Flowers said the Bletchley Park code breakers could hardly believe their eyes when they saw Colossus for the first time. Operating at 5,000 characters per second, it was soon analyzing over 100 messages a week. Not content to leave things there, Flowers used parallel processing in the Mark II Colossi to push up the speed to an incredible 25,000 characters per second

Colossus’s job was to strip a first layer of encryption from the German message. The result—still an encrypted message, called a “de-chi”—went immediately to the hand breakers, who stripped away the remaining encryption to reveal the German plaintext.

The crux to decrypting a message was discovering the letters of key that the machine had used to encrypt it. Tunny messages were soon being broken by hand, using a method invented by mathematician Alan Turing for deducing the letters of key. Turing’s method was the code breakers’ only weapon against Tunny for many months, but hand breaking proved too slow to keep up with the increasing flood of encrypted messages, especially in the face of German enhancements to the security of the system. It became clear that high-speed analytic machines were required.

After the war, Newman transferred parts of two Colossi from Bletchley Park to the University of Manchester, where he planned to create a peacetime centre for electronic computing. It was not long before Colossus’s successor, the first all-purpose electronic computer, was built in Newman’s Manchester computing laboratory. This new machine, called simply “Baby,” was the ancestor of today’s all-purpose computers.

the first all-purpose electronic computer, was built in Newman’s Manchester computing laboratory

The other way we could choose to solve the security threats posed by quantum computers is to harness the power of algorithms. Although it’s true the RSA and ECDH algorithms are vulnerable to Shor’s algorithm on a suitable quantum computer, the National Institute of Standards and Technology (NIST) is working to develop replacement algorithms that will be safe from quantum computers as part of its post-quantum cryptography (PQC) efforts. Some are already in the process of being vetted, like ones called McEliece, Saber, Crystals-Kyber, and NTRU.

In a world where global information transactions are happening nonstop, we need a safe way of delivering keys no matter the distance. Quantum physics can provide a way to securely deliver shared keys quicker and in larger volume, and, most importantly, immune to being intercepted. Using fiber optic cables (like the ones used by telecommunications companies,) special Quantum Key Distribution (QKD) equipment can send tiny particles (or light waves) called photons to each party in the exchange of data. The sequence of the photons encapsulates the identity of the key, a random sequence of 1’s and 0’s that only the intended recipients can receive to construct the key.

magine a scenario wherein you and a childhood friend want to share secrets, but can only do so once you each have the same secret passcode in front of you (and there are no phones.) One friend has to come up with a unique passcode, write it down on a piece of paper (while maintaining a copy for themselves,) and then walk it down the block so the other has the same passcode. Once you and your friend have the shared key, you can exchange secrets (encrypted data) that even a quantum computer cannot read.

This process is called public key encryption, and currently it leverages a few popular algorithms for key exchange, e.g., Elliptic curve Diffie-Hellman (ECDH) or RSA (each named after cryptologists,) each of which are vulnerable to quantum computers. The data exchange has two steps: the key exchange and the encryption itself. The encryption of the data with a secure key will still be safe, but the delivery of the key to unlock that information (key distribution) will not be secure in the future quantum era.To be ready for quantum computers, we need to devise a new method of key distribution, a way to safely deliver the key from one end of the connection to the other.

. He also wrote the first-ever programming manual, and his programming system was used in the Ferranti Mark I, the first marketable electronic digital computer (1951).

Turing was a founding father of artificial intelligence and of modern cognitive science, and he was a leading early exponent of the hypothesis that the human brain is in large part a digital computing machine.

Turing was elected a fellow of the Royal Society of London in March 1951, a high honour, yet his life was about to become very hard. In March 1952 he was convicted of “gross indecency”—that is to say, homosexuality, a crime in Britain at that time—and he was sentenced to 12 months of hormone “therapy.”

In the midst of this groundbreaking work, Turing was discovered dead in his bed, poisoned by cyanide.

The West Area Computers endured the racism of a segregated workplace and the casual sexism apparent when these grown, professional women are referred to with terms like “girl.” Nevertheless, they persisted, demanding equity and recognition. They actively fought back in ways both big and small.

Two years after starting in the West Area Computing Unit in 1951, Mary Jackson took another position researching supersonic flight as a mathematician. She received special permission to take engineering classes at a white facility, becoming NASA’s first Black engineer in 1958.

The reason Blacks were able to be hired as computers was because of an executive order banning racial discrimination in hiring for federal work. U.S. President Franklin D. Roosevelt issued Executive Order 8802 in 1941 to stop Black civil rights activist A. Philip Randolph from organizing a march on Washington, D.C., to protest racial discrimination.

Though computers were paid far more than most jobs available to women at the time, they were paid less than men with similar qualifications. To add further insult, the women were classified as “subprofessionals,” while men were termed “professionals.”

One such story came to light with the release of the 2016 book Hidden Figures and the film of the same name. It’s the story of Black women who worked at the National Aeronautics and Space Administration (NASA) in the South—specifically, in Hampton, Virginia.

Self- Incrimination Article 20(3) of the Constitution of India says that no person accused of an offense shall be compelled to be a witness against himself. The court has further interpreted the word witness to include oral as well as documentary evidence. In Bombay v. Kothi Kalu Oghad, the court observed that a witness offers testimonial and non-testimonial evidence, and only in the former, an accused may be considered as a witness against himself.

Further, in the Double Murder Case of New Hampshire, in January 2017, Timothy Verrill was accused of murdering (stabbing multiple times) Christine Sullivan (48 years) and Jenna Pellegrini (32 years) at the Farmington home but the accused pleaded not guilty. During the investigation, police found the amazon echo devices on which the prosecutor believed that it might contain some pertinent voice recordings. After that, the Court in the State of Hampshire v. Timothy Verrill observed that servers or records maintained by Amazon.com had recordings made by the Echo smart speaker from the period of 27th January to 29th January 2017,and such information containedevidence of crime against the accused. Therefore, the court directed Amazon to produce the recording for the said periods made by echo smart speaker with Alexa voice command capability.

The Arkansas Case– In November 2015, James Bates was charged with 1st -degree murder of Victor Collins in his home. The case gained national attention because, for the very first time, Alexa was treated as evidence in the court. Amazon provided the voice recording with the consent of the accused.

The virtual assistant was developed for fun and to make the life of people more comfortable but with the passage of time, the commission of the crime by the offender has drastically changed due to technological development and it is acting as a catalyst for the courts to impart justice.

It is used as a home assistant and can control various home devices like light on-off, fan on-off, and several other smart devices using its home automation system. It is used for voice Interaction; playing music, providing information, reading audio books, etc. It is available in different languages such as English, French, German, Spanish, Italian, Portuguese, Japanese, and Hindi.

It is first developed as Amazon Echo smart speaker and the echo dot, echo studio, and amazon tap speaker

Today both states and BigTechs take action against the problems of deepfakes. As an example, BigTechs develop the tools to detect challenges of deepfake contents. Virginia, Texas and California is first states in the US that have regulations against legal issues of deepfakes.

WIPO states that deepfakes may cause more severe problems such as violation of the human rights, right of privacy, personal data protection right, etc. than the copyright infringements.

n 2017, a software developer nicknamed "deepfakes" on Reddit online platform posted his creations that he swapped the Hollywood celebrities’ faces onto the faces of porn artists

even one single photo of a source is enough to create deepfake contents.

Deepfake is a new phenomenon heard by many internet users today. It is a combination of “Deep Learning” and “Fake”. As it is understood from combination, deepfakes are created by using artificial intelligence technology,

Will AI take our jobs?In the short term, some experts believe AI will enhance jobs rather than take them, although even now there are obvious impacts: an app called Otter has made transcription a difficult profession to sustain; Google Translate makes basic translation available to all. According to a study published this week, AI could slash the amount of time people spend on household chores and caring, with robots able to perform about 39% of domestic tasks within a decade.

Experts fear a wave of disinformation and scams as the technology becomes more widely available. Potential frauds include personalised phishing emails – which attempt to trick users into handing over data such as login details – produced at mass scale, and impersonations of friends or relatives.

What is deepfake? Deepfake is the term for a sophisticated hoax that that uses AI to create phoney images, particularly of people. There are some noticeable amateurish examples, such as a fake Volodymyr Zelenskiy calling on his soldiers to lay down their weapons last year, but there are eerily plausible ones, too. In 2021 a TikTok account called DeepTomCruise posted clips of a faux Tom Cruise playing golf and pratfalling around his house, created by AI. ITV has released a sketch show comprised of celebrity deepfakes, including Stormzy and Harry Kane, called Deep Fake Neighbour Wars.

The latest generation of chatbots, like ChatGPT, draw on astronomical amounts of material – pretty much the entire written output of humanity, or as much of it as their owners can acquire.Those systems then try to answer a deceptively simple question: given a piece of text, what comes next?

A chatbot draws on the AI we have just been looking at with the large-language models. A chatbot is trained on a vast amount of information culled from the internet. It responds to text prompts with conversational-style responses.The most famous example is ChatGPT. It has been developed by OpenAI, a San Francisco-based company backed by Microsoft. Launched as a simple website in November last year, it rapidly became a sensation, reaching more than 100 million users within two months.

Large-language modelsThis is one of the so-called neural networks. Large-language models are trained by pouring into them billions of words of everyday text, gathered from sources ranging from books to tweets and everything in between. The LLMs draw on all this material to predict words and sentences in certain sequences.

bout: Reinforcement learningPerhaps the most basic form of training there is, reinforcement learning involves giving feedback each time the system performs a task, so that it learns from doing things correctly. It can be a slow and expensive process, but for systems that interact with the real world, there is sometimes no better way.

It boils down to this: most old-school computers do what they are told. They follow instructions given to them in the form of code. But if we want computers to solve more complex tasks, they need to do more than that. To be smarter, we are trying to train them how to learn in a way that imitates human behaviour.

The Internet 2.0 report will be presented on Monday to a US Senate hearing on TikTok. With 142.2 million users in North America, the US is “obviously the dominant market for this app.”

But he said Internet 2.0’s research found “Chinese authorities can actually access device data”. By sending tracked bots to the app, Internet 2.0 “consistently saw … data geolocating back to China”.

TikTok’s data collection methods include the ability to collect user contact lists, access calendars, scan hard drives including external ones and geolocate devices on an hourly basis.

Cybersecurity experts have warned Australian TikTok users that the Chinese government could use the app to harvest personal information, from in-app messages with friends to precise device locations.

Last semester, Angel taught a computer science course on how to build tools for anonymity and privacy. One idea was to build a version of Netflix that would shield your movie choices from the company and yet gives you access to the full roster of content. “We can build it,” he says. “It’s technologically feasible” to find a way to stream it to millions or billions of people. But such a system would be costly. For example, if Netflix needed 10,000 computers in their data center to serve movies to everyone, under Angel’s version, it might need 10 times more, or 100,000.

The most common way a user is tracked is through the placement of ‘cookies,’ or files that a website or web service places in your device. So when you return to the website, you don’t have to re-enter your password to log on, for example, because you’re recognized, according to Sebastian Angel, professor of computer and information science at the University of Pennsylvania. “It’s for convenience,” he says. “But because they’re putting these cookies in your devices, it now allows, [say,] Facebook to know where you’re going on the internet.”

For example, a business that knows you’re a pet owner based on your searches for cat food could send you coupons. Companies can also use your data to improve product designs and performance

Every time you interact with the company, you should expect that the company is recording that information and connecting it to you.”

Some recent changes include the following: Google users can now choose to opt in to save their audio data collected by Google Assistant, which uses it to better recognize their voices over time. They can also delete their interactions at any time and agree to a human reviewer of the audio. This month, Facebook’s Instagram rolled out a new feature that lets users manage which third-party apps have access to their data

In part to head off more stringent laws, companies and computer scientists are collaborating to provide computational and business solutions to strengthen data protections while not hampering innovation and operational efficiency. Google, Facebook, Amazon, Apple and others have come forward with changes that give users more control over how they are being tracked and how their data is being used.

According to the United Nations Conference on Trade and Development, 107 countries have data privacy rules in place including 66 developing nations. In the U.S., there was a “significant” increase in data privacy bills being introduced this year, with at least 25 states and Puerto Rico starting such legislation, according to the National Conference of State Legislatures. Notably, this bill count doesn’t include related legislation on topics such as cybersecurity.

Among other stipulations, the CCPA requires businesses to inform consumers regarding the types of personal data they’ll collect at the time they collect it and also how the information will be used. Consumers have the right to ask firms to disclose with whom they share the data and also opt out of their data being sold.

Kavenna worries that, far from legislating to protect user privacy, US states will seek to access voice-assistant recordings in the name of crime prevention and national security. Last year, a judge in New Hampshire made headlines by ordering Amazon to submit Echo recordings of a double murder to investigators. “It puts them in a very complicated position between their customers and the government,” Kavenna says. “We’re very dependent on the political regime.”

His own Echo would wake up unprompted. Recordings began showing up as evidence in court cases. The FBI refused to confirm or deny that it was using Alexa for surveillance purposes. “It became increasingly clear to me that the privacy watchdogs were right,” he says. “It is, at base, a wiretapping device.”

This year has been particularly tricky. Over the past six months, Bloomberg, the Guardian, Vice News and the Belgian news channel VRT have gradually revealed that all the big five have been using human contractors to analyse a small percentage of voice-assistant recordings. Although the recordings are anonymised, they often contain enough information to identify or embarrass the user – particularly

In a statement, Amazon said that the Echo must have misheard the wake word, misheard a request to send a message, misheard a name in its contacts list and then misheard a confirmation to send the message, all during a conversation about hardwood floors. Not great, Alexa.

Last year, an Amazon customer in Germany was mistakenly sent about 1,700 audio files from someone else’s Echo, providing enough information to name and locate the unfortunate user and his girlfriend. (Amazon attributed this “unfortunate mishap” to human error.)

When the Dot’s outburst subsided, he unplugged it and deposited it in the bin. “I felt a bit foolish,” he says. “Having worked at Amazon, and having seen how they used people’s data, I knew I couldn’t trust them.”

This was especially interesting because Josephson (not his real name) was a former Amazon employee. Three years earlier, he had volunteered to sit in a room reciting a string of apparently meaningless phrases into a microphone for an undisclosed purpose

It appeared to be regurgitating requests to book train tickets for journeys he had already taken and to record TV shows that he had already watched. Josephson had not said the wake word – “Alexa” – to activate it and nothing he said would stop it. It was, he says, “Kafkaesque”.

On the morning of 8 June 1954, Turing was found dead in bed by his housekeeper. The coroner’s verdict found that he had taken his own life; there were reports that a partly eaten apple by his bed contained traces of cyanide.

But while Turing’s academic renown was growing, his private life was in turmoil. On 31 March 1952 at a court in Knutsford, Cheshire, Turing was charged with being “party to the commission of an act of gross indecency” – in effect, he was charged with being homosexual. He pleaded guilty. Instead of imprisonment he opted for hormone ‘treatment’ – oestrogen injections that made him put on weight and enlarged his breasts.

Years later, Bletchley Park codebreaker Peter Hilton explained that what set Turing apart from his colleagues was his ability to come up with ideas that Hilton felt he would not have thought of “in a million years”

, Turing managed to deduce, quite quickly, how these code books were being used, but realised that his team would need to acquire copies before further progress could be made.It wasn’t till a German naval code book was captured that Turing and his colleagues began to achieve success in working out the daily key and reading encrypted German naval messages. Intelligence reports about Germany’s U-boat and ship movements could then be produced and sent to the Admiralty for dissemination

The Bombe, though, wasn’t the complete solution to Enigma. Early in 1940, Turing was asked to take on the task of breaking the German navy’s Enigma system, which used more secure procedures than those of the air force and army. Many at Bletchley believed it could not be broken

At Bletchley Park, Turing devised a new and more powerful kind of electro-mechanical machine for determining the crucial Enigma settings. Another Cambridge mathematician working at Bletchley Park, Gordon Welchman, made a crucial addition that increased the effectiveness of the machine – called the Bombe – providing Bletchley Park with a vital codebreaking tool.

The setting that governed these substitutions was known at Bletchley Park as the daily key, because it was usually changed every 24 hours. If the Bletchley Park codebreakers could work out the daily key, they could decrypt and read all of the intercepted German messages sent that day. This was done using replica Enigma machines, manufactured in Britain. But the number of possible daily keys was almost too big to imagine. In the case of the German army and air force Enigma, there were 158.9 million, million, million possibilities. It was this daily key that Turing and his colleagues were trying to work out.

Contrary to popular belief, there was no single ‘Enigma code’. The Enigma machine – actually a family of portable encryption devices that substituted each letter of a message for another letter of the alphabet – was first developed in the 1920s and enhanced over subsequent years.

. The man was Alan Turing, and his work at nearby Bletchley Park – the secret base of the Government Code and Cypher School (GC&CS)

A paper by Turing is published that is later recognised as laying the foundation of computer science

The board lights up to show the encrypted output, and the first of the three rotors clicks round one position – changing the output even if the second letter input is the same as the first one.

Like all the best cryptography, the Enigma machine is simple to describe, but infuriating to break

But that reflector also led to the flaw in Enigma, and the basis on which all codebreaking efforts were founded: no letter would ever be encoded as itself. With that knowledge, as well as an educated guess at what might be encrypted in some of the messages (common phrases included “Keine besonderen Ereignisse”, or “nothing to report” and “An die Gruppe”, or “to the group”), it was possible to eliminate thousands of potential rotor positions.

eading to more than 17,000 different combinations before the encryption process repeats itself. Adding to the scrambling was a plugboard, sitting between the main rotors and the input and output, which swapped pairs of letters. In the earliest machines, up to six pairs could be swapped in that way; later models pushed it to 10, and added a fourth rotor.

. Eventually, the Enigma was superseded by the Lorenz. These required yet more codebreaking in Britain, and more automation to do it – leading to the production of Colossus, the world’s first digital programmable computer.

But the final steps were always performed manually: the job of the Bombe was merely to reduce the number of combinations that the cryptanalysts had to examine.

the practice of cryptography actually goes back thousands of years. One of the earliest examples dates back to around 200 BCE and was devised by the Greek historian Polybius. In a Polybius square, letters fill out a grid of 25 spaces and each letter is identified by its coordinates in the square.

he Spartans were also known to have developed a form of cryptography, based on wrapping parchment around a polygonal cylinder and Julius Caesar used a basic cypher to encode his messages – moving along the alphabet by a pre-agreed number of letters.

“The earliest known text containing components of cryptography originates in the Egyptian town Menet Khufu on the tomb of nobleman Khnumhotep II nearly 4,000 years ago.”

On the morning of 2 December 2015, Syed Rizwan Farook and his wife Tashfeen Malik shot and killed 14 people in the Californian city of San Bernardino. Approximately 20 others were injured. The attackers were tracked down later that day and in an ensuing gun battle were both killed. Determined to find answers regarding the killers’ motives, the FBI soon sought help from Apple to unlock an iPhone belonging to Farook. Apple, however, refused to comply.

Cryptography is at the heart of all secure digital communications – the emails you send, the websites you visit (well, a growing proportion of them) and the apps you use. It allows for data to be scrambled and rendered unreadable by everyone except the intended recipient.

The next stage in the development of encryption may involve the use of quantum computers, which will add layers of complexity that are currently not possible. But until quantum cryptography becomes commonplace, there is a fear that this new groundbreaking technology could render current encryption next-to-useless.

It was a view that garnered much support in the public domain but which Apple’s CEO Tim Cook called a “potentially” chilling breach of privacy: “The same engineers who built strong encryption into the iPhone to protect our users would, ironically, be ordered to weaken those protections and make our users less safe.”

In order to keep that wealth and power in a man’s hands, there’s a backlash to try to redefine it as something a woman didn’t do, and shouldn’t do, and couldn’t do.

Years later, scholars would dispute that Lovelace actually wrote the notes. The Babbage historian Bruce Collier argued that her contribution had been greatly overstated, and “it is no exaggeration to say that she was a manic depressive with the most amazing delusions about her own talents, and a rather shallow understanding of Charles Babbage and the Analytical Engine.”

When Babbage began devising a new project, the “Analytical Engine”—sketched out as a hulking machine with thousands of cogwheels that could perform more functions with greater accuracy—Lovelace served as its key interpreter

Augusta Ada Lovelace is known as the first computer programmer, and, since 2009, she has been recognized annually on October 15th to highlight the often overlooked contributions of women to math and science.

In 1990, women held thirty-four per cent of STEM jobs; in 2011, it was twenty-seven per cent.

In the late seventies, the Department of Defense developed a software language called Ada—one that brought together a number of different programming languages.

But Lovelace reconciled the competing poles of her parents’ influence. On January 5, 1841, she asked, “What is Imagination?” Two things, she thought. First, “the combining faculty,” which “seizes points in common, between subjects having no apparent connection,” and then, she wrote, “Imagination is the Discovering Faculty, pre-eminently. It is that which penetrates into the unseen worlds around us, the worlds of Science.”

There was nothing inevitable about the internet getting built. It seemed like a ludicrous idea to many, even among those who were building it. The scale, the ambition – the internet was a skyscraper and nobody had ever seen anything more than a few stories tall. Even with a firehose of cold war military cash behind it, the internet looked like a long shot.

Trying to move data from one to another was like writing a letter in Mandarin to someone who only knows Hungarian and hoping to be understood. It didn’t work.In response, the architects of the internet developed a kind of digital Esperanto: a common language that enabled data to travel across any network.

Making this dream a reality required doing two things. The first was building a wireless network that could relay packets of data among the widely dispersed cogs of the US military machine by radio or satellite. The second was connecting those wireless networks to the wired network of Arpanet, so that multimillion-dollar mainframes could serve soldiers in combat. “Internetworking,” the scientists called it.

But Arpanet had a problem: it wasn’t mobile. The computers on Arpanet were gigantic by today’s standards, and they communicated over fixed links. That might work for researchers, who could sit at a terminal in Cambridge or Menlo Park – but it did little for soldiers deployed deep in enemy territory. For Arpanet to be useful to forces in the field, it had to be accessible anywhere in the world.

The internet would end up being useful to the US military, if not quite in the ways its architects intended. But it didn’t really take off until it became civilianized and commercialized – a phenomenon that the Arpa researchers of the 1970s could never have anticipated.

As a military venture, Arpa had a specifically military motivation for creating the internet: it offered a way to bring computing to the front lines. In 1969, Arpa had built a computer network called Arpanet, which linked mainframes at universities, government agencies, and defense contractors around the country. Arpanet grew fast, and included nearly 60 nodes by the mid-1970s.

The people who invented the internet came from all over the world.

So intact, in fact, that they could travel another 3,000 miles to a computer in Boston and be reassembled into exactly the same message that was typed into the terminal at Rossotti’s. Powering this internetwork odyssey was the new protocol cooked up by Kahn and Cerf. Two networks had become one. The internet worked.

Designed specifically for computing values for artillery range tables, it lacked some features that would have made it a more generally useful machine.

The disadvantage was that it took days to rewire the machine for each new problem. This was such a liability that only with some generosity could it be called programmable.

ENIAC was enormous. It occupied the 50-by-30-foot (15-by-9-metre) basement of the Moore School, where its 40 panels were arranged, U-shaped, along three walls. Each panel was about 2 feet wide by 2 feet deep by 8 feet high (0.6 metre by 0.6 metre by 2.4 metres). With more than 17,000 vacuum tubes, 70,000 resistors, 10,000 capacitors, 6,000 switches, and 1,500 relays, it was easily the most complex electronic system theretofore built. ENIAC ran continuously (in part to extend tube life), generating 174 kilowatts of heat and thus requiring its own air conditioning system.

the first programmable general-purpose electronic digital computer, built during World War II by the United States.