Bibliographic record
Abstract
In the era of digital transformation, the dependence on information technology services and products has increased significantly. Accordingly, the challenges in information security and cyber security have increased. Social distancing, while playing an important role in containing the spread of COVID-19, increases the risk of infected workstations, unauthorized access, data leakage, malicious code execution, and all the types of risks that come with working in a vulnerable environment. Computer security, cyber security or information security - protection of computer systems and control points of networks from its interference, unauthorized use or damage to hardware, software and electronic data, as well as from destruction and violation of the services they provide to users. This area is becoming more and more important for computer systems, the Internet and wireless networks such as Bluetooth and Wi-Fi. Because of its complexity, in terms of politics and technology, cyber security is also one of the main challenges in modern life. Cyber security is one of the most important fields in today's world. This branch is connected with such demanding professions and specialties as: security analyst, security engineer, security architect, security administrator, security specialist, consultant, etc. Types of Malware - Malware (Malware); computer virus; mobile media means; Trojan (Trojan Horse); rootkit; Backdoor (Backdoor); Worm (Computer worm); Keylogger (Keylogger). In 2003, the computer virus Slammer penetrated the management system of the electric distribution network and slowed down its operation, which also caused the speed of management to slow down. As a result, even a small incident like a tree falling on a power line can set off a serious chain reaction. In particular, in the US state of Ohio, the voltage began to change, and the equipment, which was installed to prevent the cascade effect, failed to isolate the high voltage area in time. As a result, 8 US states, 2 Canadian provinces (a total of 50 million people) were left without electricity and services dependent on it. This example shows what can result from a little carelessness, ignoring security issues, in the digital information space. Today, cyber security is at risk like never before.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.027 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".