相关论文: Predicting sensitive information leakage in IoT ap…

Advances in technology have enabled tremendous progress in the development of a highly connected ecosystem of ubiquitous computing devices collectively called the Internet of Things (IoT). Ensuring the security of IoT devices is a high…

The vast increase of Internet of Things (IoT) technologies and the ever-evolving attack vectors have increased cyber-security risks dramatically. A common approach to implementing AI-based Intrusion Detection systems (IDSs) in distributed…

Internet of things (IoT) has been playing an important role in many sectors, such as smart cities, smart agriculture, smart healthcare, and smart manufacturing. However, IoT devices are highly vulnerable to cyber-attacks, which may result…

The augmentation of Internet of Things (IoT) devices transformed both automation and connectivity but revealed major security vulnerabilities in networks. We address these challenges by designing a robust intrusion detection system (IDS) to…

How much does a machine learning algorithm leak about its training data, and why? Membership inference attacks are used as an auditing tool to quantify this leakage. In this paper, we present a comprehensive \textit{hypothesis testing…

A growing issue in the modern cyberspace world is the direct identification of malicious activity over network connections. The boom of the machine learning industry in the past few years has led to the increasing usage of machine learning…

Timing side-channel attacks exploit secret-dependent execution time to fully or partially recover secrets of cryptographic implementations, posing a severe threat to software security. Constant-time programming discipline is an effective…

IoT device identification plays an important role in monitoring and improving the performance and security of IoT devices. Compared to traditional non-IoT devices, IoT devices provide us with both unique challenges and opportunities in…

Network Intrusion Detection Systems (NIDS) have progressively shifted from signature-based techniques toward machine learning and, more recently, deep learning methods. Meanwhile, the widespread adoption of encryption has reduced payload…

In vulnerability detection, machine learning has been used as an effective static analysis technique, although it suffers from a significant rate of false positives. Contextually, in vulnerability discovery, fuzzing has been used as an…

In Internet of Things (IoT) systems with security demands, there is often a need to distribute sensitive information (such as encryption keys, digital signatures, or login credentials, etc.) among the devices, so that it can be retrieved…

Advanced Persistent Threats (APTs) are stealthy customized attacks by intelligent adversaries. This paper deals with the detection of APTs that infiltrate cyber systems and compromise specifically targeted data and/or infrastructures.…

Security operations in smart cities demand detection systems that balance accuracy with response time. While ensemble methods like Random Forest achieve high accuracy, their computational overhead impedes real-time forensic triage. We…

Emerging Internet of Thing (IoT) platforms provide a convenient solution for integrating heterogeneous IoT devices and deploying home automation applications. However, serious privacy threats arise as device data now flow out to the IoT…

Internet of Things (IoT) occupies a vital aspect of our everyday lives. IoT networks composed of smart-devices which communicate and transfer the information without the physical intervention of humans. Due to such proliferation and…

This paper deals with the query problem in the Internet of Things (IoT). Flooding is an important query strategy. However, original flooding is prone to cause heavy network loads. To address this problem, we propose a variant of flooding,…

As the Internet of Things (IoT) continues to grow, cyberattacks are becoming increasingly common. The security of IoT networks relies heavily on intrusion detection systems (IDSs). The development of an IDS that is accurate and efficient is…

The decentralized and unregulated nature of cryptocurrencies, combined with their monetary value, has made them a vehicle for various illicit activities. One such activity is cryptojacking, an attack that uses stolen computing resources to…

Given the increased growing of Internet of Things networks and their presence in critical aspects of human activities, the security of devices connected to these networks becomes critical. Machine Learning approaches are becoming prominent…

Internet of Things (IoT) devices are increasingly pervasive and essential components in enabling new applications and services. However, their widespread use also exposes them to exploitable vulnerabilities and flaws that can lead to…