Countering Adversarial Inference Evasion Attacks Towards ML-Based Smart Lock in Cyber-Physical System Context
Machine Learning (ML) has been taking significant evolutionary steps and provided sophisticated means in developing novel and smart, up-to-date applications. However, the development has also brought new types of hazards into the daylight that can have even destructive consequences required to be addressed. Evasion attacks are among the most utilized attacks that can be generated in adversarial settings during the system operation. In assumption, ML environment is benign, but in reality, perpetrators may exploit vulnerabilities to conduct these gradient-free or gradient-based malicious adversarial inference attacks towards cyber-physical systems (CPS), such as smart buildings. Evasion attac…
Terveydenhuollon alustat ja tekoäly
Suomen pelialan koulutuksen kartoitus 2014
Adversarial Attack’s Impact on Machine Learning Model in Cyber-Physical Systems
Deficiency of correctly implemented and robust defence leaves Internet of Things devices vulnerable to cyber threats, such as adversarial attacks. A perpetrator can utilize adversarial examples when attacking Machine Learning models used in a cloud data platform service. Adversarial examples are malicious inputs to ML-models that provide erroneous model outputs while appearing to be unmodified. This kind of attack can fool the classifier and can prevent ML-models from generalizing well and from learning high-level representation; instead, the ML-model learns superficial dataset regularity. This study focuses on investigating, detecting, and preventing adversarial attacks towards a cloud dat…
IBM-teknologioiden hyödyntäminen terveydenhuollossa
Tekoälyn soveltaminen terveydenhuollossa ja hyvinvoinnissa
Digitaalisista sairaaloista kognitiivisiin sairaaloihin
Tekoälyn perusteita ja sovelluksia
Artificial intelligence in the cyber security environment
Artificial Intelligence (AI) is intelligence exhibited by machines. Any system that perceives its environment and takes actions that maximize its chance of success at some goal may be defined as AI. The family of AI research is rich and varied. For example, cognitive computing is a comprehensive set of capabilities based on technologies such as deep learning, machine learning, natural language processing, reasoning and decision technologies, speech and vision technologies, human interface technologies, semantic technology, dialog and narrative generation, among other technologies. Artificial intelligence and robotics have steadily growing roles in our lives and have the potential to transfo…
Tekoäly ja terveydenhuolto Suomessa
IoT -based adversarial attack's effect on cloud data platform services in a smart building context
IoT sensors and sensor networks are widely employed in businesses. The common problem is a remarkable number of IoT device transactions are unencrypted. Lack of correctly implemented and robust defense leaves the organization's IoT devices vulnerable to numerous cyber threats, such as adversarial and man-in-the-middle attacks or malware infections. A perpetrator can utilize adversarial examples when attacking machine learning (ML) models, such as convolutional neural networks (CNN) or deep neural networks (DNN) used, e.g., in DaaS cloud data platform service of smart buildings. DaaS cloud data platform's function in this study is to connect data from multiple IoT sensors, databases, private…
Tekoäly ja rakennusten ennakoiva kunnossapito
Tämän raportin tarkoituksena on tarkastella tekoälyn hyödyntämistä rakennusten ennakoivassa kunnossapidossa. Raportissa esitellään KIRA-digi –hanke ja kuvataan Jyväskylän yliopiston KIRA-digi –pilottihanke. Raportin alussa on tekoälyn kehityspolku ja menetelmiä koskeva luku, jossa määritellään tekoälyn käsite ja tekoälyn menetelmiä, kuten neuroverkot, kone- ja syväoppiminen. Kolmas luku koskee älykkäitä rakennuksia ja kaupunkeja sekä esineiden internetiä (IoT), sensoreita, analytiikkaa, päälle puettavia laitteita ja teollista esineiden internetiä (IIoT). neljännessä raportin luvussa tarkastellaan rakennuksien ennakoivan kunnossapidon hyötyjä ja haittoja, kustannuksia ja säästöjä, prosessia …
Artificial Intelligence in Protecting Smart Building’s Cloud Service Infrastructure from Cyberattacks
Gathering and utilizing stored data is gaining popularity and has become a crucial component of smart building infrastructure. The data collected can be stored, for example, into private, public, or hybrid cloud service infrastructure or distributed service by utilizing data platforms. The stored data can be used when implementing services, such as building automation (BAS). Cloud services, IoT sensors, and data platforms can face several kinds of cybersecurity attack vectors such as adversarial, AI-based, DoS/DDoS, insider attacks. If a perpetrator can penetrate the defenses of a data platform, she can cause significant harm to the system. For example, the perpetrator can disrupt a buildin…