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ALBAWABA - Google is closing close on what may be its biggest acquisition to date: the purchase of an Israeli cybersecurity startup for up to $23 billio
(Bild: frei lizenziert) Erfahren Sie, wie Large Language Models die Cyberkriminalität beeinflussen können und welche Risiken sie mit sich bringen. Lesen Sie mehr über die Nutzung von KI in der Cyberwelt.
Fast ein Drittel (31 Prozent) der OT-Unternehmen meldete im vergangenen Jahr mehr als sechs Sicherheitsvorfälle, gegenüber elf Prozent im Vorjahr.
The aim is to integrate commercial equipment into military space operations, including satellites and other hardware.
In response to the escalating frequency and complexity of cyber threats, the imperative need to enhance cybersecurity measures is evident. This study explores the potential of machine learning (ML) algorithms in advancing threat detection and classification by automating the identification of security incidents. The abstract presents a thorough assessment of various ML algorithms, including decision trees, support vector machines, and neural networks, for their efficacy in detecting and categorizing cyber threats. The evaluation encompasses a diverse dataset featuring different cyber-attack scenarios and incorporates multiple features such as network traffic patterns, system logs, and user behavior. Performance metrics, such as training accuracy and testing accuracy, are employed to assess the effectiveness of each algorithm. Furthermore, the study investigates the impact of feature selection techniques and model optimization strategies on algorithm performance. The results underscore the capability of ML algorithms to accurately identify and categorize cyber threats, providing valuable insights into their strengths and limitations. This research contributes to the field of cybersecurity by facilitating the development of practical and robust ML-based solutions, ultimately reinforcing cyber defence mechanisms against evolving threats.
IoT is a lightning-fast technology that uses clever objects or stuff that speak uncomplicatedly to the work of our daily lives. Smart homes, wearables, connected automobiles, vibrant urban communities; savvy retail, agribusiness, healthcare, and other areas are some of the most well-known applications of IoT. This document provides an overview of IoT Crypto a safe platform Internet of Things communication. Typically, they have elements from Internet of Things (IoT), such as the device functionality they need, the requirement to restrict the amount of information sent, and the ability to connect to the Internet. With real business relationships in mind, Innovative lightweight authentication setup and trust concepts are provided by IoT-Crypto. Include a secure communication protocol that only makes use of one DTLS connection that is encrypted. This article discusses and presents the unique components and nuanced execution details of IoT crypto in terms of essentially equivalent arrangements. Post-implementation testing and analysis of the IoT encrypted network have proven its accuracy and safety. Additionally, a test network was conducted to determine if the BLE IPSP profile and coding standards are suitable for IoT. Based on these results, the significance of future research was discussed. The IoT paradigm and communication protocols are introduced at the outset of this work and then compare countermeasures for a few security vulnerabilities at each tier of the IoT model to protect such a large and diverse company.
QuSecure announced it has joined NVIDIA and a select group of technology leaders in supporting NVIDIA's cuPQC, a recently launched pioneering library set to redefine cryptography in the quantum era.
AI and ML are revolutionizing cybersecurity by significantly boosting defensive and offensive capabilities. On the defensive front, these technologies empower systems to detect better and counter cyber threats. AI and ML algorithms excel in processing extensive datasets, enabling them to identify patterns and anomalies far more efficiently than traditional approaches. Techniques such as clustering, self-organizing maps, and classification and regression trees (CARTs) have become essential in intrusion detection systems, enhancing their accuracy and responsiveness. This improved capability extends to asset management, risk assessment, and overall governance, reinforcing cybersecurity infrastructures against the growing complexity of modern attacks. Conversely, AI and ML
(Bild: Dall-E / KI-generiert) Der Artikel beleuchtet die rasante Entwicklung von Ransomware durch KI, die Zunahme von Angriffen, insbesondere in nicht-englischsprachigen Ländern, und die Notwendigkeit von Präventionsmaßnahmen in Unternehmen.
Wie steht es um die Cybersecurity in industriellen Umgebungen und um nationale und internationale Gesetzgebungen und Normen? Worauf Unternehmen achten müssen, erläutert der Artikel von Hilscher.
Die deutsche Wirtschaft muss sich dringend auf die neuen Anforderungen zur Cyberresilienz aus dem NIS2-Umsetzungs- und Cybersicherheitsstärkungsgesetz (NIS2UmsuCG) vorbereiten, mahnt Dennis Weyel, International Technical Director mit Zuständigkeit für Europa beim Sicherheitsunternehmen Horizon3.ai.
Rick Driggers of Accenture Federal Services recently shared his thoughts on cybersecurity trends and challenges in an Executive Spotlight interview.
Regierungsvertreter und Mobilfunkfirmen haben sich geeinigt: Langfristig sollen die 5G-Netze ohne Technik von Huawei & Co. auskommen.
Continuous variable measurement-device-independent quantum key distribution (CV-MDI-QKD) removes all known or unknown side-channel attacks on detectors. However, it is difficult to fully implement assumptions in the security demonstration model, which leads to potential security vulnerabilities inevitably existing in the practical system. In this paper, we explore the impact of imbalanced modulation at transmitters on the security of the CV-MDI-QKD system mainly using a coherent state and squeezed state under symmetric and asymmetric distances. Assuming two different modulation topologies of senders, we propose a generalized theoretical scheme and evaluate the key parameter achievable of the protocol with the mechanism of imbalanced modulation. The presented results show that imbalanced modulation can achieve a relatively nonlinearly higher secret key rate and transmission distances than the previous protocol which is the balanced modulation variance used by transmitters. The advantage of imbalanced modulation is demonstrated for the system key parameter estimation using numerical simulation under different situations. In addition, the consequences indicate the importance of imbalanced modulation on the performance of CV-MDI-QKD protocol and provide a theoretical framework for experimental implementation as well as the optimal modulated mode.
Das BSI hat einen aktuellen IT-Sicherheitshinweis für Siemens SIMATIC WinCC herausgegeben. Mehr über die betroffenen Betriebssysteme und Produkte sowie CVE-Nummern erfahren Sie hier auf news.de.
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Opfer der Verschlüsselungstrojaner Muse, DarkRace und DoNex können ab sofort, ohne Lösegeld zu zahlen, wieder auf ihre Daten zugreifen.
German quantum computing startup planqc yesterday announced a Series A raise of €50mn for its digital atom-based technology.
(Bild: Dall-E / KI-generiert) Qualys hat eine Sicherheitslücke in OpenSSH erkannt, die über 14 Millionen Serverinstanzen betrifft, und ermöglicht den externen Zugriff auf Linux-Systeme mit Root-Rechten.
The University of Waterloo research team, led by Dr. Norbert Lütkenhaus, has developed innovative open source software that promises to revolutionize quantum cryptography. This software allows modeling quantum key distribution (QKD) protocols in a realistic way, facilitating the connection between theory and experimentation in this field.
Generative artificial intelligence (GenAI) has the capacity to understand, learn, adapt, and implement knowledge across a broad range of tasks at a level equal to or beyond human capability.
Mit der neuen EU-Direktive NIS2 stehen Unternehmen vor der Herausforderung, ihre Cybersecurity-Strategie zu überarbeiten. Um den Anforderungen der Richtlinie g
A hacker managed to gain access to OpenAI's internal systems and stole data related to its design of AI technologies.
Zero-day attacks are cybersecurity attacks that seek to exploit an unknown vulnerability in Internet of Things (IoT). This makes zero-day attacks inherently difficult to detect and costly to network administrators. Current methods of detection utilize machine learning methodologies for intrusion detection. However, these methods suffer from low performance in specific zero-day attacks. This study proposes novel features built upon network flow and raw packet data aiming to detect zero-day attacks. Our testing approach utilizes fix traditional machine learning algorithms (Decision Tree (DT), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Logistic Regression (LR), Gaussian Naive Bayes (NB), and Random Forest (RF)) with split-at-scenario cross-validation. We find that our engineered features achieve consistent high detection rates with three models (DT, SVM, and RF), whereas these models fail to detect at least one of the attacks when using raw features. Our results display potential for utilizing the proposed flow-based complex features to detect unknown network attacks with Internet of Battle Things (loBT) applications.
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