You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: No Peek: A Survey of private distributed deep learning 
Chapter Title:  No peek rule 
1. Abstract of Cited Paper (BIB001):  Regulations intended to improve health care data access have created new security risks along with headaches for patients and practitioners. 
2. Abstract of Cited Paper (BIB002):  This report contains the findings of a committee charged with reviewing the HIPAA privacy rule and its impact on health research. The committee found that the rule does not adequately protect the privacy of peopleâ€™s personal health information and hinders important health research. It recommends that Congress authorize the development of an entirely new approach to protecting personal health information in research that applies privacy, data security, and accountability standards uniformly to information used in all health-related research regardless of who funds or conducts it. 
3. Abstract of Cited Paper (BIB003):  The rise in the use of mobile devices, such as smartphones, tablet personal computers, and wireless medical devices, as well as the wireless networks that enable their use, has raised new concerns for data security and integrity. Standardized Health Insurance Portability and Accountability Act of 1996 (HIPAA)-compliant electronic data security that will allow ubiquitous use of mobile health technologies is needed. The lack of standardized data security to assure privacy, to allow interoperability, and to maximize the full capabilities of mobile devices presents a significant barrier to care. The purpose of this article is to provide an overview of the issue and to encourage discussion of this important topic. Current security needs, standards, limitations, and recommendations for how to address this barrier to care are discussed.

Literature Review:
We refer to techniques of distributed deep learning that do not look at raw data once it leaves the client as satisfying the property of 'no peek'. No peek is necessitated by trust and regulatory issues. For example, hospitals are typically not allowed to share data with for-profit entities due to trust issues. They also are unable to share it with external entities (data cannot physically leave the premises) due to limited consent of the patients, and regulations such as HIPAA BIB001  BIB002 BIB003 BIB004 that prevent sharing many aspects of the data to external entities. Some techniques go a step ahead by also not revealing details of the model architecture as well. In these techniques, neither the server nor client can access the details of the other's architecture or weights.