The scatter form of multimedia data such as text, image, audio, and video posted regularly in the social media may contain useful information for the organizations. But, this information should be derived with the use of some form of analysis known as Multimodal Sentiment Analysis (MSA). But, there is a lack of pro per analytic tools for such analysis. This paper presents a thorough overview of more than fifty most recent MSA research articles to find the gaps in terms of tasks, approaches theories and applications used till date. There seems to be no single approach, theory, and tool which can support MSA. The study showed that each and every mode presents different difficulties which have not been fully solved yet, such as feature points of a face, voice clarity in audio, video summarization and so on, and are great research opportunities for the future researchers. Also, this research recommends a list of existing and upcoming difficulties and opportunities of MSA research.

XML signature wrapping attack poses a great threat to the integrity of web services. This is evident in the losses suffered by the Amazon Company in the past. This paper presents a new algorithm called the Spatial Information Approach (SIA). The paper forges the digital signature based on the principle of ratio signature which is adopted from a study in cancer detection. SIA creates a spatial map of the entire SOAP message where its performance is compared to SESoap, another current method that faithfully constructs a digital signature from the whole message. The experiment was conducted in a controlled lab environment by using open source tools in Linux Ubuntu environment. Based on the experiment conducted, SIA is superior to SESoap in terms of performance that shows improvement of the processing speed by approximately 4-14% for messages of size 50 Kb to 750 Kb.