False alerts due to misconfigured/ compromised IDS in ICS networks can lead to severe economic and operational damage. To solve this problem, research has focused on leveraging deep learning techniques that help reduce false alerts. However, a shortcoming is that these works often require or implicitly assume the physical and cyber sensors to be trustworthy. Implicit trust of data is a major problem with using artificial intelligence or machine learning for CPS security, because during critical attack detection time they are more at risk, with greater likelihood and impact, of also being compromised. To address this shortcoming, the problem is reframed on how to make good decisions given uncertainty. Then, the decision is detection, and the uncertainty includes whether the data used for ML-based IDS is compromised. Thus, this work presents an approach for reducing false alerts in CPS power systems by dealing uncertainty without the knowledge of prior distribution of alerts. Specifically, an evidence theoretic based approach leveraging Dempster Shafer combination rules are proposed for reducing false alerts. A multi-hypothesis mass function model is designed that leverages probability scores obtained from various supervised-learning classifiers. Using this model, a location-cum-domain based fusion framework is proposed and evaluated with different combination rules, that fuse multiple evidence from inter-domain and intra-domain sensors. The approach is demonstrated in a cyber-physical power system testbed with Man-In-The-Middle attack emulation in a large-scale synthetic electric grid. For evaluating the performance, plausibility, belief, pignistic, etc. metrics as decision functions are considered. To improve the performance, a multi-objective based genetic algorithm is proposed for feature selection considering the decision metrics as the fitness function.

Cybersecurity has been a concern for quite a while now. In the latest years, cyberattacks have been increasing in size and complexity, fueled by significant advances in technology. Nowadays, there is an unavoidable necessity of protecting systems and data crucial for business continuity. Hence, many intrusion detection systems have been created in an attempt to mitigate these threats and contribute to a timelier detection. This work proposes an interpretable and explainable hybrid intrusion detection system, which makes use of artificial intelligence methods to achieve better and more long-lasting security. The system combines experts' written rules and dynamic knowledge continuously generated by a decision tree algorithm as new shreds of evidence emerge from network activity.

Sleep is a fundamental physiological process that is essential for sustaining a healthy body and mind. The gold standard for clinical sleep monitoring is polysomnography(PSG), based on which sleep can be categorized into five stages, including wake/rapid eye movement sleep (REM sleep)/Non-REM sleep 1 (N1)/Non-REM sleep 2 (N2)/Non-REM sleep 3 (N3). However, PSG is expensive, burdensome, and not suitable for daily use. For long-term sleep monitoring, ubiquitous sensing may be a solution. Most recently, cardiac and movement sensing has become popular in classifying three-stage sleep, since both modalities can be easily acquired from research-grade or consumer-grade devices (e.g., Apple Watch). However, how best to fuse the data for the greatest accuracy remains an open question. In this work, we comprehensively studied deep learning (DL)-based advanced fusion techniques consisting of three fusion strategies alongside three fusion methods for three-stage sleep classification based on two publicly available datasets. Experimental results demonstrate important evidence that three-stage sleep can be reliably classified by fusing cardiac/movement sensing modalities, which may potentially become a practical tool to conduct large-scale sleep stage assessment studies or long-term self-tracking on sleep. To accelerate the progression of sleep research in the ubiquitous/wearable computing community, we made this project open source, and the code can be found at: https://github.com/bzhai/Ubi-SleepNet.

Riverside Research strives to be one of America's premier providers of independent, trusted technical and scientific expertise. We continue to add experienced and technically astute staff who are highly motivated to help our DoD and Intelligence Community (IC) customers deliver world class programs. As a not-for-profit, technology-oriented defense company, we believe service to customers and support of our staff is our mission. Our goal is to serve as a destination company by providing an industry-leading, positive, and rewarding employee experience for all who join us. We aspire to be a valued partner to our customers and to earn their trust through our unwavering commitment to achieve timely, innovative, cost-effective and mission-focused solutions.

From commerce, finance and agriculture to self-driving cars, personalised healthcare and social media – advancements in artificial intelligence (AI) unlock countless opportunities. New applications promise to improve the quality of people's lives throughout the world, but at the same time, raise a number of societal questions. A joint panel discussion of the German National Academy of Sciences Leopoldina and the Korean Academy of Science and Technology (KAST) explores AI technologies, their benefits and their challenges for society. Virtual panel discussion of the German National Academy of Sciences Leopoldina and the Korean Academy of Science and Technology „Realizing the Promises of Artificial Intelligence" Thursday, 25 November 2021, 8am to 9am (CET) Online Following opening remarks from the President of the Leopoldina, Prof (ETHZ) Dr Gerald Haug and Prof Min-Koo Han, PhD, President of the KAST, legal scholar Prof Ryan Song, PhD, Kyung Hee University, Seoul/South Korea, will provide an introduction into the topic. Subsequently, computer scientist Prof Alice Oh PhD, KAIST School of Computing, Daejeon/ South Korea, and Member of the Leopoldina Prof Dr Alexander Waibel, Karlsruhe Institute of Technology/Germany and Carnegie Mellon University, Pittsburgh/USA, will provide input statements for further discussion.

I am writing about AI application, advantages and disadvantages and importance, as I mentioned in pervious Article. In the 1950s, early AI exploration concentrated on problem working and emblematic approaches. The US Department of Defense came interested in this type of work in the 1960s, and began tutoring computers to emulate abecedarian mortal logic. And, long before Siri, Alexa, or Cortana came ménage names, DARPA developed intelligent particular sidekicks in 2003. This early work paved the way for the robotization and formal logic that we see in computers moment, including decision support systems and smart hunt systems that can be designed to round and compound mortal capacities. Early work with neural networks stirs excitement for "allowing machines" Why is artificial intelligence important?

Sean Hannity shows how Kyle Rittenhouse is the latest in a long line of victims of Democrats' premature judgment on'Hannity.' This is a rush transcript of "Hannity" on November 17, 2021. This copy may not be in its final form and may be updated. It is now officially in the books and still no verdict. Now, earlier, today an explosive new development from the courthouse and it all surrounds this drone footage showing Kyle Rittenhouse shooting Joseph Rosenbaum in what looks like a clear act of self defense. According to one eyewitness account, Rosenbaum threatened Rittenhouse, telling him, quote, I'm going to bleeping kill you. Oh that would be a threat. Then as you can see, right there, Rosenbaum chased Rittenhouse, threw an object at his head, cornered him against a group of parked cars and then lunged for the Rittenhouse's weapon before Rittenhouse discharged his firearm, killing Rosenbaum. Now, a new reason for a potential mistrial is that the defense team did not get this high quality video until it was shown in court. Instead, during discovery, they were emailed a compressed low-quality version and what the prosecution is calling, quote, a bid to undermine Rittenhouse's self- defense. This is now the second mistrial request, one with prejudice and one without, under consideration by the judge. Now, keep in mind, the judge will not likely make a decision until after a verdict has been rendered. If Rittenhouse is found not guilty, there will be no point in declaring a mistrial. Ultimately, there are now multiple legitimate reasons for a possible mistrial with several instances of alleged prosecutorial misconduct, including criticizing the defendant's right to remain silent, maligning the defendant's right to face his accusers, violating an order banning prior gun comments and now failure to turn over video evidence as the law requires. Our very own Gregg Jarrett who will join us in a moment, he'll have a lot more detail on why a mistrial is a definite possibility in this case.

NASA's Perseverance rover is exploring Mars for signs of fossilized life, but it could be thrown off by'false biosignatures,' fossil-like specimens that are actually created by chemical processes, according to a new study. Astrobiologists from the Universities of Edinburgh and Oxford note that the rocks on the Red Planet are likely to have'numerous types of non-biological deposits,' which could make it harder to decipher what is rock and what could be signs of ancient life, assuming it once existed. The astrobiologists say that telling the difference is important for not only the Perseverance rover mission and other current NASA missions to Mars, but future missions as well. There are'dozens of processes' and potentially more yet to be discovered – that are capable of producing deposits that look like bacterial cells and carbon-based molecules that look like the known building blocks of life. Looking for life on Mars (including the Perseverance rover, shown) could be thrown off by'false biosignatures,' fossil-like specimens that are created by chemical processes The rocks on the Red Planet likely have a number of non-biological deposits,' making it harder to decipher what's rock and what could be life'We have been fooled by life-mimicking processes in the past,' the study's co-author, Dr Julie Cosmidis, said in a statement. 'On many occasions, objects that looked like fossil microbes were described in ancient rocks on Earth and even in meteorites from Mars, but after deeper examination they turned out to have non-biological origins.

Defence and national security agencies have enlisted the services of Australian researchers to explore how artificial intelligence (AI) can be used to improve military decision-making. Thanks to funding through the'Artificial intelligence for decision-making' initiative, researchers across the country are exploring how to exploit the power of AI and machine learning to enhance the decision-making of military commanders and national security analysts. According to the Office of National Intelligence (ONI), intelligence is a highly data-driven business where appropriately harnessed AI and machine learning has great potential to support the important work of the National Intelligence Community's world-class analysts. Senior Defence researchers, Darryn Reid and Simon Ellis-Steinborner, explained that in a Defence and national security context, decisions can have serious tactical and strategic consequences, both with a potentially profound cost. "There are occasions where these decisions need to be made in highly uncertain situations, sometimes with limited data and information," Dr Ellis-Steinborner said.

In 2018, thousands of Google employees protested a Pentagon contract dubbed Project Maven that used the company's artificial intelligence technology to analyze drone surveillance footage. Google said it wouldn't renew the contract and announced guiding principles for future AI projects that forbid work on weapons and surveillance projects "violating internationally accepted norms." At the same time, Google made clear it would still seek defense contracts. "While we are not developing AI for use in weapons," CEO Sundar Pichai wrote, "we will continue our work with governments and the military in many other areas." In the three years since, Google has stayed true to his word.