addition, they were banned from distributing certain Neon software products.

Mark Cresswell is currently the executive chairman of a company called LzLabs. He had been CEO at Neon. Apparently, LzLabs started up in stealth mode in 2011 and launched its first product in 2016.

IBM is now suing LzLabs because LzLab’s software-defined mainframe (SDM) product violates its mainframe patents. What does LzLabs’ product do? It runs mainframe software in the cloud. And it does this more cheaply than running it on a mainframe. You don’t need to be Sherlock Holmes to spot the parallels between these two companies and court cases. IBM claims that Lzlabs uses software that has been reverse engineered from IBM’s products. IBM also says that LzLabs is making false claims about its products.

LzLabs says that SDM uses containerized workloads running on Linux on x86 processors in a cloud environment. And users don’t need to recompile their code. IBM’s argument is that in order to translate mainframe instructions into x86 instructions, LzLabs would have to infringe two IBM patents for doing that. IBM also argues that for LzLabs to claim optimized performance, they must be using methods that IBM holds patents for in order for there to be any kind of increased emulation/translation efficiency.

Patents are a great way to show that you or your company originated a specific way of working. No-one wants other people to steal their ideas and make money out of it. And that means it is perfectly alright for large companies to sue smaller companies that do – or at least seem to – steal their ideas. If you follow Darwin’s ideas of ‘survival of the fittest’, then it simply seems like the natural order of things that larger animals will eat smaller animals.

An alternative view was proposed by Pyotr Kropotkin in his 1902 book, “Mutual Aid: A Factor of Evolution”. His view was that where animals practice mutual aid, they, “are invariably the most numerous, the most prosperous, and the most open to further progress”. He goes on to suggest that, “unsociable species, on the contrary, are doomed to decay”. Kropotkin found that many societies exhibited cooperation among individuals and groups as the norm.

Now I know that Western society has traditionally followed the ‘dog-eat-dog’ approach proposed by Darwin. What I’m suggesting is that mutual aid might be a strategy that’s worth investigating further and possibly adopting. So, rather than IBM destroying its enemies (ie companies that infringe its intellectual property, whether copyrighted or patented or not), perhaps it could work with them to their mutual benefit and the benefit of mainframe-using companies.

Even IBM must recognize that the cloud usage pricing structure is a huge threat to its rolling 4-hour average (R4HA) way of working.

I guess it depends on whether you think thieves should be punished or rehabilitated back into society as useful citizens. There must be a mathematical formula for working out which approach brings the greatest gain, isn’t there?

I’m not saying it’s OK to ‘borrow’ someone else’s work – far from it – I’m just suggesting that sometimes ‘carrots’ work better than ‘sticks’ for the good of the mainframe community.

Sweet (z)16 mainframe

On Tuesday, IBM unveiled its much-trailed new mainframe, the z16, its next-generation system with an integrated on-chip AI accelerator, which delivers latency-optimized inferencing. The accelerator is designed to enable clients to analyze real-time transactions, at scale. So, ideal for mission-critical workloads such as credit card, healthcare, and financial transactions. The z16 is also specifically designed to help protect against near-future threats that might be used to crack today's encryption technologies.

What problem is the new z16 addressing? To a large extent, it’s financial fraud. According to a study from IBM and Morning Consult “2022 IBM Global Financial Fraud Impact Report”, credit card fraud is the most common type of fraud among consumers in the seven countries surveyed. Furthermore, respondents said they believe that banks and payment networks should be most responsible for preventing fraud. But running deep-learning models at scale in real-time has not been possible due to latency issues, meaning fraud detections models are only run on less than 10% of high-volume transactions, which means that a significant amount of fraud is going undetected.

The z16, with its pre-announced 7nm Telum processor provides the much needed on-chip AI inferencing, and the rest of the mainframe (like earlier models) provides highly secured and reliable high-volume transaction processing. Banks are now able to analyze for fraud during transactions on a massive scale. IBM asserts that the z16 can process 300 billion inference requests per day with just one millisecond of latency. Users of the z16 will be able to reduce the time and energy required to handle fraudulent transactions on their credit card. For both merchants and card issuers, this could mean a reduction in revenue loss as consumers could avoid the frustration associated with false declines where they might turn to other cards for future transactions.

Tax fraud and organized retail theft are emerging as challenges for governments and businesses to control. Real-time payments and alternative payment methods like cryptocurrencies are pushing the limits on traditional fraud detection techniques. Applying the new capabilities of IBM z16 to other industries can help create an entirely new class of use cases, including:

• Loan approval: to speed up approval of business or consumer loans
•  Clearing and settlement: to determine which trades and/or transactions may have a high-risk exposure before settlement
• Federated learning for retail: to better model risk against fraud and theft.

The Telum chip contains eight processor cores that apparently run at more than 5GHz clock frequency. There will be two eight-core chips in each individual socket with the z16 processor, and they will be linked by a proprietary interconnect. To put that in perspective, the Z15's clock speed was 5.2GHz, and it came with 10 cores.

As hybrid environments become more popular, comprising on-prem and public cloud resources, it becomes critically important to protect against threats and work against cyber criminals who might steal data now for decryption later. To that end, the z16 comes with Pervasive Encryption and Confidential Computing.

IBM, like other organizations is working on quantum computing, which is promised to be able to break currently-available security techniques. The z16 is recognized as the industry's first quantum-safe system. What that means is that the z16 with the Crypto Express 8S card provides quantum-safe APIs providing access to quantum-safe algorithms that have been selected as finalists during the PQC standardization process conducted by NIST. Quantum-safe cryptography refers to efforts to identify algorithms that are resistant to attacks by both classical and quantum computers, to keep information assets secure even after a large-scale quantum computer has been built.

The IBM z16 is underpinned by lattice-based cryptography, an approach for constructing security primitives that helps protect data and systems against current and future threats. With IBM z16 quantum-safe cryptography, businesses can future-ready their applications and data today.

With secure boot (meaning that bad actors cannot inject malware into the boot process to take over the system during start-up), IBM z16 clients can strengthen their cyber resiliency posture and retain control of their system. The secure boot and quantum-safe cryptography (mentioned above) can help clients address future quantum-computing-related threats including harvest now, decrypt later attacks, which can lead to extortion, loss of intellectual property and disclosure of other sensitive data.

In terms of resiliency, IBM announced Flexible Capacity for cyber resiliency, allowing a fully automated client-initiated site swap within seconds, which can then stay for a year. Customers can dynamically shift production workloads from one IBM z16 system to another z16 system in seconds – an almost instantaneous shift of capacity from one environment to another. IBM allows customers to perform this operation up to 12 times a year, ie six round trips.

IBM also introduced the IBM Z Security and Compliance Center to simplify and streamline compliance tasks. Complex hybrid-cloud environments can make putting together all the information needed for an audit time-consuming and difficult. The IBM Z Security and Compliance Center automates the collection and validation of the evidence against a set of controls, the system, operating system, middleware, and applications. The first release will focus on PCI DSS and NIST 853 security controls, with a more planned. The solution includes a centralized interactive dashboard displaying compliance posture in real-time.

With cyber-crime such a huge issue, and the worry about quantum computers and their ability to quickly break codes, having a platform that is ahead of the game like the z16 has got to make it a first choice for any organization worried about those threats. The new mainframe becomes generally available on 31 May.

NFTs, crime, and mainframes

Collins Dictionary chose NFT as its word of the year in 2021. A non-fungible token (NFT) is a unique and non-interchangeable unit of data, eg a photo, video, audio file, or even a tweet that can be verified. By 2024, Gartner predicts that 50% of publicly listed companies will have some sort of NFT underpinning their brand and/or digital ecosystem presence.

You can think of NFTs as digital assets – something that can be bought and sold, but they really have no tangible form of their own. An example would be an image of two-year-old Chloe Clem, which was sold as an NFT in September 2021 for about $74,000.

Whereas a painting or sculpture might be considered to have a value because there is only one version of the original artwork, digital files can be copied many times. What makes NFTs special is that the artwork is ‘tokenized’ to create a digital certificate of ownership, which can be bought and sold.

In the modern world, Bitcoin (and other cryptocurrencies) are thought of as an alternative to traditional currencies, and NFTs are the alternative to traditional collectables. And, as everyone is warned when buying and selling things, the value can go down as well as up.

What’s to stop criminals copying the photos, or music, or whatever, and passing them off as their own? The answer is that a record of who owns what is stored on a shared ledger known as a blockchain. And that ledger is maintained by thousands of computers around the world.

So, blockchain is often called distributed ledger technology. Existing information can never be updated or deleted in or from a blockchain, only new information can be added. If two computers or nodes disagree about the contents of the blockchain, the version stored on the majority of the nodes or computers is used. A blockchain network can involve thousands of computers or nodes. That makes blockchain resilient, reliable, and available.

Enterprise blockchain applications can run on IBM Z mainframes, on z/OS or on a Linux logical partition. In fact, blockchain applications could access data in CICS, IMS, or Db2, using appropriate APIs

If blockchain runs on mainframes, and NFTs run in blockchain, mainframe users must be worried by all this talk about crime – and there does seem to be a lot of crime associated with NFTs.

According to an article in The Guardian newspaper in February, Lois van Baarle, a Dutch artist, found more than 100 pieces of her art for sale on OpenSea, one of the biggest NFT marketplaces. She hadn’t put any of them there. And she’s not the only artist affected.

It seems that the market for NFTs grew to an estimated $22bn last year. OpenSea has said: “It is against our policy to sell NFTs using plagiarized content”. The thing is that some artists are using NFTs as a way to earn money. However, criminals can ‘mint’ a digital file as an NFT, even though they don’t have the rights to it. And the process is anonymous by default.

Another criminal activity associated with NFTs is wash trading. This is where the same person is the buyer as well as the vendor. Why would anyone want to do that? The answer is to put up the apparent value of an NFT. In the past, it has mainly been associated with crypto-currency exchanges as a way to make it seem like sites have much higher trading volumes. If people connect their wallet to a platform, the wallet’s owner becomes very hard to identify. It’s only through blockchain analysis that transactions like this can be identified. One analysis found that most NFT wash traders have been unprofitable. However, where they have been profitable, those profits have been huge. Wash trading doesn’t seem to be covered by any laws at the moment, and there don’t seem to have been any prosecutions.

A third type of crime now associated with NFTs is money laundering. Basically, NFTs are purchased using ‘dirty’ money, and then sold at a later date. The money from the sale is now legitimate. That original purchase is made using an ‘illicit wallet’. An ‘illicit wallet’ is a wallet or crypto address associated with criminal activities such as ransomware, malware, hacks, scams, terrorist financing, sanctions, child abuse materials, fraud shops, and darknet marketplaces.

Lastly, the BBC website has reported that the UK tax authority has seized three NFTs as part of a probe into a suspected VAT fraud involving 250 alleged fake companies. According to HM Revenue and Customs (HMRC), three people were arrested on suspicion of attempting to defraud it of £1.4m. The authority said it was the first UK law enforcement to seize an NFT. It also warned others who thought they could use crypto-assets to hide money from HMRC.

The suspects were alleged to have used “sophisticated methods” to try to hide their identities including false and stolen identities, false addresses, pre-paid unregistered mobile phones, Virtual Private Networks (VPNs), false invoices, and pretending to engage in legitimate business activities.

HMRC said it had secured a court order to detain the seized crypto-assets worth about £5,000 and three digital artwork NFTs, which have not been valued, while its investigation continues.

Nick Sharp, deputy director economic crime, said: “We constantly adapt to new technology to ensure we keep pace with how criminals and evaders look to conceal their assets”.

Probably, none of these crimes have taken place on a mainframe, but this should still act as a warning to sites using mainframes for blockchain and NFTs to take care. Criminals are always on the lookout for new ways to make money from illegal activities.