Comparison study of machine learning classifiers to detect anomalies

In this era of Internet ensuring the confidentiality, authentication and integrity of any resource exchanged over the net is the imperative. Presence of intrusion prevention techniques like strong password, firewalls etc. are not sufficient to monitor such voluminous network traffic as they can be breached easily. Existing signature based detection techniques like antivirus only offers protection against known attacks whose signatures are stored in the database.Thus, the need for real-time detection of aberrations is observed. Existing signature based detection techniques like antivirus only offers protection against known attacks whose signatures are stored in the database. Machine learning classifiers are implemented here to learn how the values of various fields like source bytes, destination bytes etc. in a network packet decides if the packet is compromised or not . Finally the accuracy of their detection is compared to choose the best suited classifier for this purpose. The outcome thus produced may be useful to offer real time detection while exchanging sensitive information such as credit card details

Policy resolution of shared data in online social networks

Online social networks have practically a go-to source for information divulging, social exchanges and finding new friends. The popularity of such sites is so profound that they are widely used by people belonging to different age groups and various regions. Widespread use of such sites has given rise to privacy and security issues. This paper proposes a set of rules to be incorporated to safeguard the privacy policies of related users while sharing information and other forms of media online. The proposed access control network takes into account the content sensitivity and confidence level of the accessor to resolve the conflicting privacy policies of the co-owners

Trust Enhanced Role Based Access Control Using Genetic Algorithm

Improvements in technological innovations have become a boon for business organizations, firms, institutions, etc. System applications are being developed for organizations whether small-scale or large-scale. Taking into consideration the hierarchical nature of large organizations, security is an important factor which needs to be taken into account. For any healthcare organization, maintaining the confidentiality and integrity of the patients’ records is of utmost importance while ensuring that they are only available to the authorized personnel. The paper discusses the technique of Role-Based Access Control (RBAC) and its different aspects. The paper also suggests a trust enhanced model of RBAC implemented with selection and mutation only ‘Genetic Algorithm’. A practical scenario involving healthcare organization has also been considered. A model has been developed to consider the policies of different health departments and how it affects the permissions of a particular role. The purpose of the algorithm is to allocate tasks for every employee in an automated manner and ensures that they are not over-burdened with the work assigned. In addition, the trust records of the employees ensure that malicious users do not gain access to confidential patient data

Predicting depression using deep learning and ensemble algorithms on raw twitter data

Social network and microblogging sites such as Twitter are widespread amongst all generations nowadays where people connect and share their feelings, emotions, pursuits etc. Depression, one of the most common mental disorder, is an acute state of sadness where person loses interest in all activities. If not treated immediately this can result in dire consequences such as death. In this era of virtual world, people are more comfortable in expressing their emotions in such sites as they have become a part and parcel of everyday lives. The research put forth thus, employs machine learning classifiers on the twitter data set to detect if a person’s tweet indicates any sign of depression or not

Investigation of nano lipid vesicles of methotrexate for anti-rheumatoid activity

Prabhakara Prabhu1, Rakshith Shetty1, Marina Koland1, K Vijayanarayana3, KK Vijayalakshmi2, M Harish Nairy1, GS Nisha11Department of Pharmaceutics, Nitte University, NGSM Institute of Pharmaceutical Sciences, Paneer, Deralakatte, Mangalore, Karnataka, India; 2Department of Applied Zoology, Mangalore University, Konaje, Mangalore, Karnataka, India; 3Department of Pharmacy Practice, Manipal University, Manipal College of Pharmaceutical Sciences, Manipal, Karnataka, IndiaBackground: The purpose of this study was to formulate and evaluate nano lipid vesicles of methotrexate (MTX) for its anti-rheumatoid activity.Methods: In this study the principle of both active as well as passive targeting using MTX-loaded stealth liposomes as per the magic gun approach was followed. Stealth liposomes of MTX were prepared by thin-film hydration method using a PEGylated phospholipid-like DSPE-MPEG 2000. Similarly, conventional liposomes were prepared using phospholipids like DPPC and DSPC. Conventional liposomes were coated with a hydrophilic biocompatible polymer like chitosan. They were investigated for their physical properties and in vitro release profile. Further, in vivo screening of the formulations for their anti-rheumatoid efficacy was carried out in rats. Rheumatoid arthritis was induced in male Wistar-Lewis rats using complete Freund’s adjuvant (1 mg/mL Mycobacterium tuberculosis, heat killed in mineral oil).Results: It was found that chitosan coating of the conventional liposomes increased the physical stability of the liposomal suspension as well as its entrapment efficiency. The size of the unsonicated lipid vesicles was found to be in the range of 8–10 µm, and the sonicated lipid vesicles in the range of 210–260 nm, with good polydispersity index. Further, chitosan-coated conventional liposomes and the PEGylated liposomes released the drug for a prolonged period of time, compared to the uncoated conventional liposomes. It was found that there was a significant reduction in edema volume in the rat group administered with the test stealth liposomal formulations and chitosan-coated conventional liposomes (PEGylated and chitosan-coated conventional) compared to that of the control and standard (administered with free MTX) group of rats. PEGylated liposomes showed almost equal efficacy as that of the chitosan-coated conventional liposomes.Conclusion: Lipid nano vesicles of MTX can be administered by intravenous route, whereby the drug selectively reaches the target site with reduced toxicity to other organs.Keywords: methotrexate, stealth liposomes, conventional liposomes, chitosan coating, targeted delivery, anti-rheumatoid efficac

Collusion-resistant multiparty data sharing in social networks

The number of users on online social networks (OSNs) has grown tremendously over the past few years, with sites like Facebook amassing over a billion users. With the popularity of OSNs, the increase in privacy risk from the large volume of sensitive and private data is inevitable. While there are many features for access control for an individual user, most OSNs still need concrete mechanisms to preserve the privacy of data shared between multiple users. The proposed method uses metrics such as identity leakage (IL) and strength of interaction (SoI) to fine-tune the scenarios that use privacy risk and sharing loss to identify and resolve conflicts. In addition to conflict resolution, bot detection is also done to mitigate collusion attacks. The final decision to share the data item is then ascertained based on whether it passes the threshold condition for the above metrics

3rd National Conference on Image Processing, Computing, Communication, Networking and Data Analytics

This volume contains contributed articles presented in the conference NCICCNDA 2018, organized by the Department of Computer Science and Engineering, GSSS Institute of Engineering and Technology for Women, Mysore, Karnataka (India) on 28th April 2018