An ever-present threat to any given country's national security is that of cybersecurity. There are always hackers that want to use technology for malicious purposes, not to say the long list of adversaries that a country can pile up along the years. That's so as what it is at stake is millions of sensible data from citizens, companies, directories, senior officers and members of the government, state's papers and more. Unfortunately, not all Governments take this peril as seriously as they should, and the efforts towards creating cyber-defense strategies – in most countries – lack budget, personnel and even real, field knowledge. Before this absence of real policies, Artificial Intelligence might be well seen as a good starting point where to build the walls that keep out any possible threats.
Employees at FedEx in the U.S., Telefónica in Spain and the National Health Service in the U.K. opened their work computers one day in May 2017 to find they no longer had access to thousands of crucial documents. A message appeared demanding payment in bitcoin to have them restored. The ransomware attack known as WannaCry afflicted more than 200,000 people in 150 countries, according to Europol, and was the largest of its kind in recent history. The threat of this sort of crippling data security breach has tech giants turning to artificial intelligence for solutions. As online hackers increasingly use advanced technology for penetrative attacks, the companies that host our private information also are engaging the most advanced systems available in a bid to protect us.
Artificial intelligence is a scientific field that is responsible for finding solutions to complex problems that humans do not have. Machine learning could be used to bypass and dismantle cyber-security systems faster than most prevention and detection tools can keep up. AI will exacerbate existing threats and create new ones, but its speed could prove a great boon for cybercriminals, as it is much more effective at fighting them than human experts. The algorithm is attempted to model a decision mechanism that resembles real human decision mechanisms but is modeled by algorithms. In the context of cybersecurity, artificial intelligence (AI) tries to defend the system by weighing patterns of behavior that indicate a threat against predictive logic.
While the debate about Artificial Intelligence (AI) and augmented reality rages, virtual terrorists--those who operate primarily on the Dark Web--are getting smarter and thinking of new ways to benefit from both, creating methods to operate autonomously in this brave new world. Malware is being designed with adaptive, success-based learning to improve the accuracy and efficacy of cyberattacks. The coming generation of malware will be situation-aware, meaning that it will understand the environment it is in and make calculated decisions about what to do next, behaving like a human attacker: performing reconnaissance, identifying targets, choosing methods of attack, and intelligently evading detection. This next generation of malware uses code that is a precursor to AI, replacing traditional "if not this, then that" code logic with more complex decision-making trees. Autonomous malware operates much like branch prediction technology, designed to guess which branch of a decision tree a transaction will take before it is executed.
TEISS guest blogger and cybersecurity consultant, Harold Kilpatrick, talks us through the impact of AI and Maching Learning on cyber security. The rapid development of artificial intelligence may significantly improve efficiency in businesses, but the technology could also pose serious threats to online security, a report by a group of UK and US experts warn. As AI is becoming more powerful and faster in performing automated tasks, it is increasingly adopted in a wide variety of industries, from manufacturing to software development. In fact, analysts expect that by 2020 artificial intelligence solutions will be applied in almost all new software products and services, which will irreversibly change the way we interact with technologies and make use of their benefits. But in the quest for innovation and better operations, many miss the obvious risks AI and machine learning could bring.