Effective incident response mechanisms are crucial for maintaining system continuity during security incidents. Equally important is the secure preservation of forensic evidence and chain of custody records for potential legal proceedings. However, traditional methods of incident response and evidence handling can be vulnerable to tampering as they rely on the assumption of a pre-existing level of trust among the involved parties. In this study, we propose a blockchain-based model, DFIRChain, to record all operations within digital forensics and incident response (DFIR) processes on a private permissioned Hyperledger Fabric blockchain, from alert management to case management. By integrating our blockchain-based model into DFIR processes, we aim to ensure the integrity and authenticity of evidence, enhance legal compliance, and contribute to organizations' digital forensic readiness.

Today, the negative impact of charging on the grid is becoming a major concern as the number of electric vehicles increases. The charging topologies such as V2G, V2H and V2V are being studied to solve this problem. The most critical issue in this context is the design and use of appropriate infrastructure and equipment. In this study, firstly a low-cost and high-efficiency non-isolated bidirectional DC-DC converter suitable for DC charging stations is designed. The designed converter was analysed both by analytical methods and by operating at low powers. Secondly, a real-world implementation of V2V and V2H topologies has been performed using these designed converters. In the application study, a DC charging station model was created by using 4 of these converters as charging units. The 90-minute operation of the designed charging station was realised according to a rule-based algorithm. Accordingly, it has been shown that the efficiency of the non-isolated bidirectional DC-DC converter designed is 95%. It is also proved that 54.16% of the EVs load can be shifted to off-peak time period using V2V topology in real world application. According to the results, it is understood that the isolated and high-power version of the designed converter is suitable for charging stations.

Višerazinski izmjenjivač step sinus pulse width modulation (SSPWM) dizajniran je za reguliranje opterećenja s reducirajućim nelinearnim učincima kao harmonike. Višerazinski izmjenjivač ima šest prekidača za svaku fazu a...

The copyright violations in digital images and the violations of the privacy of personal data are happened with the development of technology and the widespread use of the internet. The usage of watermarks in digital images provides high protection to image owners in copyright protection and in protection of personal data. In this paper, watermarks have been added to digital images by using discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) methods, respectively. “Gaussian”, “shot”, “salt & pepper” and “speckle” noises are added to watermarked images, respectively. The original image and the watermark have been extracted from the watermarked image after adding noise. The original image and watermark have been re-extracted from the optimized watermarked image by using the bacterial foraging optimization (BFO) technique. In this step, the particle swarm optimization (PSO) algorithm has been used to set the best position of the chemotactic parameters of the BFO algorithm. The peak signal to noise ratio (PSNR), normalized cross correlation (NCC) and image fidelity (IF) values have been calculated and compared to see the success performance of watermarking techniques and optimization techniques.

With the transition to the information society, all areas of our lives are rapidly shifting to the digital environment. From education to health, from citizenship procedures to social life, all areas of our lives are interacting in the digital cyber environment. In this process, smart cities, smart networks, and smart factories, especially critical infrastructures required for social life, have become open to the intranet and then to the internet for reasons such as efficient efficiency, speed, remote maintenance, and maintenance. Along with this process, these systems have faced new threat surfaces. One of the components that play an essential role in the operation of these systems is embedded systems. These systems contribute significantly to the effective operation of essential infrastructures. However, any interruption in these systems can lead to significant negative consequences, including economic damage and human life. Although there are many studies on the functioning of embedded systems, there are not enough studies on the cyber security analysis of these systems. For this reason, in this study, attack and detection analyses for embedded systems have been carried out on the test environment created using real systems. The study aims to detect passive attack, which is more difficult to detect than active attacks on the system, by using artificial intelligence algorithms. The analysis results have shown that the attack has been detected in a high ratio. It has been evaluated that the study will significantly contribute to other studies on the security of embedded systems.