Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Hemberg, Erik"'
In this paper, we explore the potential of Large Language Models (LLMs) to reason about threats, generate information about tools, and automate cyber campaigns. We begin with a manual exploration of LLMs in supporting specific threat-related actions
Externí odkaz:
http://arxiv.org/abs/2310.06936
Communication strongly influences attitudes on climate change. Within sponsored communication, high spend and high reach advertising dominates. In the advertising ecosystem we can distinguish actors with adversarial stances: organizations with contra
Externí odkaz:
http://arxiv.org/abs/2308.03191
Autor:
Hemberg, Erik, Lundin, Emma
Projektet har utförts i samarbete med Elektroautomatik, ett företag som specialiserar sig inom automation. En del av företagets arbete består av PLC-programmering i Siemens TIA Portal. Vid uppstart av nya projekt, nyttjar företaget ett skalproje
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-21467
Autor:
Sit, Timothy P.H., Feord, Rachael C., Dunn, Alexander W.E., Chabros, Jeremi, Oluigbo, David, Smith, Hugo H., Burn, Lance, Chang, Elise, Boschi, Alessio, Yuan, Yin, Gibbons, George M., Khayat-Khoei, Mahsa, De Angelis, Francesco, Hemberg, Erik, Hemberg, Martin, Lancaster, Madeline A., Lakatos, Andras, Eglen, Stephen J., Paulsen, Ole, Mierau, Susanna B.
Publikováno v:
In Cell Reports Methods 18 November 2024 4(11)
Contagious respiratory diseases, such as COVID-19, depend on sufficiently prolonged exposures for the successful transmission of the underlying pathogen. It is important for organizations to evaluate the efficacy of interventions aiming at mitigating
Externí odkaz:
http://arxiv.org/abs/2108.11025
Autor:
Hemberg, Erik, O'Reilly, Una-May
Artificial Intelligence (AI) and Machine Learning (ML) algorithms can support the span of indicator-level, e.g. anomaly detection, to behavioral level cyber security modeling and inference. This contribution is based on a dataset named BRON which is
Externí odkaz:
http://arxiv.org/abs/2108.02618
Generative adversary networks (GANs) suffer from training pathologies such as instability and mode collapse, which mainly arise from a lack of diversity in their adversarial interactions. Co-evolutionary GAN (CoE-GAN) training algorithms have shown t
Externí odkaz:
http://arxiv.org/abs/2106.13590
Autor:
Emanuello, John, Ferguson-Walter, Kimberly, Hemberg, Erik, Reilly, Una-May O, Ridley, Ahmad, Ross, Dennis, Staheli, Diane, Streilein, William
Malicious cyber activity is ubiquitous and its harmful effects have dramatic and often irreversible impacts on society. Given the shortage of cybersecurity professionals, the ever-evolving adversary, the massive amounts of data which could contain ev
Externí odkaz:
http://arxiv.org/abs/2104.13254
Scaling the cyber hunt problem poses several key technical challenges. Detecting and characterizing cyber threats at scale in large enterprise networks is hard because of the vast quantity and complexity of the data that must be analyzed as adversari
Externí odkaz:
http://arxiv.org/abs/2104.11576
Autor:
Hemberg, Erik, Kelly, Jonathan, Shlapentokh-Rothman, Michal, Reinstadler, Bryn, Xu, Katherine, Rutar, Nick, O'Reilly, Una-May
Many public sources of cyber threat and vulnerability information exist to help defend cyber systems. This paper links MITRE's ATT&CK MATRIX of Tactics and Techniques, NIST's Common Weakness Enumerations (CWE), Common Vulnerabilities and Exposures (C
Externí odkaz:
http://arxiv.org/abs/2010.00533