SVBE: searchable and verifiable blockchain-based electronic medical records system

Central management of electronic medical systems faces a major challenge because it requires trust in a single entity that cannot effectively protect files from unauthorized access or attacks. This challenge makes it difficult to provide some services in central electronic medical systems, such as file search and verification, although they are needed. This gap motivated us to develop a system based on blockchain that has several characteristics: decentralization, security, anonymity, immutability, and tamper-proof. The proposed system provides several services: storage, verification, and search. The system consists of a smart contract that connects to a decentralized user application through which users can transact with the system. In addition, the system uses an interplanetary file system (IPFS) and cloud computing to store patients’ data and files. Experimental results and system security analysis show that the system performs search and verification tasks securely and quickly through the network.

Big Data Handling Approach for Unauthorized Cloud Computing Access

Nowadays, cloud computing is one of the important and rapidly growing services; its capabilities and applications have been extended to various areas of life. Cloud computing systems face many security issues, such as scalability, integrity, confidentiality, unauthorized access, etc. An illegitimate intruder may gain access to a sensitive cloud computing system and use the data for inappropriate purposes, which may lead to losses in business or system damage. This paper proposes a hybrid unauthorized data handling (HUDH) scheme for big data in cloud computing. The HUDH scheme aims to restrict illegitimate users from accessing the cloud and to provide data security provisions. The proposed HUDH consists of three steps: data encryption, data access, and intrusion detection. The HUDH scheme involves three algorithms: advanced encryption standards (AES) for encryption, attribute-based access control (ABAC) for data access control, and hybrid intrusion detection (HID) for unauthorized access detection. The proposed scheme is implemented using the Python and Java languages. The testing results demonstrated that the HUDH scheme can delegate computation overhead to powerful cloud servers. User confidentiality, access privilege, and user secret key accountability can be attained with more than 97% accuracy.

CRIMES ASSOCIATED WITH THE USE OF ELECTRONIC PAYMENT MEANS: METHODS AND TRACE INFORMATION

The results of a forensic analysis of typical methods of committing crimes involving the use of electronic payment methods are presented. It is shown that the basis of this criminal activity are the methods of social engineering based on the application of the achievements of modern information and communication technologies, as well as on actions and approaches through which offenders gain unauthorized access to the personal data of the victim. Taking into account the study of the stages of the mechanism of the considered criminal acts, the sources of trace information are formulated, reflecting the processes of interaction of participants in a criminal event with each other and with the environment.

AES Image Encryption (Advanced Encryption Standard)

An Image Encryption and Decryption Using AES (Advance Encryption Standard) Algorithm is proposed in the project. Due to increasing use of image in various field, it is very important to protect the confidential image data from unauthorized access. The design uses the iterative approach with block size of 128 bit and key size of 128, 192 or 256 bit. The numbers of round for key size of 256 bits is 14 , for 128 bits is 10 and for 192 bits is 12. As secret key increases the security as well as complexity of the cryptography algorithms. In this paper , an algorithm in which the image is an input to AES Encryption to get the encrypted image and then input it to AES Decryption to get the original image is proposed and explained which will further be implemented by me. The paper shows the study in which a system could be used for effective image data encryption and key generation in diversified application areas, where sensitive and confidential data needs to be transmitted along with the image.

Theoretical and practical considerations regarding the illegal access to a computer system in the Romanian Criminal Law

The article analyzes the legal framework for regulating the crime of illegal access to a computer system in the Romanian legal system, with a brief foray into the history of criminalization of unauthorized access to a computer system, continues with the indication of the normative text in force, after which it describes the structure and legal content of the crime, with specific references to recent relevant criminal jurisprudence.

Preventing data leakage by securing chat session with randomized session ID

Messaging applications have become one of the largest and most popular smartphone applications. It includes the capacity for the users to communicate between themselves via text messages, photos and files. It is necessary to safeguard all messages. Privacy is one of the biggest issues which most individuals in the world of instant messaging ignore. Although several instant messaging applications offer varying security for users, the weaknesses and danger of data assault are increasing. Not just business discussions, our data must also be safeguarded during everyday discussions since data is very sensitive for everybody, and data protection is very crucial to prevent undesired loss of information. To address these types of weaknesses and hazards associated with data attacks, we require an encrypted messaging protocol and also hide IP address method for a safe interaction. This paper's goal is to protect conversations from targeted attacker by securing the communication between user and hide IP address from unauthorized access.

AES Image Encryption

An Image Encryption and Decryption Using AES (Advance Encryption Standard) Algorithm is proposed in the project. Due to increasing use of image in various field, it is very important to protect the confidential image data from unauthorized access. The design uses the iterative approach with block size of 128 bit and key size of 128, 192 or 256 bit. The numbers of round for key size of 256 bits is 14, for 128 bits is 10 and for 192 bits is 12. As secret key increases the security as well as complexity of the cryptography algorithms. In this paper , an algorithm in which the image is an input to AES Encryption to get the encrypted image and then input it to AES Decryption to get the original image is proposed and explained which will further be implemented by me.The paper shows the study in which a system could be used for effective image data encryption and key generation in diversified application areas, where sensitive and confidential data needs to be transmitted along with the image.

Big Data Handling Approach for Unauthorized Access of Cloud Computing

Nowadays, cloud computing is one of the important and rapidly growing paradigms that extend its capabilities and applications in various areas of life. The cloud computing system challenges many security issues, such as scalability, integrity, confidentiality, and unauthorized access, etc. An illegitimate intruder may gain access to the sensitive cloud computing system and use the data for inappropriate purposes that may lead to losses in business or system damage. This paper proposes a hybrid unauthorized data handling (HUDH) scheme for Big data in cloud computing. The HUDU aims to restrict illegitimate users from accessing the cloud and data security provision. The proposed HUDH consists of three steps: data encryption, data access, and intrusion detection. HUDH involves three algorithms; Advanced Encryption Standards (AES) for encryption, Attribute-Based Access Control (ABAC) for data access control, and Hybrid Intrusion Detection (HID) for unauthorized access detection. The proposed scheme is implemented using Python and Java language. Testing results demonstrate that the HUDH can delegate computation overhead to powerful cloud servers. User confidentiality, access privilege, and user secret key accountability can be attained with more than 97% high accuracy.

Multiplicative knapsack injectivity as condition of effective unauthorized access protection

The mathematical modelling of data protection systems based on multiplicative knapsack is considered. In particular, development of cryptographic solution to hierarchic access control problem is represented. Previously in research the authors has formulated the requirements to knapsack in order to apply these to a hierarchic access control problem based on the requirements for similar models. Here in the article the possibility of practical implementation of the construction of such knapsacks is pointed. Based on special mathematical model for multiplicative knapsacks generalized sufficient condition of multiplicative knapsack injectivity is formulated and proved in the article. Known sufficient conditions of multiplicative knapsack injectivity are special cases of authors condition. The mathematical apparatus of additive knapsacks for building multiplicative vector is shown.

An Intrusion Detection System for Network Security Using Recurrent Neural Network

To maintain the security of vulnerable network is the most essential thing in network system; for network protection or to eliminate unauthorized access of internal as well as external connections, various architectures have been suggested. Various existing approaches has developed different approaches to detect suspicious attacks on victimized machines; nevertheless, an external user develops malicious behaviour and gains unauthorized access to victim machines via such a behaviour framework, referred to as malicious activity or Intruder. A variety of supervised machine algorithms and soft computing algorithms have been developed to distinguish events in real-time as well as synthetic network log data. On the benchmark data set, the NLSKDD most commonly used data set to identify the Intruder. In this paper, we suggest using machine learning algorithms to identify intruders. A signature detection and anomaly detection are two related techniques that have been suggested. In the experimental study, the Recurrent Neural Network (RNN) algorithm is demonstrated with different data sets, and the system’s output is demonstrated in a real-time network context.