Steganography is the technique for exchanging concealed secret information in a way to avoid suspicion. The aim of Steganography is to transfer secrete message to another party by hiding the data in a cover object, so that the imposter who monitors the traffic should not distinguish between genuine secret message and the cover object. This paper presents the comparative study and performance analysis of different image Steganography methods using various types of cover media ((like BMP/JPEG/PNG etc.) with the discussion of their file formats. We also discuss the embedding domains along with a discussion on salient technical properties, applications, limitations, and Steganalysis.

This paper presents an image Steganography algorithm that can work for cover images of multiple formats. Having a single algorithm for multiple image types provides several advantages. For example, we can apply uniform security policies across all image formats, we can adaptively select the most suitable cover image based on data length, network bandwidth and allowable distortions, etc. We present our algorithm based on the abstract concept of image components that can be adapted for JPEG, Bitmap, TIFF and PNG cover images. To the best of our knowledge, the proposed algorithm is the first Steganography algorithm that can work for multiple cover image formats. In addition, we have utilized concepts like capacity pre-estimation, adaptive partition schemes and data spreading to embed secret data with enhanced security. The proposed method is tested for robustness against Steganalysis with favorable results. Moreover, comparative results for the proposed algorithm are very promising for three different cover image formats.

Over-/underspeeding is one of the leading causes of road accidents. Traditional systems of detecting and reporting speed-limit violations are not suitable for smart cities. Even the sophisticated conventional systems that use cameras or RFIDs for automating speed-limit violations have several drawbacks, including cost, complexity, reliability, and maintenance. In this paper, we present two systems based on the Internet of Vehicles (IoV) to automatically detect speed-limit violations and autonomously report the committed violations to the authorities. Our systems require no extra hardware or equipment: only the On-Board Unit (OBU), the Road Side Unit (RSU), and the Cloud Server software have to be updated to have a fully functioning system as long as the IoV infrastructure is deployed. One of the systems will be installed on the OBU. A second alternative system design is to use Cloud Servers (CSs) and the IoV beacons that are sent from the vehicles. Additionally, unlike the existing systems installed in specific locations, all roads in the smart cities and highways will be fully monitored. Adaptive fine calculation according to new dynamic policies can be easily integrated into the proposed system. Furthermore, the proposed system can accurately operate in all weather conditions. Moreover, it allows the dynamic adjustment of the speed limits according to the current weather conditions. We have validated the proposed system by building a prototype system that effectively and accurately detects and reports over-/underspeed traffic violations alongside any road.