Biblio

In a computer world, to identify anyone by doing a job or to authenticate by checking their identification and give access to computer. Access Control model comes in to picture when require to grant the permissions to individual and complete the duties. The access control models cannot give complete security when dealing with cloud computing area, where access control model failed to handle the attributes which are requisite to inhibit access based on time and location. When the data outsourced in the cloud, the information holders expect the security and confidentiality for their outsourced data. The data will be encrypted before outsourcing on cloud, still they want control on data in cloud server, where simple encryption is not a complete solution. To irradiate these issues, unlike access control models proposed Attribute Based Encryption standards (ABE). In ABE schemes there are different types like Key Policy-ABE (KP-ABE), Cipher Text-ABE (CP-ABE) and so on. The proposed method applied the access control policy of CP-ABE with Advanced Encryption Standard and used elliptic curve for key generation by using multi stage encryption which divides the users into two domains, public and private domains and shuffling the data base records to protect from inference attacks.

This computer era leads human to interact with computers and networks but there is no such solution to get rid of security problems. Securities threats misleads internet, we are sometimes losing our hope and reliability with many server based access. Even though many more crypto algorithms are coming for integrity and authentic data in computer access still there is a non reliable threat penetrates inconsistent vulnerabilities in networks. These vulnerable sites are taking control over the user's computer and doing harmful actions without user's privileges. Though Firewalls and protocols may support our browsers via setting certain rules, still our system couldn't support for data reliability and confidentiality. Since these problems are based on network access, lets we consider TCP/IP parameters as a dataset for analysis. By doing preprocess of TCP/IP packets we can build sovereign model on data set and clump cluster. Further the data set gets classified into regular traffic pattern and anonymous pattern using KNN classification algorithm. Based on obtained pattern for normal and threats data sets, security devices and system will set rules and guidelines to learn by it to take needed stroke. This paper analysis the computer to learn security actions from the given data sets which already exist in the previous happens.

Workarounds to computer access in healthcare are sufficiently common that they often go unnoticed. Clinicians focus on patient care, not cybersecurity. We argue and demonstrate that understanding workarounds to healthcare workers’ computer access requires not only analyses of computer rules, but also interviews and observations with clinicians. In addition, we illustrate the value of shadowing clinicians and conducing focus groups to understand their motivations and tradeoffs for circumvention. Ethnographic investigation of the medical workplace emerges as a critical method of research because in the inevitable conflict between even well-intended people versus the machines, it’s the people who are the more creative, flexible, and motivated. We conducted interviews and observations with hundreds of medical workers and with 19 cybersecurity experts, CIOs, CMIOs, CTO, and IT workers to obtain their perceptions of computer security. We also shadowed clinicians as they worked. We present dozens of ways workers ingeniously circumvent security rules. The clinicians we studied were not “black hat” hackers, but just professionals seeking to accomplish their work despite the security technologies and regulations.
 

Workarounds to computer access in healthcare are sufficiently common that they often go unnoticed. Clinicians focus on patient care, not cybersecurity. We argue and demonstrate that understanding workarounds to healthcare workers’ computer access requires not only analyses of computer rules, but also interviews and observations with clinicians. In addition, we illustrate the value of shadowing clinicians and conducing focus groups to understand their motivations and tradeoffs for circumvention. Ethnographic investigation of the medical workplace emerges as a critical method of research because in the inevitable conflict between even well-intended people versus the machines, it’s the people who are the more creative, flexible, and motivated. We conducted interviews and observations with hundreds of medical workers and with 19 cybersecurity experts, CIOs, CMIOs, CTO, and IT workers to obtain their perceptions of computer security. We also shadowed clinicians as they worked. We present dozens of ways workers ingeniously circumvent security rules. The clinicians we studied were not “black hat” hackers, but just professionals seeking to accomplish their work despite the security technologies and regulations.