I feel it in my fingers/I feel it in my toes
AI is all around me / And so the feeling grows
(with apologies to Reg Presley)
Artificial intelligence (AI) has played an increasing and important role in many aspects of the maritime transportation system (MTS) for several years. In one way or another, AI has been around for over 70 years, although it was only widely reported in public media about a decade ago and finally appears to have reached critical mass in terms of public awareness last year. The year 2023 has seen a flurry of articles about AI in many aspects of life – not the least of which has to do with actors’ and writers’ strikes in Hollywood – and everyone seems to have a opinion on what it is about, whether it is progress for humanity or progress for humanity. begetting of the devil, and how this should be regulated and legislated.
AI refers to the combined intelligence of machines and software. It has been personified in science fiction primarily in the form of humanoid robots, such as in the robot stories of Isaac Asimov (1940–1955) and by Robby the Robot in the classic 1956 film Forbidden Planet. AI has been a serious academic and research discipline since the mid-1950s and its form has changed over time, reflecting technological changes in computers and peripherals. It’s probably fair to say that AI research began with Alan Turing’s description of the imitation game in 1950; The Turing test determines whether a human can have an interaction with a machine that is indistinguishable from an interaction with another human. There is some debate as to whether Chat Generative Pre-trained Transformer (ChatGPT) has passed the Turing test or not, but it is probably very close to doing so if it hasn’t already.
Modern AI (post-2010) is based on deep learning, a combination of machine learning, big data and neural networks. The digital revolution that began in the 1960s was essential to the development of big data; By digitizing all forms of data and communications, we had the ability to create enormous data sets that could be searched, analyzed and transformed in endless ways to become the systems learning database of AI. Neural networks refer to computers capable of learning from collective knowledge distributed within a network rather than relying solely on their own programming, as first demonstrated as early as 1952 by the computer stochastic neural analog reinforcement (SNARC). Current AI research goals include advancements in knowledge representation, reasoning, planning, natural language processing, and perception in order to build a machine that will demonstrate general intelligence and the ability to solve arbitrary problems. AI is already playing an increasingly important role in our daily lives, although in ways that are often neither obvious nor invisible; common applications include advanced search engines, marketing and “recommendation” systems, human speech recognition, autonomous vehicles, creative/artistic tools, strategic and serious games, and diagnostic and monitoring tools. medical treatment.
To illustrate how advanced AI can be, an English computer scientist has filed patent applications with the Intellectual Property Office (IPO) on behalf of an AI he invented. The IPO rejected the applications in 2019, saying only one person could obtain a patent. Although the inventor claimed that AI was a “conscious and sentient form of artificial intelligence”, the UK Supreme Court upheld the IPO decision in December 2023.
Although these concepts seem distant from maritime security and cybersecurity, AI is already an integral part of both. It’s probably not necessary to look at all the ways automation and autonomy in the maritime sector are powered by AI at some level, from smart ships, ports and containers to navigation and fully autonomous ships. But don’t confuse automation and some forms of autonomy with AI. Many automatic systems read a series of sensors, dials and other inputs; if the system state is X, then the action is Y. This is purely algorithmic. It’s not about intelligence per se, but about programming.
The interaction between AI and cybersecurity essentially falls into three categories, often referred to as defensive, offensive, and adversarial. As the name suggests, defensive AI refers to the methods used to assist in cyber defense. AI can help detect cyber fraud, abnormal email messages or data traffic patterns, and phishing attempts. Intrusion detection and prevention, log analysis, and incident response and recovery strategies and procedures can be aided by the use of AI tools. Mitigating denial of service (DoS) attacks and even predicting potential software vulnerabilities and zero-day exploits can benefit from AI tool analysis. AI-powered risk management planning and patch management can be much more efficient and optimized than managing these processes manually.
Offensive AI refers to counter-defensive methods, used to help plan and carry out cyberattacks. AI can collect information from the Internet to quickly generate highly personal and effective spearphishing messages and other forms of social engineering attacks. Misinformation and disinformation almost seem to be a specialty of AI, given its ability to create well-written, plausible messages that seem both correct and definitive. AI makes it easier to combat deep fakes, data poisoning, and the manipulation of data traffic that may appear legitimate. Password cracking, automated hacking, and botnet management are much easier with AI tools.
The third form is adversarial AI (AAI), which are methods that directly attack other AI systems. AAI methods degrade, deny, deceive or manipulate an AI system. There are many adversarial methods that can be used, such as attacking the model used by other AI systems, adding noise to the system with which to confuse the opposing AI, reprogramming or introducing errors into the other AI software. AI, or poison training data used by other AI systems.
The maritime transportation system has unique cybersecurity needs due solely to the unique environment in which we operate and our unique information and operational technology systems. AI will be part of the cyber products, procedures and strategies we employ, just as it is in other sectors and for the same reasons. AI will be able to detect, predict and test potential vulnerabilities and attack patterns faster than anyone. AI will be able to produce and even predict exploits and defense mechanisms faster than humans. It will also be able to detect and predict errors, as reported by the Global Positioning System (GPS) and Automatic Identification System (AIS), and estimate the trajectories of other vessels in real time. And the AI will learn about maritime systems at record speed, so the learning curve will be steep to learn how to both attack and defend the MTS.
All MTS stakeholders have a vested interest in discovering how and where AI fits into their organizations, systems and requirements. It’s a safe bet that we will all need AI for our cyber defense, but we can’t rely on that alone; we must always focus on creating/maintaining a cybersecurity culture, performing basic Cyber 101 correctly, and focusing on finding and mitigating vulnerabilities.
I’m going to repeat a paraphrase I’ve been saying for many years: “Anyone who thinks technology can solve their problem doesn’t understand technology or their problem.” » It is imperative that we understand the role of AI and not develop an over-reliance on (yet) technology, especially one that we (really!) don’t understand. AI will be the basis of many tools to help MTS workers, but it is far from a replacement.
Gary C. Kessler, Ph.D., CISSP is a Principal Consultant at Fathom5 and a member of the Cydome Advisory Board. This article is excerpted and expanded from Maritime Cybersecurity: A Guide for Leaders and Managers, by Gary Kessler and Steve Shepard.
The views expressed here are those of the author and are not necessarily those of The Maritime Executive.
