Security
This dataset is generated for the purpose of developing and testing attestation techniques for IoT devices. The dataset consists of RAM traces for eight different firmwares including traces for running the legitimate firmware as well as tampered versions of the firmwares. we upload the firmware onto the IoT device and allow it to operate for a predefined time period of 300 seconds. Throughout the device's normal operation, we utilize the gateway node to collect numerous RAM trace samples, each comprising 2048 bytes, with randomized intervals between consecutive samples.
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174 Views
Numerous studies have focused on exploring Android malware in recent years, covering areas such as malware detection and application analysis. As a result, there is a pressing need for a reliable and scalable malware dataset to support the development and evaluation of effective malware studies. Although several benchmarks for Android malware datasets are widely used in research, they have significant limitations. Firstly, many of these datasets are outdated and do not capture current malware trends. Additionally, some have become obsolete or inaccessible, limiting their usefulness.
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349 Views
The optical chaos communication (OCC) can provide physical layer security for high-speed data transmission. In these OCC systems, the time delay signature (TDS) serves as a crucial encryption key. We propose a method based on reservoir computing (RC) network for TDS extraction of OCC systems. The mapping relationship between the system output time series and its delay variants is learned by the RC network. Then, the convergence performance of the RC network is measured and used for TDS extraction. The effectiveness is verified by extracting TDS of the two main types of optical time-delay fe
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97 Views
The optical chaos communication (OCC) can provide physical layer security for high-speed data transmission. In these OCC systems, the time delay signature (TDS) serves as a crucial encryption key. We propose a method based on reservoir computing (RC) network for TDS extraction of OCC systems. The mapping relationship between the system output time series and its delay variants is learned by the RC network. Then, the convergence performance of the RC network is measured and used for TDS extraction. The effectiveness is verified by extracting TDS of the two main types of optical time-delay fe
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39 Views
The optical chaos communication (OCC) can provide physical layer security for high-speed data transmission. In these OCC systems, the time delay signature (TDS) serves as a crucial encryption key. We propose a method based on reservoir computing (RC) network for TDS extraction of OCC systems. The mapping relationship between the system output time series and its delay variants is learned by the RC network. Then, the convergence performance of the RC network is measured and used for TDS extraction. The effectiveness is verified by extracting TDS of the two main types of optical time-delay fe
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35 Views
Human facial data hold tremendous potential to address a variety of classification problems, including face recognition, age estimation, gender identification, emotion analysis, and race classification. However, recent privacy regulations, such as the EU General Data Protection Regulation, have restricted the ways in which human images may be collected and used for research.
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406 Views
Dynamic malicious software detection aims to assess whether executable programs exhibit malicious behavior by thoroughly studying and analyzing their dynamic features. However, many current methodologies insufficiently explore the semantic features of API sequences and instead rely more on mining parameter information during API call processes to enhance detection performance. This leads to issues such as excessive dependence on prior knowledge, larger model parameter sizes, and higher computational complexities.
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496 Views
The Illinois 200-Bus Cyber-Physical System (CPS) serves as an important case for studying risk analysis through the integration of physical and cyber components. This system designed to reflect real-world architectures. Access Complexity scores are assigned to its network edges based on the Common Vulnerability Scoring System (CVSS) Access Complexity (AC), allowing for the simulation of adversarial pathways within the system.
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131 Views
Traditional authentication models are vulnerable to security breaches when personal data is exposed. This study introduces novel hybrid visual stimuli protocols integrating event-related potentials (ERP) and steady-state visually evoked potentials (SSVEP) to develop an authentication system that enhances both performance and personalization in neural interfaces. Our model utilizes distinctive neural patterns elicited by a range of visual stimuli based on 4-digit numbers, such as familiar numbers (personal birthdates, excluding targets), standard targets, and non-targets.
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34 Views
A real world radio frequency fingerprinting (RFF) dataset for enhancement strategy by exploiting the physical unclonable function (PUF) to tune the RF hardware impairments in a unique and secure manner, which is exemplified by taking power amplifiers (PAs) in RF chains as an example. This is achieved by intentionally and slightly tuning the PA non-linearity characteristics using the active load-pulling technique. The dataset is collected from the cable-connected measurement and over-the-air measurement.
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455 Views